WORLD METEOROLOGICAL ORGANIZATION GLOBAL ATMOSPHERE WATCH
No. 155
1st INTERNATIONAL EXPERT MEETING on SOURCES and MEASUREMENTS of NATURAL RADIONUCLIDES APPLIED to CLIMATE and AIR QUALITY STUDIES
Gif sur Yvette, France, 3 - 5 June 2003
APRIL 2004 WORLD METEOROLOGICAL ORGANIZATION GLOBAL ATMOSPHERE WATCH
No. 155
1st INTERNATIONAL EXPERT MEETING on SOURCES and MEASUREMENTS of NATURAL RADIONUCLIDES APPLIED to CLIMATE and AIR QUALITY STUDIES
Sponsored by WMO/IAEA/CNRS
Gif sur Yvette, France, 3- 5 June 2003
WMO TD No. 1201 Table of Contents
1. FOREWORD...... iii
2. EXECUTIVE SUMMARY ...... 1
3. WORKSHOP RECOMMENDATION SUMMARY...... 3
4. WORKING GROUP REPORTS
4.1 Source Processes and Source Algorithms for Global 222Rn...... 5 4.2 Global Radionuclide Measurements...... 11 4.3 Modelling Radionuclides ...... 20
5. EXPERT PRESENTATIONS
Natural Radionuclide Research and Observations in the Global Atmosphere Watch (GAW) and World Climate Research Programmes (WCRP) (Leonard Barrie and Gilles Sommeria-Klein)...... 27
Issues and Challenges of Using Natural Radionuclides As Tracers for Atmospheric Studies (Hsi-Na (Sam) Lee)...... 30
Variation of 222Rn Flux and its Implications for Atmospheric Tracer Studies Franz Conen (presented by Stephen Schery)...... 35
Progress on Global 222Rn Flux Maps and Recommendations for Future Research (Stephen Schery)...... 43
EML Global Network For Measuring Radionuclides (Colin Sanderson and Hsi-Na (Sam) Lee)...... 48
222Rn in the Atmospheric Boundary Layer: A Contrast Between Measurements Made at a Baseline Site in the Southern Ocean and a Network of Sites in East Asia ( Wlodek Zahorowski,) ...... 53
Natural Radionuclides as Tracers in Multi-Compartment Transport Models (Johann Feichter)...... 61
Simulation of Cosmogenic Radionuclide Production in the Earth Atmosphere (Jozef Masarik) ...... 65
Measurements of Cosmic-Ray Neutron Spectra in the Stratosphere: a Benchmark for Calculations of Cosmogenic Nuclide Production (Paul Goldhagen)...... 68
Beryllium-7 and 222Rn as the Atmospheric Tracer - Observation at the Summit of Mt. Fuji Located in the Free Troposphere (Yasuhito Igarashi)...... 75
14CO and its Application in Studies of Atmospheric Chemistry and Transport (Patrick Jöckel and Carl A. M. Brenninkmeijer)...... 81
Meteorological Traceability In Radionuclide Measurements, Present Status And Future Challenges (Aleš Fajgelj)...... 84
i
Annex A: Final Announcement ...... 85
Annex B: Workshop Agenda ...... 87
Annex C: List of Contributors and Participants...... 89
ii 1. Foreword
The use of radionuclides in the atmosphere to understand atmospheric dynamics, pollutant dispersion and pollutant removal processes has a long history punctuated by the landmark book of C.E. Junge on Air Chemistry and Radioactivity published in 1963 (Academic Press). Since that time, considerable attention has been paid to the cycles of natural radionuclides originating from continental soils and from cosmogenic production in the upper troposphere and lower stratosphere. Systematic monitoring of radionuclides in the atmosphere was first motivated by the need to understand the effects of atmospheric nuclear bomb fallout which occurred mostly from tests in the 1960s. Natural radionuclides in suspended particulate matter in the atmosphere (commonly known as aerosols) were measured simultaneously with anthropogenic radionuclides in fallout. The Environmental Measurements Laboratory (EML) that was, until recently, in the US Department of Energy and now in the Department of Homeland Security, led the world in the systematic observations, data archiving and reporting of fallout levels in aerosols and precipitation.
Atmospheric chemistry, air pollution and climate-related issues became prominent after the 1970s. Networks for monitoring air composition were established regionally and globally and regional-to-global chemical transport models were developed. These models simulate the pathways of atmospheric chemicals from source to sink incorporating processes of transport and dispersion, chemical transformation, dry deposition and precipitation scavenging. They use a quantitative estimate of the source of a chemical and mass conservation equations incorporated into models developed for weather forecasting and climate. During the past three decades, the largely separate communities making observations and modeling of natural radionuclides and of chemical constitutents began to merge. The value of natural radionuclide tracers in atmospheric chemistry research and assessment has been recognized. Thus, at many of the Regional, Global and Contributing-partner stations in the Global Atmosphere Watch (GAW) network of the World Meteorological Organization (WMO), natural radionuclides are measured. A series of global chemical transport model intercomparisons supported by the World Climate Research Programme (WCRP) have included simulations of the atmospheric cycle of 222Rn and its particulate progeny 210 Pb as surrogates for the SO2 - sulphate system. However, much remains to be done to improve the utility of natural radionuclides in atmospheric research. Quantitative estimates of radionuclide sources used by the modelling community have not been changed for a decade despite considerable new information at hand. Techniques of measuring radionuclides need to be standardized and harmonized, observations need to be collected and archived with information on uncertainty and finally, research to generate even better source functions is needed.
The purpose of this international meeting was to bring different research communities together to document the current situation with respect to measurements of natural radionuclides and modelling of their global cycles as well as to make recommendations for improving sources, measurements and modelling. It was kindly hosted by M. Ramonet, L. Jourdheuil and colleagues at the Laboratory of Science of Climate and the Environment (LSCE), CEA/CNRS, France. On behalf of the co-sponsors WMO, WCRP (G. Sommeria), IAEA (G. Voigt) and EML, we wish to thank all contributors (Annex C) and to acknowledge the significant role played by the science advisory group consisting of Y. Balkanski, Y. Igarashi, J. Feichter, I. Levin, C. Sanderson, S. Schery and W. Zahorowski.
Leonard A. Barrie (co-chair) H.N. (Sam) Lee (co-chair) WMO/GAW EML
iii
2. EXECUTIVE SUMMARY
Natural radionuclides including 222Rn, 220Rn, 212Pb, 210Pb, 7Be, 10Be and 14CO have been widely used to examine a large variety of relevant atmospheric processes and to validate the comprehensive global chemical transport models. Routine measurements of these naturally occurring radionuclides in a global monitoring network for atmospheric composition support global climate change and air quality research. The effective use of radionuclide observations is limited by the accuracy of source functions used by models and by a globally uncoordinated approach to measurements, data archiving and data quality assurance. The Environmental Measurements Laboratory (EML) in the United States assists GAW in developing the capacity of the global monitoring network and provided support for the co-chair of this meeting. Currently, there are 21 regionally representative stations measuring 222Rn that are operated by GAW and its partners.
Evaluations of atmospheric chemical transport models rely in part on accurate estimates of the 222Rn source term. Our knowledge of the magnitude and the distribution of 222Rn flux to the atmosphere over the Earth’s surface is still in a fairly primitive state due to insufficient research. Mapping the variation of 222Rn flux over the Earth’s surface requires knowledge of many factors, such as soil moisture, atmospheric precipitation, soil temperature and soil type that control the release of 222Rn gas to the atmosphere. 222Rn is produced by the decay of 226Ra in soil. Suitable global datasets for predicting 222Rn emissions are only just now becoming available. However, global information on the crucial factor of 226Ra in soil is incomplete. Two new schemes for 222Rn flux parameterizations are proposed for use by modellers.
222Rn concentrations in surface air are measured using either a two-filter or one-filter method. At present, the two-filter method is the recommended technique for measuring low level 222Rn in surface air. However, under some circumstances and for some applications, single filter observations are adequate. There are two types of instrument using the two-filter method. One instrument developed by EML uses single air flow and the other developed by Australian Nuclear Science and Technology Organization in Australia uses a dual air flow. The calibration procedure for the two-filter instruments should be routinely performed using a 222Rn calibration source traceable to a primary source. Sensitivity, accuracy and instrumental background of two-filter instruments should be evaluated on a regular basis. Aircraft measurement of 222Rn is another important component for understanding atmospheric processes and improving model validation. Two methods have been used for determining vertical profiles of 222Rn concentration: (i) an advanced electrostatic collection technique for measuring in real-time and (ii) sampling air in high- pressure tanks for analysis after the flight. The observations of vertical profiles of 222Rn concentrations are sparse. Currently, 210Pb and 7Be surface air concentrations are measured routinely at the GAW stations by weekly cumulative filtration and subsequent gamma counting. These are summarized in Table 2 in this report.
At present, very few measurements exist to assess the rapid trans-continental transport either in the Northern or in the Southern Hemisphere. Also, none of the current global transport models can capture the very wide variations of 222Rn concentrations in the upper troposphere over Hawaii. A systematic underestimate of 222Rn emissions in China might have caused this bias. The long-range transport of 222Rn gas provides a good test for the treatment of advection and diffusion in global models. Radionuclides, such as 210Pb, 7Be and 10Be, which condense on particle surfaces, provide tests of aerosols physical processes including wet and dry deposition. In the last decade, substantial progress has been made in the field of numerical simulation of cosmogenic nuclide production rates. The rates as functions of altitude, latitude, solar and geomagnetic field intensity are available. With the advent of new particle flux measurements, the quality of numerical models can be tested.
1 Taking into account the above issues concerning the source processes, measurement techniques, calibration procedures, data collection, data quality and model validation, an international group of 30 scientists from 12 countries summarized current knowledge of radionuclides used for atmospheric studies. In this report, they make constructive recommendations for improving applications of natural radionuclides in the atmosphere to climate and air quality studies.
Group Photo at the Meeting
2 3. WORKING GROUP RECOMMENDATIONS
The Source Processes and Source Algorithm Group recommended that:
1. Two new schemes for 222Rn flux parameterizations suggested in this workshop using large scale models and quality-controlled observations should be tested;
2. Our understanding of the global distribution of 226Ra in surface soils should be improved by collection of existing information in North America and Europe as well as parts of China, India and Russia and by encouraging new measurements in other regions where observations are completely lacking;
3. A number of 222Rn flux measurement campaigns should be conducted at 25-50 km intervals along transects across continents in addition to intensive measurements at a few sites to test proposed 222Rn flux parameterizations should be conducted;
4. Quality control of 222Rn flux measurements with the accumulator chamber technique should be improved. Too much published data lacks information on quality control and measurement conditions;
5. WMO/GAW, WCRP and IAEA should emphasize to their communities the need for better knowledge of 222Rn flux from the Earth’s surface, more accurate atmospheric222Rn flux measurements and to encourage in Africa and South America measurements of 226Ra in surface soil and 222Rn flux.
The Global Radionuclide Measurements Group recommended that:
6. When considering installation of new 222Rn detectors at WMO/GAW stations, preference should be given to a two-filter system, calibrated routinely using a 222Rn calibration source traceable to a primary standard;
7. For both double and single filter measuring systems, a regular maintenance schedule should be drawn up and should include aspects such as dust removal from sampling inlet systems and regular flow checks etc.;
8. Travelling standard calibrators (e.g. certified 222Rn sources used for calibration of two-filter systems) should be routinely checked for integrity and commutability;
9. Assessment of the variability arising from sampling should contribute to the overall uncertainty statement;
10. The efficiency of the counting system of the one-filter detectors should be monitored using a radioactive source (241Am) until a proper calibration can be performed using the method outlined in Section 5.2;
11. The one- filter system should be “normalized” to the dual filter system in order to make future data intercomparison and global database usage more reliable;
12. The comparison of the two-filter and one-filter instruments at the GAW Global Station in Pallas, Finland, should continue. Addition of other one-filter instruments for a period of a year should be considered;
3 13. Organize a comparison of the two-filter system at Cape Point, South Africa (identical to that at Cape Grim and MLO) with an LSCE one-filter instrument in order to review and merge historic observations obtained at Amsterdam Island with a one filter instrument;
14. A calibration procedure for the one-filter instrument should be adopted;
15. Recognizing that synoptic scales of motion cannot be traced with weekly mean observations, it is recommended that GAW Global and Regional stations making 7Be and 210Pb observations in parallel with 222Rn observations, consider measurements with maximum averaging time of 12 to 24 hours;
16. WMO and IAEA contact the CTBT Organization in Vienna to discuss possibilities of extending cooperation to include 7Be and 210Pb observations;
17. Long term continuous measurements of 222Rn made at GAW Global Regional and Contributing stations should be submitted to the GAW World Data Centre for Greenhouse Gases of the Japan Meteorological Agency;
18. A GAW World Data Centre for continuous observations of 7Be and 210Pb should be established and linked to the WDCGG in Japan;
19. Undertake monitoring 14CO at 6 GAW stations (one in each 300 latitude band) on a weekly or bi-weekly basis to track global OH changes.
The Modelling Applications of Radionuclides Group recommended that:
20. Future transport model evaluations such as AEROCOM should use one of the two suggested source functions for 222Rn and best quality-assured observations of 222Rn and 210Pb;
21. Collaborate with other communities interested in cosmogenic nuclides to conduct basic measurements of cross sections of nuclear reactions leading to the production of cosmogenic nuclides produced in the atmosphere. This is critical for a quantitative source function for 7Be, 10Be and 14CO;
22. Conduct observations of vertical profiles of nuclides particularly in the tropics to better understand vertical exchange;
23. Observing networks measuring chemical species and aerosols should include 222Rn and its particulate decay product 210Pb;
24. The global database of radionuclide observations including vertical profiles should be consolidated;
25. A homogeneous dataset for the concentrations of species produced in past atomic bomb tests of the 1960’s and 1970’s should be made available to the community through EML.
4 4.1 Source Processes and Source Algorithms for Global 222Rn
Contributors: S. D. Schery, H. N. Lee, M. Ramonet, S. Taguchi and H. Yamazawa
4.1.1 Introduction
The gas 222Rn has long played an important role for testing atmospheric chemistry transport models. Predictions of atmospheric 222Rn gas are sensitive to processes such as vertical transport in the atmosphere and trans-continental zonal transport. Since 222Rn is a precursor to the radionuclide 210Pb which attaches to aerosol in the atmosphere, additional processes such as aerosol attachment, dry deposition and wet removal can be a part of combined 222Rn/210Pb studies. An increasing number of WMO/GAW stations, and other atmospheric composition monitoring stations include 222Rn gas measurements. To better interpret data on atmospheric 222Rn gas and 210Pb aerosol observations and to test atmospheric chemical transport models, it is important to have a good understanding of the global source term for 222Rn gas.
Through a series of meetings initiated with focus questions (see section 4.1.6), the scientists from the working groups for WMO/GAW reviewed the understanding of 222Rn flux from the Earth’s surface and the need for new research. Given the existence of 21 continuous monitoring stations for atmospheric 222Rn concentrations at regionally representative sites(see section 4.2), it was felt that priority should be given to issues involving the source for atmospheric 222Rn gas. Thus, review of sources of other radionuclides was not attempted by this working group. Review of sources for other radionuclides was touched upon by other working groups.
Currently, many atmospheric chemistry transport models rely on simple parameterizations of the 222Rn source term such as a constant value of 1 atom cm-2s-1 for flux from land at lower latitudes with perhaps a much lower value at higher latitudes. The working group on source processes felt that more refined estimates of 222Rn flux from the Earth’s surface are long overdue. It is now clear that there are significant spatial and temporal variations of 222Rn flux over the Earth’s surface that need to be better and represented in models. In their papers for this workshop, Conen (2003) and Schery (2003) review the literature on 222Rn flux, provide preliminary suggestions for refined estimates of global 222Rn flux and suggest steps for developing more comprehensive and accurate estimates. Based on a review of their work and that in their references, the working group on source processes summarized the current understanding of 222Rn flux from the Earth’s surface in section 4.1.2 and provided the approaches given in Section 4.1.3 for improving the estimates of the global 222Rn source term.
4.1.2 222Rn Flux From The Earth’s Surface: The Current Understanding
At the fundamental level of porous media transport theory, the processes controlling 222Rn transport from soil to the atmosphere seem fairly well understood. Since 222Rn is a product of 226Ra decay, the 226Ra content of soil is of primary importance. A fraction of the 222Rn gas produced by 226Ra (the emanating fraction) is able to make it to the pore space where it is free to migrate towards the surface; the remaining fraction stays trapped in the soil. Migration to the surface is usually controlled by gaseous diffusion. Occasionally, advective flow can also be important such as that occurring when there is dropping atmospheric pressure over deep, dry soils. If the depth of soil to bedrock or the water table is less than the average distance of 222Rn diffusion before decay (the diffusion length), shallow soils will release less 222Rn to the atmosphere because the reservoir of 226Ra producing 222Rn is smaller. However, in many practical situations, it is difficult to know the fundamental soil properties, such as diffusivity and emanating fraction, directly controlling these fundamental processes. So, it is also common to identify indirect factors that are important for controlling 222Rn flux from soils. These factors ultimately affect 222Rn flux from soil by changing one or more of the primary processes listed above. Examples of important indirect factors are soil moisture, precipitation, soil temperature, and the physical and chemical properties of soil (such as reflected in soil classifications).
5 On a per unit surface area basis, the flux of 222Rn from lakes and oceans is usually much smaller than that from soil. This is because the concentration of 226Ra in water is typically much less than that in soil, and because the gaseous exchange between the surface water layer and the atmosphere is less effective than that which occurs with a porous media such as soil. In fact, the 222Rn flux from bodies of water is difficult to measure directly with methods such as the accumulator method. However, since the oceans cover such a large part of the Earth’s surface, the integrated effect of 222Rn release from the oceans can be important in some situations. An example is the understanding and modelling the atmospheric 222Rn “background” signal that occurs at certain marine monitoring sites.
In spite of a comparatively satisfactory understanding of the fundamental processes controlling release of 222Rn from soil to the atmosphere, our knowledge of the magnitude and distribution of 222Rn flux over the Earth’s surface is still in a fairly primitive state. There are several reasons for this situation. There are not enough measurements available for flux at different parts of the Earth’s surface to directly map the variation of 222Rn flux with position and time. In fact, there is some question as to whether we even have a good estimate of the annual average value of 222Rn flux from the Earth’s surface. Simplified estimates of the average 222Rn flux over the Earth’s surface, such as the commonly used value of 1 atom cm-2s-1 for ice-free land, typically come from analysis of a comparatively small number of direct, or indirect measurements, for which the rigor of the statistical sampling is less than convincing. In addition, there are sometimes questions of calibration and quality control of measurements that may have been designed for purposes other than a quantitative estimate of global 222Rn flux.
A more promising approach to mapping variations of 222Rn flux over the Earth’s surface appears to make use of knowledge about the distribution of indirect factors, such as soil moisture, soil temperature, and soil type, for which more global information is available than for 222Rn flux itself. Some initial steps have been taken in this direction. However, up to this point, efforts in this direction have been hampered by the lack of a calibrated set of 222Rn flux measurements suitable for identifying and studying correlations with indirect factors available in global datasets. Suitable global datasets for predicting these indirect factors are only just now becoming available. Global information on the crucial factor of 226Ra in soil, or surrogates such as gamma ray intensity, is presently sporadic at best.
4.1.3 Approaches For Improving Estimates Of Global 222Rn Flux
Since both Conen (2003) and Schery (2003) provide preliminary, but specific, suggestions for improving estimates of global 222Rn flux, the working group on source processes recommends that their suggestions be evaluated by new calculations with chemical transport models. Based on 222Rn flux measurements that show a trend with latitude, and other evidence, Conen (2003) suggests a new latitudinal dependence of average 222Rn flux that goes from 1 atom cm-2s-1 at 30o N to 0.2 atom cm-2s-1 at 70o N. Based on the work of Schery and Wasiolek (1998), Schery (2003) provides estimates of global 222Rn flux on a one degree by one degree grid for each month of the year using a parameterised porous media transport model and information on the global distribution of 226Ra, soil moisture, and surface temperature. Evaluation of this refinement of the 222Rn source term should hopefully be quick and indicate the most effective directions for further improvement in estimates of global 222Rn flux. For example, inclusion of a variable for depth-to- water table in the Schery and Wasiolek (1998) model, or improved 226Ra soil data for higher latitudes, might improve the agreement between Schery ‘s and Conen ‘s approaches at higher latitudes. If the difference cannot be resolved, a new and carefully calibrated approach for 222Rn flux measurements targeted to specific locations should be taken. Additional soil variables that are hopefully available in global datasets, might be identified to improve flux predictions. Examples might be new datasets on soil classification or surface geology.
In the longer term, it is clear that surface 226Ra plays a central role in controlling 222Rn flux from the Earth’s surface and its spatial variation. Presently, the major obstacle to providing, say, daily predictions of 222Rn flux over the Earth’s surface using output of auxiliary variables from GCMs (such as soil temperature and soil moisture) in porous media transport models is adequate
6 estimate of global surface 226Ra. If such surface 226Ra data become available, it is likely that almost real time estimates of global 222Rn flux will be possible. Any steps that can be taken to improve our understanding of its distribution in surface soils over the Earth’s surface are sorely needed. Surface 226Ra data can sometimes be used by itself to estimate spatial variation in 222Rn flux, but in any case it plays a central role as an input variable in the more sophisticated models of 222Rn flux. There is a fair amount of public information related to surface 226Ra and uranium available for the USA, Western Europe, and parts of China and India. However, little or no published information for a large geographical scale is available for regions such as Africa, South America, and Russia. All methods for improving estimates of surface 226Ra should be explored. The use of surrogate data should be considered. Information on such subjects as surface gamma radiation (radiometric data), uranium surveys, soil classifications, surface geology, and stream sediments may be helpful. Estimates of average conversion factors for surrogate data to get 226Ra concentration, or even 222Rn flux, are useful.
Direct mapping of 222Rn flux by measurement would be ideal, such as the measurements carried out for Ireland by Jennings et al., (2003). Unfortunately, this approach is not practical for the entire Earth’s surface. It would be desirable to use the accumulator method, which measures 222Rn gas in a chamber placed over the soil, for each season for each one degree by one degree grid section of the Earth’s land surface. Quality control of these measurements would be crucial, probably greater than that documented in the past, with carefully traced calibrations and/or intercomparison exercises. Alternatives to the accumulator technique are possible, such as the technique of measurement of the 210Pb deficit in profiles of surface soil (Graustein and Turekian, 1990). However, at the moment, these procedures seem even more labour intensive and unrealistic on the global scale.
A more practical measurement alternative for improving global 222Rn flux estimates might be to obtain a more modest number of accumulator measurements but targeted at carefully chosen locations. For example, measurements along an intermittent transect that ran from Norway down Western Europe into Spain and then to Egypt (summer and winter) would be extremely valuable for calibrating free parameters in models, such as the model of Schery and Wasiolek (1998). A spacing of about 25 to 50 km might be adequate. Carefully calibrated measurements are needed that cover a range of climate and soil conditions as predicted in global datasets from GCMs and, preferably, for regions where information is available on soil 226Ra. Present calibration data are particularly weak for arctic regions. A transect that ran from Alaska into the United States and then Mexico might also satisfy these requirements. Such data would then be available for vastly improved calibration of free parameters in the Schery and Wasiolek (1998) model, and any future models of this type.
In addition, a few fixed test sites where measurements of 222Rn flux, meteorological conditions, and soil variables could be made would be valuable. These sites could facilitate study and validation of fundamental models of 222Rn flux. For example, development and testing of models that use GCM output with 226Ra data to provide prediction of 222Rn flux might be carried out at such sites. The sites could also be used for testing of flux measuring equipment and intercomparison exercises.
Chemical transport predictions are now to a point that they are sensitive to values of 222Rn flux assumed for the oceans. The different constant values presently assigned to the oceans should be reviewed. It may be necessary to consider spatial and/or temporal variation. Direct measurements of flux from oceans, such as done with the accumulator method (Wilkening and Clements, 1975), are very difficult. Indirect measurements based on the radon deficit in surface water, such as carried out by Smethie et al. (1985), may be more practical. Analysis of atmospheric 222Rn data from baseline stations that measure air masses coming over long fetches of pure ocean should be valuable. For instance, Southern Ocean fluxes within the measurement fetch of the Cape Grim observatory are 0.0024 atoms cm-2s-1. Based on the 10/90 percentile range of 222Rn concentrations in minimally perturbed oceanic air masses, and assuming a constant mixing height, the range of oceanic 222Rn fluxes for this region could be as large as 0.0014-0.0035 atoms cm-2s-1 (Zahorowski et al., 2004). These new estimates are less than those commonly
7 assumed. In addition, it may be possible to use models of gaseous exchange at the ocean’s surface, such as Wanninkhof (1992) and Donelan et al. (2002), with data on 226Ra in surface ocean water (e.g., Peng et al., 1979) and predictions of surface wind and sea surface temperature from GCMs to predict temperature and spatial variation of radon flux from the oceans on a global scale.
Quality control in any new measurement programs should be given careful attention. Too much data in the historical literature lacks quality control information and careful documentation of measurement conditions. For this reason, much of these data are not useful for generating global 222Rn flux maps and may have to be redone. For example, although the accumulator technique is a time honoured method for measuring 222Rn flux, it is only in recent years that the importance of minimizing back diffusion, boundary leaks, and insuring full mixing of air within the accumulator has become evident. New measurements should take into consideration the latest information on these potential source of errors. If new maps, or datasets, are generated for 222Rn flux, careful consideration should be given to validation and error analysis.
Organizations such as WMO/GAW, WCRP, and IAEA should facilitate execution of the above recommended approaches by several steps. First of all, they should point out to their members the importance of better knowledge of 222Rn flux from the Earth’s surface and encourage their members to support activities of the type suggested. In addition, the IAEA might take the lead in coordinating quality control programs that relate to new measurement programs with 222Rn flux and surface soil 226Ra (or related variables). WMO might consider the support for the selected nations, particularly countries for which 222Rn flux related data are presently unavailable (such as in Africa and South America), for study of 226Ra and 222Rn flux in those nations.
4.1.4 Additional Recommendations
(see the Workshop Recommendations in this report)
4.1.5 References
Conen, F., 2003. Variation of 222Rn Flux and Its Implication for Tracer Studies, [this workshop publication]. Donelan, M. A., W. M. Drennan, E. S. Saltzman, and R. Wanninkhof, 2002. Gas Transfer at Water Surfaces, American Geophysical Union, Washington, DC. Graustein, W. C., and K.K. Turekian, 1990. 222Rn Fluxes from Soils to the Atmosphere Measured by 210Pb- 226Ra Disequilibrium in Soils, Geophys. Res. Lett., 17, 841-844. Jennings, S. G., P. Ciais, S. Biraud, and M. Ramonet, 2003. Irish Greenhouse Gas Emissions, Final Report, Environmental Protection Agency, Johnstown Castle, Ireland. Peng, T. –H., W. S. Broecker, G. G. Mathieu, and Y. –Hi Li, 1979. Radon Evasion Rates in the Atlantic and Pacific Oceans as Determined During the Geosecs Program, J. Geophys. Res., 84, 2471-2486. Schery, S. D., and M.A. Wasiolek, 1998. Modelling 222Rn Flux from the Earth’s Surface, in 222Rn and Thoron in the Human Environment, editors Katase, A., and Shimo, M., World Scientific, pages 207-217; 222Rn flux density datasets available at http://www.nmt.edu/~schery/mapdata.html. Schery, S. D., 2003. Progress on Global 222Rn Flux Maps and Recommendations for Future Research [this workshop Publication].
Smethie, W. M., T. Takahashi, D. W. Chipman, and J. R. Ledwell, 1985. Gas Exchange and CO2 Flux in the 222 Tropical Atlantic Ocean Determined from Rn and pCO2 Measurements, J. Geophys. Res., 90, 7005- 7022. Wanninkhof, R., 1992. Relationship Between Wind Speed and Gas Exchange Over the Ocean, J. Geophys. Res., 97, 7373 – 7382. Wilkening, M. H., and W. E. Clements, 1975. Radon 222 from the Ocean Surface, J. Geophys. Res., 80, 3828 – 3830. Zahorowski, W., S. Chambers, and A. Henderson-Sellers, 2004. A new method for the estimation of regional oceanic radon-222 fluxes. Geophysical Research Letters, (submitted).
8 ANNEX
4.1.6 Focus Questions - Source Processes and Source Algorithms
A. What are the Processes and Major Parameters Determining 222Rn Emanation and Exhalation Rate from Soil?
For most situations relevant to global mapping of 222Rn flux the primary controlling factors are:
a. 222 Rn production (226Ra content); b. Emanation rate (fraction of generated 222Rn that escapes to pore space); c. Transport by diffusion; d. Depth of soil to bedrock or water table IF soil thickness less than average distance of diffusion (diffusion length for 222Rn).
In addition, there are important indirect factors causing variation in 222Rn flux: These indirect factors act through affecting one or more primary factors listed above. Examples are:
e. Soil moisture and precipitation; f. Soil temperature; g. Soil physical properties such as porosity and grain size.
There are a number of other factors, mostly indirect, that may affect flux; but on a relative basis are usually less important. Examples are wind; atmospheric pressure change, freezing, snow cover, and vegetation (roots).
Comment: Of all these factors, only a and g are constant in time at a given location. Both b and c are sensitive to water content of pores.
B. Can Comprehensive Global Climate Models (GCMs) Be of Use in Improving Predictions of 222Rn Flux?
Predictions of variables such as soil temperature, soil moisture, surface wind, and surface pressure are potentially of value for predicting 222Rn flux: A prediction of depth to water table on a global scale would be very helpful. However, given the level of sophistication of 222Rn flux models, historical averages and archived values for quantities such as these may be a sufficient alternative at present.
C. Do We Need More Source Process Studies and Systematic Flux Measurements?
Yes! For example (see section 4.1.5, Jennings, 2003).
a. A realistic approach is to make a small number of flux measurements, carefully timed and placed. They could greatly improve calibration of 222Rn flux models. For example, winter and summer transects that go from Norway to Egypt might be very valuable. Or similar transects running from Southern Mexico to Alaska since 226Ra data already exist for both transects. In case people chose to do other transects, they should favour regions where surface 226Ra has already been mapped. b. Test sites to study 222Rn flux processes and compare instruments and techniques are needed. c. Need to specify uncertainties on the flux prediction derived from the flux models. d. Need for a better evaluation of flux from the ocean (both measuring fluxes and recommendation for further modelling studies)
9 D. What is the Best Methodology to Create a Global Map of 222Rn Exhalation Rate?
a. Quick and cheap options: Evaluate the proposed approaches of Schery and Conen (using SW1998 maps and Conen's 2003 prescription, see section 4.1.5) and merge these approaches. b. Intermediate speed and cost option: Improve SW1998 maps with new calibration data for flux and new data for surface soil 226Ra. (Given the central role of 226Ra in controlling 222Rn flux from soil, all methods of mapping it should be explored. The use of surrogate data should be investigated. Information on such subjects as surface gamma radiation, uranium surveys, soil classification, surface geology, and stream sediments should be considered). c. Most expensive and slowest option: (but possibly best if cost is not a factor): Try to map the Earth's surface directly with several flux measurements per one degree by one degree grid at least summer and winter seasons.
Priority should be on b (a and c are obvious ones to do).
E. How Can WMO/GAW, WCRP, and IAEA Help?
• Encourage measurements for 226Ra and 222Rn flux as indicated above. • IAEA establish and organize quality control programs for such measurements. • WMO provide funding for such measurements for selected countries. • Possibility to fund a doctoral thesis? (1st year: calibrate and refine measurement equipment then measure transects, 2nd year: construct model predicting flux, 2nd-3rd year: apply these fluxes to a global transport model).
10 4.2 Global Radionuclide Measurements
Contributors: Len Barrie, Ales Fajgelj, Dominique Filipi, Casper Labuschagne, Jussi Paatero, Zbigniew Radecki, Colin Sanderson, Thomas Steinkopf, Wlodek Zahorowski and Yasuhito Igarashi
4.2.1 Introduction
Routine measurements of naturally occurring 222Rn, 210Pb, 7Be and 14CO are ongoing and are key variables to be measured in a global monitoring network for atmospheric composition in support of climate change research and policy setting. The Group first considered the current state of monitoring of the first three variables by addressing the following questions:
i. What measurement techniques are currently used and recommended for routine atmospheric 222Rn and 222Rn progeny observations at GAW baseline air monitoring stations?
ii. What instruments are available, or instrument development needed, for use in systematic aircraft measurements of vertical profiles of 222Rn and its daughters?
iii. How can 222Rn, 210Pb and 7Be measurements (in the atmosphere, in soil pore air, as well as flux measurements) be calibrated?
iv. Is there a need for instrument inter-comparison studies on a campaign or routine basis?
v. Is there a need for a central archive for routinely measured 222Rn, 210Pb and 7Be?
vi. Are there any new types of naturally occurring radionuclide measurements techniques that should be developed and implemented that would benefit the development and validation of climate and atmospheric chemical transport models?
vii. Independently, it also considered a strategy for 14CO observations.
4.2.2 222Rn Global Monitoring
Currently under the Global Atmosphere Watch programme of WMO involving member country and contributing partner efforts, routine observations are being made at regional representative locations as shown in Figure 1. There are approximately 21 stations. Additional routine observations are made elsewhere in the world but generally not associated with other atmospheric composition measurements.
4.2.3 222Rn Measurements at Ground Stations
222Rn concentration in air is measured using either two-filter or one-filter instruments. These involve counting of 222Rn progeny using either alpha or beta particle detectors.
At present, the two-filter method [Thomas and LeClare, 1970] is the best direct technique for low level measurements of 222Rn in air. The one-filter method, still widely used at the GAW stations (Table 1), relies on measurement of 222Rn progeny concentration in the sample air, and the corresponding 222Rn concentration is calculated upon assumptions regarding equilibrium, or establishing the degree of disequilibrium, of the progeny with respect to the ambient 222Rn [Larson, 1973; Lambert et al., 1970].
The current 222Rn instruments operated in the GAW network are shown in Table 1.
11
Figure 1: Routine observations of 222Rn, at GAW Global, Regional and Contributing Stations as of 2003
12 Table 1: Description of 222Rn instruments at GAW stations ( see Figure 1).
Stations Instrument Averaging Lower Limit of Reference Type/Group Time Detection /Response (mBq/m3)* Time (min) Neumayer, Alert, 222Rn progeny, One 60/90 20 Schmidt et al., 1996 NyAlesund, filter, α count, Schauinsland Heidelberg Amsterdam Is., 222Rn progeny, One 120/120 10 Polian et al., 1986 Mace Head, Puy de filter, α count, Dome, Mt. Cimone CNRS/LSCE, France Cape Point, South 222Rn 60/45 20 Whittlestone and Africa Zahorowski, 1998 SA Weather Service Cape Grim, Mauna 222Rn 60/45 10 (CG) , 20 Whittlestone and Loa, Mt. Waliguan, Two filter, α count, (MLO and Mt Zahorowski, 1998 Sado I, Gosan, ANSTO, Australia Waliguan) Hong Kong Matorva, 222Rn progeny, 60/90 100 Paatero et al., 1994 Pallas, One filter, β count Sodankyla FMI, Finland Pallas 222Rn 60/60 50 Hutter et al.,1995 Two filter, α count, FMI, Finland Hohenpeissenberg, 222Rn progeny, One 60/90 500 Tracerlab, Aachener Str. Zugspitze filter, α count, 1354, 50859 Köln, DWD, Germany Germany DWD internal reports Jungfraujoch 222Rn progeny, One 60/60 50 Gäggeler et al., 1995; filter, α count, Lugauer et al., 2000 PSI, Switzerland
* in the case of one-filter instruments the measurement is 222Rn equivalents.
4.2.3.1 222Rn measurements techniques
Two-Filter
The principle of the two-filter detector is as follows: sample air is conditioned as it is drawn into the detector through the first filter by removing aerosols as well as ambient Rn222and Rn220 progeny. Once inside the detector delay chamber, 222Rn is delayed for sufficient time to allow a number of new progeny to be produced. The new progeny are collected on the second filter. Since they have been produced in controlled conditions, their number is proportional to the 222Rn concentration (and 220Rn, if present in the delay chamber). The collected progeny are counted using an alpha particle detector. The second filter can be implemented as a filter tape [Hutter et al., 1995] or a wire mesh [Whittlestone and Zahorowski, 1998]. Usually a zinc sulphide scintillator and a photo multiplier tube serve as the alpha particle detector. Electrostatic collection has also been applied, with the collecting surface being either a scintillator or a solid state detector (Iida et al., 1996). In the latter case, a multichannel analyser is required for signal processing. Each of these systems and solutions has its own advantages and disadvantages. At the moment, all four two- filter 222Rn detectors deployed at the WMO/GAW stations are based on counting of two short lived 222Rn alpha emitting progeny (218Po and 214Po, Figure 2) collected on a second filter, with a scintillator- photo multiplier tube assembly as the alpha detector. These instruments are of two types: one flow loop or dual flow loop and are described in more detail below.
13 222Rn
3.82 d
α GAS
PARTICLE
Po-210 Po-214 Po-218 -4 138 d 1.6 x 10 s 3.05 min
β¯ β¯ α Bi-210 α Bi-214 α 5.01 d 19.9 min
β¯ β¯ Pb-206 Pb-210 Pb-214 STABLE 22.3 y 26.8 min
Figure 2: A section of the 238U decay series showing 222Rn and its progeny.
One flow loop, two-filter detector. The instrument [Hutter et al., 1995; Guggenheim and Negro, 1990] can be configured with a 500 or 1,000 litre delay chamber and set up to 60-min or 30-min sampling and counting. Sample air is pumped through a decay chamber at flow rates ranging from 350 to 400 litre min-1. For a 60 minute sample collection followed by a 60 minute alpha count, the lower limit of detection is equal to about 55 mBqm-3. The response time of the detector is about 60 minutes. A 500 litre instrument is deployed at the Pallas station in Finland (Table 1). A 1,000 litre instrument was operational at the Mauna Loa Observatory (MLO) until 1996.
Dual flow loop, two-filter detector. The detector [Whittlestone and Zahorowski, 1998] is a major redesign of an earlier instrument [Schery et al.,1980]. It aims at measurement of very low levels of 222Rn and low power consumption which might be an essential requirement at remote locations. Two air flow paths are used to separate the high flow rate required in the original two-filter design to prevent loss of 222Rn progeny to the walls of the detector, and the low flow rate needed to change the air sample in the instrument. The high flow rate path is achieved by using a second blower inside the chamber and results in the progeny being transported through the second filter within about a minute of their production. The change of the air inside the detector is set to be completed on a timescale of about half an hour to ensure that the overall time resolution of the instrument is less than 45 min. There are three detectors of this type deployed at the GAW stations (Cape Grim, Cape Point, and MLO). The lower limit of detection for a 60 min count depends on the volume of the main detector delay chamber, and is about 20 and 10 mBq m-3 for MLO and Cape Point, and Cape Grim, respectively.
One-Filter
222Rn progeny concentrations in air are often approximated by measurements of atmospheric aerosol specific radioactivity. This is usually done using the one-filter method. There are site- and experiment-specific assumptions regarding equilibrium or the degree of disequilibrium which need to be made and justified to derive 222Rn concentration from aerosol specific radioactivity [e.g. Biraud et al., 2000; Schmidt et al., 1996; Paatero et al.,1994]. If at a specific site,
14 the validity of the equilibrium assumption can be demonstrated, and a measure of accuracy is achieved through comparison with other techniques, then use of the one-filter method is justified.
Implementation of the one-filter method is based on either alpha or beta counting [Larson, 1973; Lambert et al., 1970]. Typically, air is pumped continuously through a filter and the alpha particles resulting from the decay of 214Po and 218Po are collected on the filter and counted [e.g. Schmidt et al., 1996]. Systems based on beta counting do not differ greatly from those based on alpha counting, the difference being in the detection unit. For instance, a system deployed at Matorva, Pallas and Sodankyla in Finland has a dual filter arrangement in which air is pumped alternatively through one of the two cylindrical filters with a G-M counter located co-axially inside. The counted beta particles come from the short-lived beta emitters of 222Rn progeny, 214Pb and 214Bi (Figure 2). The integration time of one-filter systems depends on the targeted lower limit of detection and is usually set at 60 min (Table 1). The best time resolution of the one-filter method is defined by a time lag between 222Rn progeny activity on the filter and 222Rn changes in sampled air and is equal to about 30 min. In practice, however, the time resolution is usually more than 1 hour (Table 1). If an experiment requires a better time resolution, this can be achieved by counting alpha particles resulting from the decay of 218Po, which has a half-life of 3.05 min (Figure 2). This has been implemented in both one- and two- filter instruments [e.g. Negro et al., 1996; Iida et al., 1996].
4.2.4 Aircraft-Based Measurements Of 222Rn and 222Rn Progeny Profiles
Aircraft measurements have been used to determine vertical profiles of 222Rn and other radionuclides from several hundred meters to 10,000 meters above ground level. As for ground measurements, the currently used techniques rely on 222Rn or 222Rn progeny measurements. However, all onboard systems are to comply with safety requirements.
222Rn can be sampled and analysed during flights using in-situ analysers. An in-situ analyser developed by Negro et al. (1996) uses advanced electrostatic collection techniques to measure in real-time 222Rn concentration from the 218Po decay. Installed on a research aircraft with the mass flow controlled at 1.13 cubic metres/minute, 1cpm of 218Po is equivalent to a 222Rn concentration of 0.001 pCi/l. The background is negligible, as the instrument uses alpha spectroscopy for the determination of 218Po. Such instrument designed for aircraft measurements was used in the field study for determining vertical profiles of 222Rn concentrations (Lee and Larsen, 1997).
Other methods separate sampling from analysis, with the latter taking place after completion of the flight. One method [Kritz et al., 1990; Kritz and Rosner, 1998] relies on compressing sampled air in high-pressure tanks. A sampling unit consists of an inlet, a high- pressure compressor, and a set of high-pressure tanks. During a flight, the tanks are flushed and then filled with ambient air. In the laboratory, 222 Rn is transferred from the high-pressure tanks and counted in a Lucas cell and a photo multiplier assembly. Approximately 8 hours are required to process one sample. At a 222Rn concentration of 60 mBq m-3, the uncertainty is about ± 8%. Another sampling method relies on collecting 222Rn on activated charcoal traps [Zauker et al., 1996]. In this case, the sampler consists of membrane pumps and stainless steel sampling tubes filled with activated charcoal. The trapped 222Rn is extracted into a scintillation cell using helium as the carrier gas. For low ambient 222Rn activity, the overall uncertainty is about ± 15 %.
A one-filter instrument developed by Filippi and Le Roulley consists of an aerosol sampler and an alpha particle detector [Filipi, 2000]. The aerosols are collected for 15 min using an isokinetic probe on a cellulose filter tape. The flow rate depends on the speed of the aircraft and the altitude, and is typically around 35 STP m3 min-1. The alpha particle detector consists of four alpha particle solid state detectors to achieve a total counting time equal to four times the pumping time. The lower limit of detection is 10 mBq m-3 222Rn equivalent.
15 4.2.5 Calibration of 222Rn Instruments
4.2.5.1 Calibration of two-filter instruments
The Group agreed that the calibration procedure for the two-filter method should be routinely performed using a 222Rn calibration source traceable to a primary source one of which is hosted by the GAW World Calibration Centre at EML. Also, sensitivity, accuracy, and instrumental background of two-filter instruments should be evaluated on a regular basis [e.g. Brunke et al., 2002].
4.2.5.2 Calibration of one-filter instruments
The Group concluded that monitoring the counting efficiency of one-filter instruments in field conditions can be easily implemented. However, calibration of such instruments can only be accomplished in a certified 222Rn chamber where a range of 222Rn and 222Rn progeny concentrations as well as other factors including ambient humidity and temperature can be established and maintained.
Taking the above into account, the Group recommended that a calibration procedure for the one-filter instrument be adopted. The procedure includes the following steps:
• Calibration of a small one-filter detector in a 222Rn chamber using a range of 222Rn and 222Rn progeny concentrations; • Certification of the calibrated detector for intercomparison purposes for a set period (at least two years); • Transport of the certified system to a site equipped with a field detector to be tested; • Running of the certified detector side by side with the tested detector for a period of at least several days; • Establishment/adjustment of the calculation factors for the tested detector based on the comparison with the certified detector; • Certification of the tested detector.
The Group discussed the relative merits of organising a new field intercomparison of current instrumentation, similar to those done previously [Cole et al, 1995; Whitttlestone, 1989]
4.2.6 Measurement of 210Pb and 7Be
Currently, 210Pb and 7Be are measured routinely at the GAW stations by filtration and subsequent γ counting. These are summarized in Table 2. Many GAW stations are operated by EML laboratory. The laboratory also conducts routine measurements at 20 other sites around the world. Several independent measurements are made at GAW sites and are also listed in Table 2.
Table 2: Measurements of 7Be and 210 Pb at GAW stations (see Figure 1).
Station Group Averaging Time Reference Cape Point, South EML, USA 4 weeks except Larsen et al., 1995 Africa Waliguan and Ryori (1 Mt. Waliquan, China, week) Ryori, Japan; Barrow USA; South Pole, Cape Grim, Australia Sodankyla FMI, Finland 24h Paatero and Hattaka, 2000 Zugspitze DWD, Germany 12h and weekly Internal DWD reports Jungfraujoch PSI, Switzerland 48h STACCATO, 2002 Amsterdam Island CNRS/LSCE, France (Pb210 only)
16 The Group discussed the potential for 7Be and 210Pb measurements made by the CTBT network of about 80 stations worldwide. This network is designed to detect the release to the atmosphere of artificial radionuclides. However, samples collected routinely and measured by gamma counting could yield 7Be and 210Pb. Such data would be very useful for atmospheric studies.
4.2.7 Need For Central Archiving of Global Long Term 222Rn, 7Be and 210Pb Data
GAW World Data Centres [see Barrie and Sommeria, these proceedings] collect all available observations globally and make them available free of charge to researchers. They contain as comprehensive a set of global long term measurements as possible. They focus on a selected set of variables recommended by scientific advisory groups. As recommended in this report, the central archive of long-term measurements of 222Rn, 7Be and 210Pb made at GAW stations should be established. Currently, the GAW World Data Centre for Greenhouse Gases in Japan has agreed to archive 222Rn data.
4.2.8 Ongoing Activities in 14CO Research
• The US National Science Foundation is supporting 14CO measurements at two tropical sites (John E. Mak, Marine Sciences Research Centre State University of New York, Stony Brook). • The National Institute of Water and Atmospheric Research, Wellington, New Zealand (Dave Lowe) is measuring 14CO at Baring Head and on ship cruises. • The Max Planck Institute for Chemistry in Mainz, Germany (in cooperation with Lufthansa, the Oxford Radiocarbon Accelerator Unit (funded by the Natural Environment Research Council), and the Department of Nuclear Physics at the Komensky University, Bratislava, Slovakia) is measuring the cosmogenic production rate of atmospheric 14C (Project CORAXX - COsmic Radiation Aircraft eXposure eXperiment). One aspect of this project is to evaluate calculations of cosmogenic nuclide production rates (e.g. 14C, 7Be, 10Be) in the atmosphere (see contribution of J. Mazarik).
4.2.9 Recommendations for 14CO
As shown in various studies (for references see ”14CO and its Application in Studies of Atmospheric Chemistry and Transport” on page 81 in this report), 14CO can be regarded as an atmospheric tracer separate from CO. Atmospheric 14CO is virtually uninfluenced by human activities; it is a natural tracer. Its abundance is controlled by mainly three processes:
• the source strength and its modulation with solar activity; • the tropospheric OH abundance and its seasonal cycle; • the transport from the stratosphere into the troposphere.
Its atmospheric lifetime of about two to three months makes 14CO a very promising candidate for monitoring the changing state of the Earth's atmosphere and its inter-annual variability, with focus on the three controlling processes which are all essential for the understanding of climate change.
Within the framework of IGAC activities, it is well acknowledged that improved assessments of global tropospheric OH, its distribution, its changes and its trend are needed. OH, which is the main component of the troposphere’s self-cleansing capacity may be changing, but trends, and inter-annual variations are difficult to gauge. The main reason for this is that OH measurements are extremely difficult, and that OH is highly variable. Consequently, most of what is known about the OH distribution throughout the atmosphere is reconstructed from model calculations. For verification of these model results, few tracers are available. The International Global Atmospheric Chemistry (IGAC) project is proposing to tackle the problem of better quantifying OH and its changes. 14CO may well offer the best possible way to do this.
17 14CO is very well suited for long-term monitoring. The advantages of 14CO are:
• the measurement technique is well established; • at a monitoring station no complicated equipment is needed (only air sampling); air samples are shipped to a 14CO / AMS-laboratory; • the measurement is an absolute measurement; • since 14CO is a natural tracer, it can also be observed in polluted areas (e.g., urban areas); • 14CO at the surface level shows a distinct (OH driven) seasonal cycle; • because of the lifetime, tropospheric vertical gradients and meridional gradients of 14CO are small.
In summary, long-term observations of 14CO could provide valuable information about the variability of important aspects of the atmosphere. At least six 14CO monitoring stations of GAW (one in each 30o latitude band) should be considered to measure the atmospheric 14CO bi-weekly or weekly.
4.2.10 References Brunke, E-G., C. Labuschagne, B. Parker, D. Van der Spuy, S. Whittlestone, Cape Point GAW Station 222Rn detector: factors affecting sensitivity and accuracy. Atmospheric Environment, 36, 2257 – 2262, 2002.
Collé, R., M.P. Unterweger, P.A. Hodge, J.M.R. Hutchinson, S. Whittlestone, G. Polian, B. Ardouin, J.G. Kay, J.P. Friend, B.W. Blomquist, W. Nadler, T.T. Dang, R.J. Larsen and A.R. Hutter. An international intercomparison of marine atmospheric 222Rn in Bermuda. J. Geophys. Res.,, 100, No. D8, 16617- 16638, 1995.
Filippi, D., 2000. « Etude et développement d’un instrument aéroporté destiné à la collecte des aérosols et à la mesure du 222Rn par son dépôt actif », Phd thesis, Université Paris 6 Pierre et Marie Curie, July 2000.
GAW-109, 1995. Report of an Expert Consultation on Kr85 and Rn222: Measurements, Effects and Applications, WMO/GAW Report 109, WMO, AREP/ENV, 7 bis, avenue de la Paix, BP 2300, CH- 1211 Geneva, Switzerland.
Gäggeler H.W., U. Baltensperger, M. Emmenegger, D.T. Jost., A. Schmidt-Ott, P. Haller and M. Hofmann. The epiphaniometer, a new device for continuous aerosol monitoring. J.Aerosol Sci., 20, 557-564, 1989.
Guggenheim S.F. and V. C. Negro. Automatic Filter Changer for Environmental 222Rn Measurements. Winter Annual Meeting of The American Society of Mechanical Engineers, 90-WA/DE-2, Dallas, Texas, November 25-30, 1990.
Hutter, A.R., R.J. Larsen, H. Maring, J.T. Merrill. 222Rn at Bermuda and Mauna Loa : Local and Distant Sources. J. Radioanal. And Nuclear Chem., 193, 309-318, 1995.
Iida,T., Ikebe,Y., K. Suzuki, K. Ueno, Z. Wang, and Y. Jin. Continuous measurements of outdoor 222Rn concentrations in various locations in east Asia. Environment International 22(suppl.), 139-147,1996.
Kritz M.A. and S. W. Rosner. Validation of an off-line three-dimensional chemical transport model using observed 222Rn profiles. J. Geophys. Res., Vol.103, No. D7, 8425-8432, 1998.
Kritz, M. A., J.C. Le Roulley and E.F. Danielsen. The China Clipper - fast advective transport of 222Rn rich air from the Asian boundary layer to the upper troposphere near California. Tellus, 42B, 46-61,1990.
Kritz, M. and S.W. Rosner. Validation of an off-line three-dimensional chemical transport model using observed 222Rn profiles. 1 Observations. J. Geophys. Res., 103(D7), 8425-8432, 1998.
18 Lambert, G., G. Polian, and D. Taupin. Existence of periodicity in 222Rn concentrations and in the large scale distribution at lower altitudes between 40o and 70oS. J. Geophys. Res., 75, 2341-2345, 1970.
Larsen, R.J., C.G. Sanderson, and J. Kada. EML Surface Air Sampling Programme, U.S. Department of Energy Report EML-572, National Technical Information Service, Springfield, Va, 142, 1995.
Larson, R.E., and W.A. Hoppel, 222Rn measurements below 4 km as related to atmospheric convection. Pure Appl. Geophys., 105, 900, 1973.
Lee, H. N., and R. J. Larsen, Vertical diffusion in the lower atmosphere using aircraft measurements of 222Rn. J. Applied Meteorology, 36, 1262-1270, 1977.
Lugauer, M., U. Baltensberger, M. Furger, H.W. Gäggeler, D.T. Jost, S. Nyeki, and M. Schwikowski,.Influences of vertical transport and scavenging on aerosol particle surface area and 222Rn decay product concentrations at the Jungfraujoch (3454 m above sea level). J. Geophys. Res., 105, 19869-19879, 2000.
Negro, V. C., N. Y. Chiu, R. J. Larsen, S. B. Wurms and C. Breheny. Continued testing and evaluation of the Radgrabber. USDOE Rep. EML-580, 153 pp, 1996.
Paatero, J., J. Hatakka, R. Mattsson and I. Lehtinen. A Comprehensive Station for Monitoring Atmospheric Radioactivity. Radiation Protection Dosimetry, 54(1), 33-39,1994.
Paatero, J. and J. Hatakka. Source Areas of Airborne 7Be and 210Pb Measured in Northern Finland. Health Physics, 79(6), 691-696, 2000.
Polian, G., G. Lambert, B. Ardouin, and A. Hegou. Long-range transport of continental 222Rn in subantarctic and antarctic area. Tellus, Ser.B, 38, 178-189, 1986.
Ramonet M., J.C. Le Roulley, P. Bousquet, et P. Monfray. 222Rn measurements during the TROPOZ II mission, and comparison with a global atmospheric transport model. Journal of Atmos. Chem., 23, 107-136, 1996.
Schery, S.D., D.H. Gaeddert, and M.H. Wilkening. Two-filter monitor for atmospheric 222Rn. Rev. Sci. Instrum., 51(3), 338-343, 1980.
Schmidt, M., .R. Graul, H. Sartourius, and I. Levin. Carbon dioxide and methane in continental Europe : A climatology, and 222Rn -based emission estimates. Tellus, Ser.B 48(4), 457-473, 1996.
STACCATO. An EU project (Contract No.: EVK2-CT-1999-00050) report on Influence of Stratospheric- Tropospheric Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity. A summary is available on the web: http://www.forst.tu-muenchen.de/EXT/LST/METEO/staccato/, 2002.
Whittlestone, S. Australian-French 222Rn detector intercomparison, in Baseline Atmospheric Programme (Australia), CSIRO Atmos. Res., 47-49, Melbourne, 1989.
Whittlestone S. and W. Zahorowski. Baseline 222Rn detectors for shipboard use: Development and deployment in the First Aerosol Characterisation experiment (ACE 1). J. Geophys. Res., 103, 16,743- 16,751, 1998.
Zaucker, F., P. Daum, U. Wetterauer, C. M. Berkowitz, B. Kromer, and W. Broecker. Atmospheric 222Rn Measurements During the 1993 NARE Intensive. J. Geophys. Res., 101(D22), 29,149-29,164, 1996.
19 4.3 Modelling Radionuclides
Contributors: Y. Balkanski, J. Feichter, P. Jöckel and J. Masarik With participation of B. Josse, S. Taguchi and M. A. Mélières
4.3.1 Use Of Radionuclides To Test Atmospheric Transport
Comprehensive evaluation of thousands of man-made chemicals is a challenging task, which has to comprise transport in and cycling between the atmosphere, the soil, the vegetation and the ocean. Cosmogenic and terrigenic natural radiotracers and radionuclides from nuclear bomb tests have been widely used to test a large variety of relevant processes. Species used as test tracers should ideally be chemically inert, have well known sources and sinks and have sufficient observations for use in model evaluations. They are summarized in Table 1 (Annex 1) of Chapter 4.3.
222Rn measurements at surface sites, from ships or aircraft have been used to test modelled boundary layer transport as well as modelled exchange between the boundary layer and the free troposphere. The long-range transport of 222Rn from the African continent to subantarctic islands several thousand kilometres downwind from South Africa (radonic storms) provides a test for the treatment of advection and diffusion in global models.
Krypton-85 has been used to evaluate the inter- and intra-hemispheric transport times. This long-lived radionuclide (e-folding time of 15.51 years) is produced by the reprocessing in nuclear power plant. Sources are mostly located at Northern Hemisphere mid-latitudes which makes it a good proxy for inter-hemispheric transport of pollutants. The very pronounced latitudinal profiles that have been measured for 85Kr yield an interhemispheric exchange time of approximately 1.1 years.
One challenge in global 3 dimensional atmospheric models is to simulate accurately the stratosphere-to-troposphere exchange, an issue which might partly be resolved by higher vertical model resolutions in the tropopause region.
The upward transport from the troposphere to the stratosphere occurs in great part in the tropical regions where convective systems inject lower tropospheric air into the upper troposphere/lower stratosphere region. The importance of these events requires observation of vertical profiles of these compounds in the altitude range 10 to 22 km. No such profiles have been acquired recently and measurements of one radionuclide 222Rn or a suite of them including 222Rn/210Pb would greatly enhance the observational basis to understand these phenomena.
14CO is a very good tracer of stratosphere-to-troposphere exchange, and can also be used to assess the tropospheric OH abundance (see contribution of P. Jöckel and Carl A.M. Brenninkmeijer in this report). The main source for 14CO is production within the atmosphere by cosmic particle radiation, and the only sink is oxidation by OH.
Radionuclides which condense on particle surfaces provide tests of aerosol physics including wet and dry deposition. Radionuclide tracers like 210Pb, 7Be, 10Be and 90Sr have been used for this purpose.
4.3.2 Observational Data
Long time-series of 222Rn measurements at the surface were reported by EML whereby most of the sites are located in the US and South America. French groups report 222Rn observations in the Indian Ocean and German groups measured in Germany, in Canada (Alert) and at Antarctica. At present very few measurements exist to assess the rapid trans-continental transport either in the Northern or in the Southern Hemisphere. Noticeable exceptions are the measurements made by Kritz et al. (1986) and 222Rn vertical profiles acquired during the Pacific
20 14 Exploratory Missions (PEMs). CO2: Radiocarbon surface data has been monitored from 1968 to the 80s at about 10 sites over Europe. EML operates a global network measuring surface concentrations of natural and bomb test tracers in filter samples beginning in the early 1950’s. EML performed measurement flights taking filter samples within the High Altitude Sampling Program (HASP) (Leifer and Russell, 1986). They report radionuclide concentrations of nuclear fission products of bomb tests in the stratosphere. EML operated also a worldwide net reporting surface concentration measurements of natural and artificial radiotracers. The data set listed in Table 2 (Annex 2) is available for model testing.
4.3.3 Availability Of Cosmogenic Nuclide Production Inventories
In the last decade, substantial progress was made in the field of numerical simulation of cosmogenic nuclide production rates. New powerful nuclear physics codes like GEANT, LCS, FLUKA were extended and tailored for cosmic ray applications. As result of this effort, the fluxes of neutrons and protons in the Earth’s atmosphere were calculated. In order to study the spatial variations of particle fluxes, the whole atmosphere was divided into cubic cells with depth of 30 g/cm2 and horizontal dimension of 10 deg. Temporal variations in the particle fluxes were also examined through the variation of solar modulation parameter and also the geomagnetic field intensity, covering whole range of values observed for this parameters in the past. Calculated particle fluxes are available on internet together with the software necessary for production rate calculations. The production rates for 3H, 7Be, 10Be, 14C, and 36Cl as functions of altitude, latitude, solar and geomagnetic field intensity are available. At present, with the advent of new particle fluxes measurements (Paul Goldhagen in this report), numerical models can be tested. This is of primary importance, as this can reduce one of the two main sources of uncertainties in numerical models – systematic uncertainty of particle fluxes.
4.3.4 Needs For Tracer Transport Modellers
A series of intercomparisons of global atmospheric transport models has shown that the usefulness of vertical profiles of 222Rn in constraining the vertical mixing in the troposphere (Jacob et al., 1997, Rasch et al. 2000 and Barrie et al. 2001). However, uncertainties in 222Rn flux densities and in observations leave considerable room for improvement.
4.3.5 Recommendations
(See the Workshop Recommendations in Section 2 of this report).
4.3.6 References
Anderson, R., R. Larson. Atmospheric electric and 222Rn profiles over a closed basin and the open Ocean, J. of Geophys. Res., Vol. 79, No. 24, 3432-3435, 1974.
Barrie, L.A., et al. A comparison of large-scale atmospheric sulphate aerosol models (COSAM): overview and highlights, Tellus, 53B, 615-645, 2001.
Beck, H. L., 222Rn measurements at Chester, NJ, 1987-1990, In: USDOE Rep. EML-538, Environmental Measurements Laboratory, U.S. Dept. of Energy, New York, 1991.
Dibb, J., The accumulation of Pb-210 at Summit, Greenland since 1855, Tellus, Vol. 44B, 72-79, 1992.
Fisenne, I. M., 222Rn measurements at Chester, NJ through July 1986, In: USDOE Rep. EML-504, Environmental Measurements Laboratory, U.S. Dept. of Energy, New York, 1988.
Fukuda, K., S. Tsunigai, Pb-210 in precipitation in Japan and its implication for the transport of continental aerosols across the ocean, Tellus Vol 18, 514-521, 1975.
Gesell, T., Background atmospheric 222Rn concentrations outdoors and indoors: A review, Health Physiks, Vol. 45, No. 2, 289-302, 1983.
21 Gopalakrishnan, S., C. Eapen, C. Rangarajan. Fallout and athmospheric radioactivity measurements in India, HASL-323, 1977.
Graustein, W., K. Turekian. Pb-210 and Cs-137 in air and soils measure the rate and vertical profile of aerosol scavenging, J. of Geophy. Res., Vol. 91, No. D13, 14355-14366, 1986.
Graustein, W., K. Turekian. The effects of forests and topography on the deposition of sub-micrometer aerosols measured by lead-210 and cesium-137 in soils, Agricultural and Forest Met., 47, 199-220, 1989.
Hosler, C., Urban-rural climatology of atmospheric 222Rn concentrations, J. of Geophys. Res., Vol. 73, No. 4, 1155-1166, 1968.
Hosler, C., Vertical diffusivity from 222Rn profiles, J. of Geophy. Res., Vol. 74, No. 28, 1018-7026, 1969.
Jacob, D., M. Prather. 222Rn as a test of convective transport in a general circulation model, Tellus, Vol. 42B, 118-134, 1990.
Lambert, G., G. Polian, J. Sanak, B. Ardouin, A. Buisson, A. Jegou, J. Le Roulley. Cycle du 222Rn et de ses descendants: application a l'etude des echanges troposphere-stratosphere, Ann. de Geophys., Vol. T 38, 496-531, 1982.
Lambert, G., B. Ardouin, J. Sanak. Changes in the atmospheric transport of trace elements toward Antarctica, Tellus, Vol. 42B, 76-82, 1990.
Larsen, R. J., and C. G. Sanderson. EML surface air sampling program, 1989 data, In: USDOE Rep. EML- 541, Environmental Measurements Laboratory, U.S. Dept. of Energy, New York, 1991.
Lockhart, L., Atmospheric radioactivity in South America and Antarctica, J. of Geophys. Res., Vol. 65, 3999- 4005, 1960.
Lockhart, L., Natural radioactive isotopes in the atmosphere at Kodiak and Wales, Alaska, Tellus, Vol. 14, 350-355, 1962.
Lockhart, L., R. Robert, L. Patterson, A. Sanders. Airborne radioactivity in Antarctica, J. of Geophys. Res., Vol. 71, No.8, 1985-1991, 1966.
Mattsson, R., Seasonal variation of short-lived 222Rn progeny, Pb-210 and Po-210, in ground level air in Finland, J. of Geophys. Res., Vol. 75, No. 9, 1741-1744, 1970.
Monhagan, M., S. Krishnaswami, K. Turekian. The global-average production rate of Be-10, Earth a. Planet. Sci. Lett., 76, 279-287, 1985/86.
Monhagan, M., Lead 210 in surface air and soils from California: Implications for the behaviour of trace constituents in the planetary boundary layer, J. of Geophy. Res., Vol. 94, No. D5, 6449-6456, 1989.
Nijampurkar, V., H. Clausen. A century old record of lead-210 fallout on the Greenland ice sheet, Tellus, 42B, 29-38, 1990.
Olsen, C., I. Larsen. Atmospheric depositional characteristics of beryllium-7 and lead-210 along the southeastern Virginia Coast, J. of Geophy. Res., Vol. 94, No. D8, 11106-11116, 1989.
Peierson, D.H., R.S. Cambray, G.S. Spicer. Pb-210 and Po-210 in the atmosphere, Tellus XVIII, 427-433, 1966.
Polian, G., G. Lambert, B. Ardouin. Long-range transport of continental 222Rn in subantarctic and antarctic regions, Tellus, Vol. 38B, 178-189, 1986.
Ramu, M., K. Vohra, Investigations on radioactive equilibrium in the lower atmosphere between 222Rn and its short-lived decay products, Tellus, Vol. 21, 395-403, 1969.
Rangarajan, C., S. Gopalakrishnan, C.D. Eapen. Global variation of lead-210 in surface air and precipitation, HASL – 298.
22 Rasch, P.J, et al. An assessment of scavenging and deposition processes in global models: results from the WCRP Cambridge workshop of 1995, Tellus, 52B, 1025-1056, 2000.
Riley, J., R. Chester. Chemical Oceanography: SEREX: The sea/air exchange program, Academic Press, Vol. 10, ISBN 0-12-588610-1, 1989.
Savoie, Dennis, Rosenstiel School of Marine and Atmospheric Science, University of Miami, (personal communication), please contact Mr. Savoie if the data are used in a publication.
Servant, J., O. Tanaevsky. Mesures de la radioactivite naturelle dans la region Parisienne, Ann. de Geophys., Vol. T 17, 405-409, 1961.
Tsunugai, S., T. Kurata, T. Suzuki, and K. Yokota. Seasonal Variation of Atmospheric 210 Pb and Al in the Western North Pazific Region, J. Atmos. Chem., 7, 389-407, 1988.
Tsunogai, S., T. Shinagawa, T. Kurata. Deposition of anthropogenic sulfate and Pb-210 in the western North Pacific area, Geochem. J., Vol. 19, 77-90, 1985.
Turekian, K., Y. Nozaki, l. Benninger. Geochemistry of atmospheric 222Rn and 222Rn products, Ann. Rev. Earth Planet Sci., 227-255, 1977.
Turekian, K., L. Benninger, E. Dion. Be-7 and pb-210 total deposition fluxes at New Haven, Connecticut and at Bermuda, J. of Geophy. Res., Vol. 88, No. C9, 5411-5415, 1983.
23 ANNEX 1
What radionuclides are useful for chemical transport models?
Species Application Source Ref 222Rn Turbulent transport Soil A Zonal trans-continental transport 210Pb Scavenging Rn-decay B 212Pb Scavenging Rn-decay Vertical transport 14CO Downward transport (STE), Cosmogenic C Tropospheric OH D 14CO2 Carbon cycle Cosmogenic E Vegetation + sea 7Be Scavenging, Cosmogenic F Downward transport (STE) 10Be Scavenging, Cosmogenic G Downward transport (STE) 3H Water vapor transport Cosmogenic 36Cl Paleo-climate, geomagnetic Cosmogenic field 85Kr Trans-continental transport Nucl. processing H Anthropogenic 137Cs Wind erosion, resuspension Bomb-test, accident 90Sr Downward transport Bomb-test
A: Schery, S. D., and M.A. Wasiolek, 1998. Modelling 222Rn Flux from the Earth’s Surface, in 222Rn and Thoron in the Human Environment, editors Katase, A., and Shimo, M., World Scientific, pages 207-217; 222Rn flux density datasets available at http://www.nmt.edu/~schery/mapdata.html. B: Feichter, J., R.A. Brost, M. Heimann, Three-dimensional modelling of the concentration and deposition of 210Pb aerosols, J. Geophys. Res. 96, 22 447-22 469, 1991 C: Patrick Jöِckel, and Carl A.M. Brenninkmeijer, The seasonal cycle of cosmogenic 14CO at surface level: A solar cycle adjusted, zonal-average climatology based on observations, J. Geophys. Res., 107(D22), 4656, doi: 10.1029/2001JD001104, 2002. ,D: Patrick Jöِckel, Carl A. M. Brenninkmeijer, Mark G. Lawrence, Adriaan B. M. Jeuken, and Peter F. J. van Velthoven Evaluation of stratosphere - troposphere exchange and the hydroxyl radical distribution in 3-dimensional global atmospheric models using observations of cosmogenic 14CO, J. Geophys. Res., 107(D20), 4446, doi:10.1029/2001JD001324, 2002. E: Johnston, H., Evaluation of excess carbon 14 and strontium 90 for suitability to test two-dimensional stratospheric models. J. Geophys. Res., 94, 18,845-18493, 1989. F: Brost R.A., J. Feichter, M. Heimann, Three-dimensional modelling of 7Be in a global climate simulation model, J. Geophys. Res., 96, 22 423-22 445, 1991. G: Land C., Feichter J., Stratosphere-troposphere exchange in a changing climate simulated with the general circulation model ECHAM4, J. Geophys. Res. 108, No. D12, Art.-No. 8523, 2003. H: Zimmermann, P.H., J. Feichter, H.K. Rath, P.J. Crutzen, H. Weiss, A global three-dimensional source receptor model investigation using 85Krypton, Atmos. Env., 23, 25-35, 1989.
24
EXPERT PRESENTATIONS
25 Natural Radionuclide Research and Observations in the Global Atmosphere Watch (GAW) and World Climate Research Programmes (WCRP)
Leonard A. Barrie and Gilles Sommeria
1. INTRODUCTION
The Global Atmosphere Watch (GAW) Programme and the World Climate Research Programme (WCRP) located at the World Meteorological Organization headquarters in Geneva support research communities that are investigating global change, developing predictive tools and assessing the current state of knowledge of science. Radionuclides from natural sources in the continental crust or formed cosmogenically in the upper atmosphere play an important role in these studies. In this article, we will briefly describe each programme and highlight how radionuclide measurements and modelling play a role.
2. GAW
The GAW mission is threefold: i. Systematic monitoring of atmospheric chemical composition and related physical parameters on a global to regional scale ii. Analysis and Assessment in support of environmental conventions and future policy development iii. Development of a predictive capability for future atmospheric states
A network of measurement stations for greenhouse gases, ozone, ultraviolet radiation, aerosols, reactive gases and precipitation chemistry form the backbone of GAW monitoring. Global and Regional stations operated by WMO members as well as Contributing stations are involved. Approximately 80 countries host GAW Global and Regional stations through either their National Hydrological and Meteorological Services (NHMSs) or through collaboration with other national scientific organizations. A data base of network station information is maintained in the GAW Station Information System (GAWSIS) (see GAW website: www.wmo.ch/web/arep/gaw/gaw_home.html). It is important to emphasize that, depending on the variable measured, the world network of GAW Global, Regional and Contributing stations has a very different configuration. The task of ensuring that the data sets can be merged falls to GAW and requires substantial international collaboration and resources (e.g. routinely conducted instrument intercomparisons). In Figure 1, the components of the GAW programme are illustrated.
Measurements of Rn222 are made continuously at 20 to 25 locations around the globe (Figure 1 page 11). In addition, they are extremely useful as tracers of the continental influence of air arriving at a station and therefore in understanding simultaneous observations of other atmospheric chemical components. Together with 12 to 24 hour average Pb210 aerosol observations, they can be used to validate models of the global Rn222/Pb210 cycle provided the emissions of Rn222 used by those models are sufficiently accurate. This workshop will address what is known about the accuracy of Rn222 emissions used by models and what is the state of the global long-term Rn222/Pb210 observational network. A second goal is to describe the current situation with regard to source and use of cosmogenically generated Be7 and Be10 observations globally. Finally, the usefulness of cosmogenically generated 14CO is reviewed.
27
Figure 1: The GAW programme coordinates many ground–based global composition monitoring networks through a Working Group of the WMO Commission of Atmospheric Science, its Scientific Advisory Groups, Quality Assurance and Calibration facilities and World Data Centres. It plays a lead role in the development of an Integrated Global Atmospheric Chemistry Observations System (IGACO).
3. WCRP
WCRP, a programme jointly sponsored by WMO, ICSU (the International Council of Scientific Unions) and IOC (the International Oceanography Commission), has two major objectives: i. to assess the nature and predictability of seasonal to interdecadal variations of the climate system at global and regional scales, in order to provide the scientific basis for operational predictions of these variations by climate services. ii. to provide the scientific underpinning for the detection of climate change and attribution of causes, and the projection of the magnitude and rate of human-induced climate change, as needed for input to the IPCC UNFCCC and other Conventions.
It leads four major scientific core projects, each of them with observational and modelling components: CLIVAR dealing with climate variability, the role of ocean circulation and the study of monsoons, GEWEX dealing with the global water and energy cycle and hydrology at the continental scale, CLIC dealing with the cryosphere in relation with climate, and SPARC dealing with stratospheric and troposphere-stratosphere interaction.
The overall modelling activity is coordinated by two international working groups: WGNE, the Working Group on Numerical Experimentation, and WGCM, the Working Group on Coupled Models. They both conduct model intercomparison projects, respectively with global atmospheric models and coupled ocean-atmosphere models. WGNE conducts specific studies on the
28 parameterisation of surface fluxes, boundary layer and other turbulent transports, clouds and convection, including the intercomparison and validation of ocean-atmosphere and land- atmosphere fluxes. It also encourages the development of global reanalysis projects. WGCM deals in addition with the formulation and understanding of the various feedbacks within the climate system, and with the modelling of the 20th century climate; it is the main modelling group aimed at improving climate variability and trend forecasts at various time scales.
WCRP has sponsored, as part of WGNE, several intercomparisons of global chemical transport models: in 1990 for CFC simulation, in 1993 for the simulation of the global cycle of Rn222 and Pb210, in 1995 and again in 1998 for the simulation of S and Rn222/Pb210 (see introduction to COSAM, 2001 for a summary of all of the above). WCRP/WGNE intends to support a new aerosol intercomparison study under preparation with improved Rn222 source algorithms, air- surface exchange and transport processes, making use of new validation data from the global network of GAW and contributing partner stations.
4. REFERENCES
WMO/GAW, 2003, Current activities of the Global Atmosphere Watch Programme (as presented at Cg-XIV, May 2003) (GAW Report No. 152, WMO TD No. 1168). COSAM, 2001, Barrie, L. A., Y. Yi, W.R. Leaitch, U. Lohmann, P. Kasibhatla, G.-J. Roelofs, J. Wilson et al. A comparison of large scale atmospheric sulphate aerosol models (COSAM): overview and highlights, Tellus, 53B, pp. 615-645, 2001. WCRP, 2003, Annual Review of the World Climate Research Programme and report of the twenty-third session of the Joint Scientific Committee, January 2003 (WMO TD No 1137). See also website www.wmo.ch/web/wcrp.
29 Issues and Challenges of Using Natural Radionuclides as Tracers for Atmospheric Studies
H. N. Lee
1. INTRODUCTION
Atmospheric scientists have extensively used natural radionuclides, such as 222Rn, 210Pb and 7Be as tracers for atmospheric studies (Lee and Feichter, 1995; Barrie et al. 2001; Rasch et al., 2000). There still remain main issues that involve the improvement of sources of these tracers and global expansion of their measurements for global model validation.
Other issues of improvement of sources could be: what are the factors involved for improving the global 222Rn source flux ? How bad is it by using a constant 222Rn source flux of 1 atom/cm2/s ? Would neutron measurements and calculations help improve our determination of production rate related to 7Be source ?
For global expansion of measurements of these tracers, we could list a few. Into which region of the globe do we need to expand the surface radionuclide measurements? What is the best and most cost-effective way to expand the high altitude measurements? How can the community best collaborate with WMO/GAW? How can we improve quality of measurement ? Do the current global radionuclide measurements meet the needs for validating atmospheric models? What are the strength and weakness of global model? In other words, what approach do we need to continually improve the global model ?
In this paper, we will address the challenges in order to resolve some issues mentioned above.
2. 222Rn AND 7Be SOURCES
The accurate determinations of 222Rn and 7Be sources are essential to evaluation of global model performance. Unfortunately, they pose many difficulties because the 222Rn source flux depends on soil properties and atmospheric conditions (Schery and Wasiolek, 1998), and 7Be depends on the accurate calculation of neutron spectra in the stratosphere.
We have developed one-dimensional 222Rn model for calculating 222Rn source flux by considering the soil properties and atmospheric conditions. The governing equations involve:
(a) 222Rn distributions within the atmospheric boundary layer
where wi is a characteristic turbulent velocity scale and h is a boundary layer height. The boundary conditions are
30 (b) 222Rn distributions within the soil
where γ is a porosity, 8 a 222Rn decay constant, v a Darcy velocity, and D an effective diffusion coefficient, Tg a ground temperature, S a water moisture in soil, p and p0 are pressures in air and at sea-level. D0 is a pore-dependent diffusion coefficient
where kf, ke1 and ke2 are constants. ∆s is a soil density and E is a pore-dependent emission coefficient
(d) Soil model equations
Based on the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) model that was developed by NASA Goddard Space Flight Centre, we solved the surface energy budget equation, soil-water budget equation and the ground-soil temperature equation to obtain ground 222 temperature, Tg that is required for solving the Rn equations.
We have tested the 222Rn model mentioned above at Socorro, New Mexico, USA. Figure 1 showed the calculated and measured 222Rn surface flux associated with the atmospheric pressure. It is clearly seen that the diurnal variations of atmospheric boundary layer and pressure affect the 222Rn surface flux. The calculated flux is generally agreement with the measurement. Hence, the 222Rn concentration in the atmosphere and its surface flux can be calculated by incorporating the 222Rn model with a General Circulation Model that can provide ground temperature and soil parameters.
Figure 1: Comparisons of model calculated 222Rn surface flux with measurements corresponding with atmospheric pressure at Socorro, New Mexico, USA.
31 3. GLOBAL EXPANSION OF RADIONUCLIDE MEASUREMENTS AND QA/QC
Recently, EML expanded its radionuclide measurements to the remote areas in China. In December of 2001, EML’s system was operated at Guiyang site, southwest of China. In May of 2002, EML set up the measurements at Mt. Waliguan (a GAW site, as shown in Figure 2), northwest of China. In August of 2003, EML installed another RAMP system at Ryori, a GAW site in Japan. Figure 3 shows a multiyear timed series of monthly mean surface air concentrations of 210 7 Pb, Be and surface O3 measurements at New York City, New York, USA. The summer maximum of ozone corresponds well with the summer minimum of 210Pb and maximum of 7Be.
For QA/QC, we compared EML gamma counting for each weekly sample with the counting from the onsite Guiyang chemistry Lab at Guiyang site. Good agreement was found. At Mt. Waliguan site, we just start the QA/QC processes.
Figure 2: Mt. Waliguan Observatory, China.
New York, NY
0.8
0.6
0.4
0.2
Pb-210 Conc. (mBq/m3) Pb-210 Conc. Pb- 210 0 Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 D ec-97 Date
New York, NY
10 0.06
0.05 8
0.04 6 0.03 4
0.02 (ppm) Ozone
Be-7 Conc.(mBq/m3) 2 0.01 Be-7 Ozone 0 0 Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 D ec-97 Date
Figure 3: Monthly surface air measurements of 210Pb (top figure) and 7Be (bottom figure in blue dots) corresponded with the surface ozone measurements (bottom figure in red dots) at New York City, New York, USA.
32 4. VALIDATION OF GLOBAL MODEL
Various global models have been developed by scientists at their institutions. Here we will introduce a global chemistry model developed at the Meteorological Research Institute (MRI) in Japan. The model is an on-line 3-D global model coupled with MRI’s General Circulation Model. It consists of advective, diffusive and convective transport as well as the gas- and aqueous-phase chemical reactions. Removal processes including dry deposition (i.e., aerodynamic resistance) and wet deposition using Giorgi and Chameides scheme were taken into account. I improved the model by using the nonlocal eddy diffusivity approach in the atmospheric boundary layer and implemented an efficient method (Lee, 1997) for calculating surface eddy flux, rather than the Louis approach. Figure 4 showed the model calculations compared with the measurements at Guiyang site, southwestern China. The MRI global model with the improved boundary layer approach produced better agreement with the measurements than other models.
We need to have more measurements in Asian continental areas for model validation. Particularly, the atmospheric flow generated by the Himalaya Mountains could have a significant impact on global transport. We should enchance the measurements at Mt. Waliguan Observatory in the northeastern plateau of Tibet extending from the north of the Himalaya Mountains and at Mt. Fuji Observatory, both being located at about 4 km height in the free atmosphere. The measurements from these two locations are unique and very useful for examining the global model transport and performance.
Figure 4: Model calculations from TM2, MOCAGE and MRI were compared with the measurements at Guiyang site, southwestern China.
5. CONCLUSIONS
222Rn, 210Pb and 7Be can serve as natural tracers for modelling atmospheric flow. Accurate sources of these tracers are key inputs in model simulations and are continually being examined and improved. We expanded EML global surface measurements of these tracers and will continually collaborate with WMO/GAW installing EML’s system at GAW sites. Finally, I would suggest having another meeting/workshop on model-model comparisons with measurements by using improved 222Rn source flux stimulated from this workshop.
33 REFERENCES
Barrie, L.A., et al. A comparison of large-scale atmospheric sulphate aerosol models (COSAM): overview and highlights, Tellus, 53B, 615-645, 2001. Lee, H. N., 1997. ”Improvement of surface flux calculations in the atmospheric surface layer”, J. Applied Meteoro., 36, 1416-1423. Lee, H. N. and J. Feichter, 1995. “An intercomparison of wet precipitation scavenging schemes and the emission rates of 222Rn for simulation of global transport and deposition of 210Pb”, J. Geophys. Res., 100, 253-270. Rasch, P. J., J. Feichter, K. Law, N. Mahowald, J. Penner, C. Benkovitz, C. Genthon, C. Giannakopoulos, P. Kasibhatla, D. Koch, H. Levy, T. Maki, M. Prather, D. L. Roberts, G.-J. Roelofs, D. Stevenson, Z. Stockwell, S. Taguchi, M. Kritz, M. Chipperfield, D. Baldocchi, P. McMurry, L. Barrie, Y. Balkanski, R. Chatfield, E. Kjellstrom, M. Lawrence, H. N. Lee, J. Lelieveld, K. J. Noone, J. Seinfeld, G. Stenchikov, S. Schwartz, C. Walcek, D. Williamson, 2000. “A comparison of scavenging and deposition processes in global models: results from the WCRP Cambridge Workshop of 1995”, Tellus, 52B, 1025 – 1056, 2000. Schery S. D. and M. A. Wasiolek, 1998. “Modeling 222Rn flux from the Earth’s surface”, World Scientific, 207- 217, ISBN 981-02-3443-0.
34 Variation of 222Rn Flux and its Implication for Tracer Studies
Franz Conen (with contributions from my colleagues Lynette Robertson, David Stevenson and Jim Wright)
1. INTRODUCTION
Probably the first study on temporal variation of 222Rn flux from soil was conducted by Louis B. Smyth in Dublin in 1912, who concluded "The conditions influencing the escape of [222Rn] from the soil spaces to the atmosphere are very complex, and the various factors interfere with one another." Since then, numerous studies have been made to assess 222Rn fluxes from various soils and parts of the world. Most of them by direct measurements using accumulation chambers of different designs but generally covering areas smaller than 1 m2. Indirect measurements over much larger areas were also made by aircraft measurement of tropospheric 222Rn concentration profiles, mainly in the 1970's.
There is a large discrepancy between where we are and where we want to be in terms of defining the source term of 222Rn in atmospheric studies. It would be desirable to have a global map of 222Rn flux based on direct or indirect measurements, modelling of fluxes, or a combination of both. Any of these approaches is currently, and is likely to be for some time to come, limited by the lack of data from large parts of the world. This includes all of Africa, South America, Russia (Siberia), and to some extent China. Thus, in climate and air quality studies, 222Rn flux is usually assumed to be constant over time and space and on average about 1 atom cm-2 s-1 (or 76 Bq m-2h- 1) from ice free land surfaces. Regional mass balance studies have sometimes involved direct characterisation of the 222Rn source term and subsequent use of a region-specific (often smaller) 222Rn flux value. In general, model development has progressed to a point where improved knowledge of the 222Rn source term is needed for accurate validation.
Here, we review studies on spatial and temporal variation of 222Rn flux from soil and assess the possibility to account for them in atmospheric studies. The potential of a modified flux term for the global scale will be illustrated in an example. For the regional scale, we will also present the possibility to obtain high spatially and temporally resolved flux data by making use of existing networks for gamma radiation monitoring.
2. CONTROLLING FACTORS
222Rn flux from soil to atmosphere is a function of 222Rn production, emanation rate into air- filled pore space, transport through these pore spaces by diffusion and partial decay before escape into the atmosphere. Production of 222Rn which is relevant to surface flux is limited to the relaxation depth of 222Rn in the soil. This is the depth at which production rate equals decay rate. While in deep and well aerated soils this might be around 1-2 m, it is much less than that in wet soils (Dörr and Münnich, 1990). This depth, and therefore flux, might be substantially reduced by a shallow bedrock (Wilkening, 1974), or water table (Conen and Robertson, 2002, Levin et al., 2002). 226Ra, the precursor of 222Rn, can vary substantially in concentration above the relaxation depth. Soils formed on igneous rocks tend to have higher 226Ra concentrations than those developed on most sedimentary material; negligible amounts of 226Ra are found in peat. Emanation rate increases with increasing specific surface area of soil grains and is also dependent on the siting of 226Ra within grains, which can be modified by weathering processes (Schumann and Gunderson, 1996). At the very dry end of natural conditions, the emanation rate can be limited by low moisture content (Nazaroff, 1992). Transport rate, and thus the proportion of 222Rn that decays before reaching the soil surface, depends primarily on soil gas diffusivity which is modulated over time by rainfall and its impact on soil moisture (Lehmann et al. 2000; Ferry et al., 2001). Higher temperatures slightly enhance diffusion coefficients and might very modestly increase surface flux. Being slightly soluble in water, part of the 222Rn may become dissolved in soil water lining air filled pore spaces. Under very dry conditions, very small amounts of 222Rn may also be sorbed to, and desorbed from, solid surfaces (Schery and Whittlestone, 1989).
35 Other factors that have been reported to be correlated to 222Rn flux are fluctuations in pressure gradients between soil and atmosphere (Kojima, 1998), thermal gradients in the soil profile (Dueñas et al., 1997) and vegetation cover (Schery et al., 1989). However, these factors are closely related to differences and changes in soil moisture and are unlikely to have a strong functional relationship with 222Rn flux on their own. Under controlled conditions, for example, no impact on atmospheric pressure variations was found by Schubert and Schulz (2002). To summarise, the main factors controlling spatial variations in 222Rn flux are depth of aerated soil, soil 226Ra concentrations and emanation rate. The main factors determining temporal variations are precipitation and soil moisture. Shallow water tables can be a cause of temporal but also of spatial variation.
3. EXAMPLES OF VARIATION
3.1 Temporal
In the short term, 222Rn flux can be almost completely suppressed by heavy rain (Ferry et al., 2001). In the longer term, increasing imbalance between rainfall and evapo-transpiration leads to changes in water table and can have a longer term impact on the flux of 222Rn. This could explain some of the observed seasonal trends (Figure 3). Schüβler (1996), studying fluxes of 222Rn at different locations around Heidelberg, Germany, found the amplitude of seasonal cycles to depend on soil texture. On two purely sandy soils he observed no seasonality, on a sand soil covered with fluvial silt deposits he found a weak seasonal trend, and on two silty loam soils maximum fluxes in summer were twice as large as the minimum fluxes in winter. In modelling 222Rn on a global scale, Schery and Wasiolek (1998) found this scale of variation (factor of two) not to be uncommon. A slightly smaller variation was observed by Whittlestone et al. (1998) in Tasmania. They found summer fluxes to be about 50% higher than winter fluxes.
3.2 Spatial
No single study seems to have been undertaken to cover the global scale. To study spatial variations, we have to rely on a patchwork of individual studies conducted with different intensities by different groups at different times using different materials and methods. Also studies were conducted over areas ranging from square metres to an entire continent. This might somewhat exaggerate real differences in flux densities. The only geostatistical study, we are aware of was conducted throughout the state of Florida. It suggests a doubling of the geometric standard deviation in 222Rn flux when, for example, going from a 1 m2 area to an area of about 34 km2. This sort of relation held over 12 orders of magnitude in change in area (Nielson et al., 1996).
When looking at the frequency distribution of mean flux densities from 40 studies from around the world (as cited in Turekian et al., 1977 and Conen and Robertson, 2002), we find again a close to log-normal distribution (Figure 1). About half of the studies show means between 0.5 and 1.5 atom cm-2 s-1, one tenth are above this range and the rest below it. In geographical terms, studies are biased towards Europe (13 studies) and North America (16 studies), with coverage of Asia (7 studies) and Australia (3 studies, one of which covering the entire continent). There is only one published study from South America and none from Africa. No general pattern in global variations can be deducted from the evidence provided by these direct measurements.
However, indirect measurements over larger areas indicate that north of 30oN flux is declining from around 1 atom cm-2 s-1 to 0.2 atom cm-2 s-1 around 70oN (Figure 2). Global average 222Rn flux based on such a distribution would be 0.7 atom cm-2s-1 and identical with the estimate by Lambert et al. (1982), which is based on probably the most comprehensive 222Rn and 210Pb inventory. There has been one modelling study that produced a 1ox1o map of 222Rn flux based on soil 226Ra content, soil temperature and moisture (Schery and Wasiolek, 1998). It predicted regional variations of a factor of three not to be uncommon. However, current lack of detailed data on input parameters in large parts of the world means the modelled map is still preliminary and might change as more data becomes available. This might be a reason why the global average
36 222Rn flux based on this map is much higher (1.6 atom cm-2s-1), than the measurement based estimate by Lambert et al. (1982).
4. ACCOUNTING FOR VARIABILITY
4.1 Global Scale
While on the regional scale, adjustments are often made based on direct measurements in the region, little has been done on the global scale. In validating global models, 222Rn flux is generally assumed to be spatially uniform and 1 atom cm-2s-1 from ice-free land surfaces and zero from oceans. However, some have modified this assumption to a certain degree and found improved predictions.
Including emissions of 0.01 atoms cm-2s-1 from oceans between 60oS and 60oN improved predictions of measured 222Rn concentrations by the GCM NIRE-CTM-96 at remote sites in the South Indian Ocean and Antarctic (Taguchi et al, 2002). For continental emissions Lee and Feichter (1995) concluded that a non-uniform distribution (1 atom cm-2s-1 from 60oS to 60oN; 0.005 atoms cm-2s-1 from 60oN to 70oN) would improve predictions of global transport and deposition of 210Pb, a daughter product of 222Rn. A similar assumption (1 atom cm-2s-1 from 60oS to 60oN; 0.5 atoms cm-2s-1 from 60oN to 70oN) was made in a comparison of scavenging and deposition processes in global models at the WCRP Cambridge Workshop 1995 (Rasch et al., 2000).
A more profound modification of the source term based an observed decrease in flux between 30oN and 70oN was proposed by Conen and Robertson (2002). Recent indirect measurements on a tall tower in the eastern part of Siberia further support this conjecture (J. Moriizumi, personal communication). This northwards declining term was compared in the UK Met- Office model STOCHEM to the generally assumed uniform term in simulating 222Rn concentrations in the surface layer at 17 stations world wide. It reduced model / observation ratios for the 7 stations north of 30oN from 1.5 to 1.0 and reduced the root-mean-square-errors of predictions relative to measurements to half (Table 1).
Table 1: Comparison of model / observation ratios of 222Rn mixing ratios for uniform and northwards- declining 222Rn flux distributions (n is the number of stations).
Mean model/observation ratio Root-mean-square-error Geographic n Uniform Northwards- Uniform Northwards- coverage declining declining North of 30oN 7 1.52 0.98 1.00 0.50 South of 30oN 10 1.20 1.19 0.76 0.77 Global 17 1.33 1.11 0.87 0.67
Using the same northwards declining flux term, Gupta et al. (2003) found significant improvements in 222Rn predictions for the NARE-93 measurements over Nova Scotia.
4.2 Regional Scale
Source term estimates on the regional scale, for example for mass balance studies to estimate trace gas fluxes, are often based on direct measurements. Seasonal variation in 222Rn flux have been taken into account by Levin et al. (1999), but were omitted by others (Schmid et al, 1996; Moriizumi et al., 1996). Eckart (1990, cited in: Chevillard et al., 2002) produced a 222Rn flux map for Europe based on the FAO soil map and spot measurements on various soil types around Europe . Source terms indicated on this map were used in a regional transport model (REMO) to predict concentrations at a number of ground stations in Europe. Compared to a uniform flux term of 1 atom cm-2s-1 the map based term (0.3 to 1.5 atom cm-2s-1, depending on soil type) did not improve predictions (Chevillard et al. 2002). A similar study on a smaller area (200 x 200 km,
37 centred on Nagoya, Japan) showed improved predictions, when spatial variation in 222Rn flux was taken into account, as compared to a constant flux term (0.48 atom cm-2s-1) (Sakashita et al., 1997). Here, the 222Rn flux map was produced by weighted interpolation between direct measurements in the region. A method for predicting 222Rn flux on a regional scale has been proposed by Ieltsch et al. (2002). It is based on rock and soil chemical and physical properties. The current range of application is limited by the availability of information on these parameters.
We would like to propose another approach, which we think might be more readily applicable and could produce high temporal and spatial resolution of the 222Rn flux term with little effort. It might not be applicable in many parts of the world but there is certainly scope for it in highly industrialised countries. This approach is based on determining spatial and temporal variations in 222Rn flux from variations of routinely measured total gamma radiation. Spatial and temporal variations of gamma radiation are partially subject to the same parameters as the flux of 222Rn. Spatially, gamma radiation is fairly well related to soil 226Ra concentrations (Anagnostakis et al., 1995) and temporally it is closely related to soil moisture content (Peck et al., 1992). In two independent studies in Australia and in Florida, 222Rn flux has been found to be relatively well correlated with gamma radiation measured 1 m above ground, with correlation coefficients (r) above 0.5 (Schery et al., 1989, Nielson et al., 1996).
In some countries, gamma radiation is routinely measured on a regular basis by national radiation protection agencies or operators of nuclear plants as a measure for early detection of artificially enhanced radiation. In Germany, for example, 2150 stations with a mean distance between stations of 15 km measure continuously gamma radiation with a time resolution 2 h (Bundesamt für Strahlenschutz, http://www.bfs.de/info/themen/st9601/st9601.htm). Once properly calibrated against direct measurements of 222Rn flux at a number of stations, this information could be fed into regional transport models like meteorological data. Here, in a first attempt, we used a preliminary power regression function derived from the data published in Schery et al. (1989) after subtracting 30 nS from the original gamma radiation data for background correction, as proposed in Schery and Wasiolek (1998). We used this function (222Rn flux [Bq m-2h-1] = 0.44 x (gamma radiation [nSv h-1] -30)1.2485) to transform daily means of gamma radiation for all the stations in Germany for the year 2002. The result is a time series of 365 maps indicating the spatial and temporal variations in 222Rn flux for the country. It shows low 222Rn fluxes mainly in the northern part of the country and some small areas with high fluxes in mountainous areas. The spatial pattern is largely maintained over the season but superimposed by temporal changes. The monthly mean of the calculated 222Rn flux is within the range of directly measured fluxes around Heidelberg (Figure 4).
This is only a first attempt to illustrate the potential of using routine gamma radiation measurements to produce high resolution 222Rn source terms for regional scale studies. There is obviously still room for improvement. For example, gamma radiation can increase suddenly during rain because of 222Rn-daughters being precipitated (Nishikawa et al., 1995; Yamanishi and Miyake, 2003). This effect can last as long as the rain event and should be taken out. It might relatively easily be identified from the suddenness of the increase. On the time series of maps described before, these events show up like apparent fronts of high 222Rn emissions moving across the country mainly from the south-west to the north east.
5. CONCLUSION
5.1 Global Scale
No longer use 1 atom cm-2s-1 from 60oS to 70oN in global models but 1 atom cm-2s-1 from 60oS to 30oN, declining linearly to 0.2 atom cm-2s-1 at 70oN (until something better comes up).
Make direct and, where possible indirect, measurements in Africa, South America, Russia and China, to improve on this simplification and to provide calibration points for modelled maps.
38 5.2 Regional Scale
Get direct measurements trying to cover the full range of the regional variation. If possible, do stratified random sampling and calculate a regional weighted mean. Stratify by geology, soil thickness and type and water table depth.
Where applicable, identify networks of routine and continuous gamma radiation measurement over natural soils (national radiological protection boards, nuclear power stations, businesses handling radioactive material).
Establish the relationship between gamma radiation and 222Rn flux through direct measurements over brief periods at the same sites (or at some of them).
Find agreement with the institutions running the gamma radiation measurements to get access to the data (should be free and immediate: this is something where the IAEA and CEA could help!).
Create a commonly accessible database for 222Rn flux with high temporal and spatial resolution for entire regions (for example for France, Germany, Benelux, where there will also be continuous measurements of atmospheric 222Rn concentrations on tall towers).
ACKNOWLEDGEMENTS
We thank U. Stöhlker from Bundesamt für Strahlenschutz, Freiburg, Germany, for providing the gamma radiation data for Germany for 2002.
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39 Lee, H.N. and J. Feichter. 1995. An intercomparison of wet precipitation scavenging schemes and the emission rates of 222Rn for the simulation of global transport and deposition of 210Pb. Journal of Geophysical Research, 100, 23,252-23,270. Lehmann, B.E., M. Lehmann, A. Neftel, and S.V. Tarakanov. 2000. 222Rn monitoring of soil diffusivity. Geophysical Research Letters, 27, 3917-3920. Levin, I., M. Born, M. Cuntz, U. Langendörfer, S. Mantsch, T. Naegler, M. Schmidt, A. Varlagin, S. Verclas, and D. Wagenbach. 2002. Observations of atmospheric variability and soil exhalation rate of 222Rn at a Russian forest site. Tellus, 54B, 462-475. Levin, I., H. Glatzel-Mattheier, T. Marik, M. Cuntz, and M. Schmidt. 1999. Verification of German methane emission inventories and their recent changes based on atmospheric observations. Journal of Geophysical Research, 104, 3447-3456. Moriizumi, J., K. Nagamine, T. Iida, and Y. Ikebe. 1996. Estimation of areal flux of atmospheric methane in an urban area of Nagoya, Japan, inferred from atmospheric 222Rn data. Atmospheric Environment, 30, 1543-1549. Nazaroff, 1992. 222Rn transport from soil to air. Reviews of Geophysics, 30, 137-160. Nielson, K.K., V.C. Rogers, and R.B. Holt. 1996. Measurements and calculations of soil 222Rn flux at 325 sites throughout Florida. Environment International, 22 (Suppl. 1), S471-S476. Nishikawa, T., Tamagawa, Y., Aoki, M. and Okabe, S. 1995. Analysis of the time variation of environmental gamma radiation due to the precipitation. Applied Radiation and Isotopes, 46, 603-604. Peck, E.L., T.R. Carroll, and D.M. Lipinski. 1992. Airborne soil moisture measurements for the first international satellite land surface climatology program field experiment. Journal of Geophysical Research, 97, 18,961-18,967. Rasch, P.J., J. Feichter, K. Law, N. Mahowald, J. Penner, C. Benkovitz, C. Genthon, C. Giannakopoulos, P. Kasibhatla, D. Koch, H. Levy, T. Maki, M. Prather, D.L. Roberts, G.-J. Roelofs, D. Stevenson, Z. Stockwell, S. Taguchi, M. Kritz, M. Chipperfield, D. Baldocchi, P. McMurry, L. Barrie, Y. Balkanski, R. Chatfield, E. Kjellström, M. Lawrence, H.N. Lee, J. Lelieveld, K.J. Noone, J. Seinfeld, G. Stenchikov, S. Schwartz, C. Walcek, and D. Williamson. (2000). A comparison of scavenging and deposition processes in global models: results from the WCRP Cambridge Workshop of 1995. Tellus, 52B, 1025- 1056. Sakashita, T., A. Suzuki, T. Iida, and Y. Ikebe, 1997. Effects of atmospheric transport on temporal variations of 222Rn and its progeny concentrations in the atmosphere. Journal of Nuclear Science and Technology, 34, 63-72. Schery, S.D. and M. Wasiolek. 1998. Modeling 222Rn flux from the Earth's surface. In: Katase, A. and Shimo, M. (eds.): 222Rn and Thoron in the Human Environment. World Scientific, Singapore, pp. 207-217. Schery, S.D. and S. Whittlestone, 1989. Desorption of 222Rn from the Earth's surface. Journal of Geophysical Research, 94, 18,297-18,303. Schery, S.D., S. Whittlestone, K.P. Hart, and S.W. Hill. 1989. The flux of 222Rn and thoron from Australian soils. Journal of Geophysical Research, 94, 8567-8576. Schmid, M., R. Graul, H. Sartorius, and I. Levin. 1996. Carbon dioxide and methane in continental Europe: a climatology, and 222Rn-based emission estimates. Tellus, 48B, 457-473. Schubert, M. and H. Schulz. 2002. Diurnal 222Rn variations in the upper soil layers and at the soil-air interface related to meteorological parameters. Health Physics, 83, 91-96. Schumann, R.R. and L.C.S. Gundersen. 1996. Geologic and climatic controls on the 222Rn emanation coefficient. Environment International, 22, S439-S446. Schüβler. 1996. Effective Parameter zur Bestimmung des Gasaustauschs zwischen Boden und Atmosphäre. PhD thesis, University of Heidelberg. Smyth, L.B. 1912. On the supply of 226Ra emanation from soil to the atmosphere. Philosophical Magasin, 24, 622-637. Taguchi, S., T. Iida, and J. Moriizumi. 2002. Evaluation of the atmospheric transport model NIRE-CTM-96 by using measured 222Rn concentrations. Tellus, 54B, 250-268. Turekian, K.K., Y. Nozaki, and L.K. Benninger. 1977. Geochemistry of atmospheric 222Rn and 222Rn products. Ann. Rev. Earth Planet Sci., 5, 227-255.
40 Whittlestone, S., W. Zahorowski and S.D. Schery. 1998. 222Rn flux variability with season and location in Tasmania, Australia. Journal of Radioanalytical and Nuclear Chemistry, 236, 213-217. Wilkening, M.H. 1974. 222Rn from the island of Hawaii: deep soils are more important than lava fields or vulcanoes. Science, 183, 413-415. Yamanishi H. and H. Miyake. 2003. Separation of natural background by using correlation time-series data on radiation monitoring. Journal of Nuclear Science and Technology, 40, 44-48.
12
11
10 9 8
7
6 5 Frequency Frequency 4 3
2 1 0 -5 -4 -3 -2 -1 0 1 2 3
222 -2 -1 loge Rn flux (atom cm s )
222 Figure 1: Frequency distribution of mean Rn flux values (loge-transformed) for 40 studies from around the world using direct flux measurement methods.
1.2
) 1.0 -1 s
-2 0.8
0.6
0.4
Rn flux (atom cm 222 0.2
0.0 -80-60-40-200 20406080
Latitude
Figure 2: Distribution of 222Rn flux across the latitudes from 60oS (-60) to 70oN (70). North of 30oN, the often assumed flux of 1atom cm-2s-1 is indicated by the dotted line; open circles show values of indirect measurements which support the thought that flux might decline from 30oN to 70oN (Conen and Robertson, 2002). The continuous line is proposed as an alternative to the assumed constant 222Rn flux distribution of 1 atom cm-2s-1.
41 140
) -140 -1
h 120
-2 -120 100 -100 80 -80 60 -60
Rn Flux(Bq m 40 -40 222 -20 20 0 0 20 -20 40 -40 60 -60 80 -80 100 Jan May Sep Jan (cm) Water Depth Table
Figure 3: Seasonal trends in 222Rn flux and water table depth as observed in the garden of the Botany Department at the University of Edinburgh, UK in 2001. The lower limit of the water table (74 cm) was determined by underlying rocks.
120
100
) -1 80 h
-2
60
Rn(Bq flux m 40
222
20
0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 4: Monthly mean 222Rn fluxes for (open triangles) 5 sites near Heidelberg measured from 1987-1995 (data from Schüβler, 1996), and (closed circles) as calculated from measurements of total gamma dose rate covering all of Germany in 2002. Error bars indicate 1 standard deviation of the calculated estimates.
42 Progress on Global 222Rn Flux Maps and Recommendations for Future Research
S. D. Schery
1. INTRODUCTION
Schery and Wasiolek (SW 1998) published what was probably the first attempt to predict natural 222Rn flux from the entire Earth’s surface on a detailed grid (one degree by one degree spacing). Their methodology was based on a fundamental porous media model of 222Rn transport. After reformulation, the free parameters of their model (here called the SW model) were calibrated using global datasets then available for certain soil properties and a set of 101 experimental measurements of 222Rn flux, mostly from Australia. Predictions of the SW model suggested a significant regional variation (a factor of three was not uncommon) and significant seasonal variation (a factor of two was not uncommon) in 222Rn flux for land over the Earth’s surface.
Given the amount of detailed information used as an input into the SW model, it should hopefully provide some improvement in the picture of global 222Rn flux compared with earlier estimates. Many of these earlier estimates limited themselves to average values of flux for sea and land (regardless of position), or perhaps some limited variation of land flux based on latitude or atmospheric pressure. The SW model attempts to predict variation in land flux based on variation in 226Ra content of soil, soil moisture, and soil temperature.
At this point, I am aware of very little subsequent evaluation of the strengths and weaknesses of the SW model generated maps of 222Rn flux. Shoichi Taguchi (private communication, 2003) has tried them in a global chemical transport model (Taguchi et al., 2002) that predicts atmospheric 222Rn gas. The new maps appear to significantly alter predictions of atmospheric 222Rn compared with a more traditional source term (1 atom cm-2 s-1 with some reduction at high latitudes). Although on average the SW model gives some reduction in 222Rn flux with increasing latitude, it is not as great as that suggested by the recent work of Conen and Robertson (2002). As mentioned in the original SW model paper, the estimated annually-averaged 222Rn flux for land (34±9 mBq m-2 s-1 or 1.6±0.4 atom cm-2 s-1) is higher than that given by many previous estimates. This estimate probably warrants closer scrutiny since the overall normalization of the SW model had to be tied to calibration factors for soil 226Ra and 222Rn accumulator measurements through multiple steps. Notwithstanding this need for greater study of the existing SW model predictions, there are several straightforward ways in which it can be improved. They will be discussed later in this paper.
Most of the references directly relevant to the SW model can be found in SW 1998. There has been a fair amount of new work done using global chemical transport models to predict atmospheric 222Rn gas. Most of this work involves use of a traditional, or modestly modified, uniform flux as the source term. I will leave reference to this literature to other papers in this conference. I will also not reference the extensive new literature for evaluating the potential of soil to provide 222Rn gas to indoor housing. Unfortunately, in part due to the importance of pressure driven flow for that subject, much of the literature is not directly applicable to the natural 222Rn flux issue. A few new papers are more directly relevant to generating global maps of the natural 222Rn flux. For example, Conen and Robertson (2002) studied the trends of 222Rn flux variation from soil and proposed a new latitudinal variation. A study by Ielsch et al. (2001) demonstrated a correlation between 222Rn flux and a geochemical evaluation of the presence of uranium and thorium. Their work reinforces the commonly held view of the importance of 226Ra concentration for controlling the exhalation of 222Rn and might be useful for improving 226Ra maps for the SW model. The report of an intercomparison exercise by Hutter and Knutson (1998) is valuable for evaluating the accuracy of 222Rn flux measurements.
43 2. THE ORIGINAL SW MODEL
The original SW model was based on a fundamental porous media model of 222Rn transport in soil as outlined by Holford (1994). Her model had been quite successful at a site-specific prediction of 222Rn flux and its time variation using no free parameters (Holford, 1993, cited in SW 1998). However, since the fundamental independent variables needed for her model (such as soil porosity, emanating 226Ra fraction, etc.) were not generally available in global datasets, the SW model was reformulated in terms of less fundamental variables for which more global information was available.
A relative small set of 101 222Rn flux measurements was selected for calibration of the model. Although this set of measurements (primarily from Australia) was small and did not cover a wide enough variation in certain important variables, it did have the feature that measurements were mutually consistent and calibrated, and clear records of important auxiliary information (such as geographical coordinates, meteorological conditions, and soil conditions) had been recorded. A study of correlations between flux and soil properties indicated a relative strong correlation with soil 226Ra or a surrogate, surface gamma ray intensity. Much weaker correlations with soil moisture and soil temperature were also identified. Although there was reason to believe that correlations should exist with other properties of soil, no such clear correlations were identified with this measurement set and the then available global datasets. The final reformulated model for 222Rn flux F used to generate global maps was then
3 / 4 3 / 2 K F R(E / E m )(T/ 273 ) (1 - S ) | F | → , [1 - S+ S κ ]1 / 2 (1) E - K E 2 S → (1 - K E 1 e ), (2) E m
where KF is an overall normalization factor, T = KTTa + 273, S = KSd/dmax, and the values of the free parameters KF, KT (scale factor for temperature dependence), KS (scale factor for soil moisture dependence), KE1 and KE2 (both related to dependence of emanating fraction on soil moisture) were determined from least squares prediction of the flux data. The temperature dependence of the solubility coefficient κ was taken as 0.1048 + 0.405 exp(-0.0500KTTa). If the temperature Ta was less than 0°C, κ was fixed at its value for 0°C (0.51). The values of the independent variables 226 R (soil Ra activity concentration), Ta (air temperature as a surrogate for soil temperature), d/dmax (a parameter from Wilmott 1985 for soil moisture, cited in SW 1998) were obtained from global datasets. Schery and Wasiolek generated their own global dataset for R from published information on soil 226Ra, uranium surveys, gamma ray surveys, and geological information. This dataset was incomplete, and had large regions set at a country-averaged value, or even a globally- averaged value.
Figure1 shows examples of the predicted global 222Rn flux on a one degree by one degree grid for the average climate conditions of July and January. Southeast Asia and the USA are two good geographical areas to focus on since more detailed 226Ra information was available for them. A regional variation of flux is obvious within each area, in significant part due to variation in soil 226Ra content. Taguchi’s preliminary calculations with a global chemical transport model suggest that such regional variation in the flux causes significant regional variation in the predicted atmospheric 222Rn gas concentration and distribution. Although the exact magnitude of this regional effect may be in question, it is hard not to conclude that a more detailed (regionally varying) source term is needed in predictions of atmospheric 222Rn gas with chemical transport models. Comparing 222Rn flux in July with January, a significant seasonal effect for these same areas can also be seen. This seasonal variation is due to changes in soil moisture and soil temperature. Although the SW model’s calibration for these variables is not presently as well
44 determined as that for the soil 226Ra concentration, it seems likely that here also a seasonal (and general climate-related) variation of the 222Rn source term is needed for predictions of atmospheric 222Rn gas.
Figure 1: SW model predictions for surface 222Rn flux.
3. IMPROVEMENT OF THE SW MODEL
The most pressing need for improvement of the SW model is an expanded set of 222Rn flux measurements. These measurements need to cover a wider variation in key soil variables such as soil moisture and soil temperature as mapped by global datasets that would be used with the SW model predictions. The original set of 222Rn flux measurements was just too small and did not cover a wide enough sampling of these variables. Measurements from arctic climates were totally lacking. For several reasons, almost certainly a new measurement effort is required rather than a revised collation of historically published values. For one thing, much of the published data does not provide the necessary auxiliary information, such as exact position (latitude and longitude) of measurements and their date and time. Perhaps more important is the lack of documented quality control for many of the published measurements. For example, if new flux measurements are to be obtained by the accumulator method (there are other possibilities), it should be noted that only in recent years have some of the factors causing erroneous readings, such as back diffusion, been identified and quantified. Even so, the intercomparison exercise reported by Hutter and Knutson
45 (1998) indicated a standard deviation among measurements of participating groups of ± 34%. And this was for groups presumably expert in the technique operating under controlled conditions! I fear that measurement errors in the published values of much of the historical literature from divergent times, locations, and groups are probably much greater.
A new, improved set of measurements should be quite feasible, perhaps easily obtainable by a single group in a year using a standardized measurement protocol. In North America, a north- south transect that ran from the deserts of Mexico to the arctic of Canada or Alaska would go a long way to improving the calibration dataset. Something like a 25 or 50 km spacing might be sufficient, with one transect each for the winter and summer season. In Europe and Africa, the same sort of protocol going from the deserts of North Africa into the arctic of Scandinavia might be equally useful. An additional benefit of new, targeted measurement sets of this type is that they would provide a straightforward overall normalization for the model predictions of flux that could be more convincing than the present normalization requiring multiple steps.
Another point for improvement of the SW model is that there are now new global datasets for variables such as soil moisture and soil temperature that should improve predictions of the SW model. For example, the National Oceanic and Atmospheric Administration's National Centres of Environmental Prediction (NOAA NCEP) provides daily model predictions for soil temperature and moisture (such as contained in gblav.t00z.pgrbf12 from www.emc.ncep.noaa.gov/data). Preliminary studies with these seem to indicate that even with the existing, limited 101 flux measurements there is some improvement in the correlations. In any case, current datasets for variables such as soil moisture and soil temperature offer the possibility of current predictions for 222Rn flux rather than predictions based on average historical soil conditions. The assumed map for surface 226Ra is central to the predictions with the SW model. Schery and Wasiolek spent a lot of time generating such a map using such sources as soil 226Ra surveys, uranium and thorium aerial surveys, gamma ray surveys, and geological maps. Although probably only incremental progress can be expected on this subject, it will always be something that can benefit from further attention.
As suggested earlier, the existing SW model may not provide good predictions at the high latitudes, such as those for the arctic. This might be due to the inadequacy of the original soil moisture global dataset for predicting soil moisture at these latitudes, at least in the sense appropriate for the porous media transport model. However, it might be due to the fact that the model as given by Eqs. 1 and 2 assumes a homogeneous, semi-infinite soil layer. In practice, this condition is approximately met if the homogeneous soil depth is of the order of a meter or more. However, if the depth of the lower soil boundary (perhaps due to the presence of a water table) is smaller than a meter or so, a correction is in order.
It is not difficult to show that if the depth to the water table (or lower boundary of the soil) is L, then Eq. 1 should be approximately modified by the factor (KLL)/(1+ KLL) to give
3/ 4 3/ 2 KF R(E/ Em)(T/ 273) (1-S) (K L) L | F | → 1/ 2 , (3) [1-S+Sκ ] (K L L +1)
222 Here KL is a parameter that can be related to the inverse Rn diffusion length in the soil. However, for practical use KL would probably just become an additional free parameter adjusted to provide best prediction of the flux measurements. The challenge with Eq. 3 is to find a global dataset that provides suitable prediction of L. I have tried the soil depth given in the global dataset collection of Messon et al. (1995) and found it of little use in improving predictions with the existing 101 flux measurements. Perhaps a new global dataset for L needs to be generated, or perhaps some cruder approximation could be used. For example, if there is reason to believe that on average L decreases at higher latitudes, perhaps a latitude dependence of L could be built into the model.
46 Although it is really off the main subject of this paper, it might be worth mentioning that a second look should be given to the 222Rn flux value assigned to the oceans. This number is not well known, and, in all probability, also has some variation with position and meteorological conditions. Even though the flux for the oceans is undoubtedly small, the oceans form such a large part of the Earth’s surface that apparently atmospheric predictions of 222Rn gas are already becoming sensitive to the integrated effect from the assigned value.
4. CONCLUSIONS
(1) The present SW model predictions for 222Rn surface flux should be evaluated more thoroughly and further tested in global chemistry transport models. At the very least, this process will give an indication of the magnitude of the effect to be expected from a more detailed 222Rn source term that has significant regional and seasonal variation.
(2) A new, coordinated set of 222Rn flux measurements should be obtained that provide a much wider sampling of climate conditions and variation in soil moisture, temperature, and 226Ra concentration. North-south transects that go from low to high latitudes at an approximate spacing of 25 to 50 km would be very useful. The sites of such measurements should be chosen so as to match up with a wide variation in soil properties as predicted by updated global datasets.
(3) Improved global datasets for relevant soil properties now exist. These should be tested with the present SW model or any improved version.
(4) Consideration should be given to adding a soil depth variable to the SW model. For effective implementation, it may be necessary to generate a new global dataset for soil depth such as depth to water table. Surrogates for soil depth may need to be considered.
(5) Although the 222Rn flux from the oceans is small, the integrated effect from the large areas of ocean might be significant in global predictions of atmospheric 222Rn gas. Estimates of the 222Rn flux from the oceans should be re-examined. The possibility of a seasonal or regional variation should be considered.
REFERENCES
Conen, F., and L.B. Robertson. 2002, Latitudinal Distribution of 222Rn Flux from Continents, Tellus, 54B, 127- 133. Holford, D. J., et al., 1993, Modelling 222Rn Transport in Dry, Cracked Soil, J. Geophys. Res., 98, 567-580. Hutter, R. and E.O. Knutson. 1998, An International Intercomparison of Soil Gas 222Rn and 222Rn Exhalation Measurements, Health Phys., 74, 108 - 114. Ielsch, G., et al., 2000. 222Rn Level Variations on a Regional Scale: Influence of the Basement Trace Element (U,Th) Geochemistry on 222Rn Exhalation Rates, J. Environ. Radioactivity, 53, 75-90 Meeson, B. W., et al., 1995. ISLSCP Initiative I – Global Data Sets for Land-Atmosphere Models, 1987-1988, Volumes 1-5. Published on CD by NASA. Schery, S. D., and M.A. Wasiolek. 1998. Modeling 222Rn Flux from the Earth's Surface, in 222Rn and Thoron in the Human Environment, editors Katase, A. and Shimo,M., World Scientific, pages 207-217; 222Rn flux density datasets available at http://www.nmt.edu/~schery/mapdata.html. Taguchi, S., et al., 2002. Evaluation of the Atmospheric Transport Model NIRE-CTM-96 by using 222Rn Concentrations, Tellus, 54B, 250-268.
47 EML Global Network for Measuring Radionuclides
Colin G. Sanderson and H. N. Lee
1. INTRODUCTION
The Environmental Measurements Laboratory (EML) has a long history and an international reputation in natural and anthropogenic radionuclide measurements. EML has developed a worldwide sampling network for measuring low-level radionuclides, as shown in Figure 1. The network is composed of sites from EML’s Global Deposition Program (GDP), Surface Air Sampling Program (SASP), Remote Atmospheric Measurements Program (RAMP), and 222Rn Program. These programs, some of which have been in existence for over 50 years, consist of 39 fallout and 26 surface air sampling sites, representing the most extensive and comprehensive global sampling network of its kind for low-level radionuclide measurements. These radionuclide data have been used extensively by many atmospheric scientists for validating their transport models (Rasch et al., 2000; Lee and Feichter, 1995).
2. INSTRUMENTS FOR MEASURING RADIONUCLIDES
At each SASP site the air sampler, as shown in Figure 2, draws air through a filter to collect airborne radionuclides. The filters are changed weekly and returned to EML for analysis. RAMP sites contain EML’s remote atmospheric measurements systems which include an air sampler and an analyzer and detector system as shown in Figure 3. RAMP is an upgrade of SASP. The RAMP samples are analyzed for gamma-ray emitting radionuclides at the local site, and the resulting spectra are transmitted by satellite to EML. Additionally, the weekly samples are returned to EML and these samples are composited into monthly samples for analysis. EML maintains an extensive archive of samples that are available for retrospective studies, as well as an Internet database of the results of the analyses of these samples for various radionuclides at its web site (www.eml.doe.gov).
The RAMP systems require an on-site operator to: 1) load filters into the air sampler and the gamma-ray detector, 2) initiate the sample analysis and data collection processes, and 3) transmit the data to the ARGOS satellites. To overcome these requirements, a completely AUTOmatic RAMP (AUTORAMP) system as shown in Figure 4, was developed at EML. The AUTORAMP system will immediately and automatically transmit the resulting spectral data through a two-way modem link or a satellite telephone to the designated station. This allows us to perform a system status check, to order the system to start a count or transmit data for analysis. The system is suitable for very remote sites and an ideal tool for making measurements during an emergency situation.
EML has also developed a unique instrument called “The Beast,” as shown in Figure 5, that was designed for surface measurements of 222Rn using the two-filter method. It is an electromechanical device that collects total alpha particles resulting from 222Rn decay. The Beast is operated automatically by using a long filter tape connected with an automatically rewinding device. This instrument, which produces reliable and precise measurements of surface air 222Rn, has been validated with the National Institute of Standards and Technology (NIST). The comparisons of measurements from Beast with the standard sample concentrations provided by NIST are shown in Figure 6. The figure shows that the Beast produced good agreement with the NIST standards (Colle, et. al. 1996). Currently, the Beast is being continually operated at Pallas, Finland, a World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) site.
EML also developed an instrument as shown in Figure 7, called “Radgrabber.” This instrument was designed specifically for aircraft measurements of 222Rn. It uses electrostatic fields to collect charged 218Po directly on a solid-state detector. Polonium-218 is produced by the alpha decay of 222Rn. The measured 218Po (half-life 3.05 min) concentrations represent local 222Rn concentrations. This is especially true in the free troposphere where little neutralization of the
48 initially charged 218Po occurs. The inferred 222Rn concentrations are directly displayed and stored in an onboard computer. During the 1995 northeast aircraft field study of the U. S. Department of Energy’s (DOE) Atmospheric Chemistry Program, the measured 222Rn concentrations from the Radgrabber were used to characterize the profiles of vertical eddy diffusivities and mixing processes (Lee and R. J. Larsen, 1997).
3. SUMMARY
WMO’s GAW program recognizes the importance of radionuclide measurements and their contributions to atmospheric studies. Because EML has an international reputation for measuring surface air radionuclides it has been selected to assist WMO GAW by serving as the World Calibration Centre for Radioactivity (WCC-R) and a GAW radionuclide lead agency. The EML’s role, as a WCC-R, is to assist WMO GAW to establish the radioactivity measurements at the GAW sites. This activity will also expand the coverage of EML’s global network for measuring surface air radionuclides that are being used by atmospheric scientists for validating their global models and examining the atmospheric transport processes.
The instruments presented here are unique and have been used successfully for many years to measure natural radionuclides in the atmosphere.
REFERENCES
Colle, R., M. P. Unterweger, J. M. R. Hutchinson, S. Whittlestone, G. Polian, B. Ardouin, J. G. Kay, J. P. Friend, B. W. Blomquist, W. Nadler, T. T. Dang, R. J. Larsen and A. R. Hutter. 1996. “An international marine-atmospheric 222Rn measurement intercomparison in Bermuda, Part II: Results for the participating Laboratories”, J. Res. Natl. Inst. Stand. Technol., 101, 21-45. Lee, H. N. and R. J. Larsen. 1997. “Vertical diffusion in the lower atmosphere using aircraft measurements of 222Rn”, J. Applied Meteor., 36, 1262 – 1270. Lee, H. N. and J. Feichter. 1995, “An intercomparison of wet precipitation scavenging schemes and the emission rates of 222Rn for simulation of global transport and deposition of 210Pb”, J. Geophys. Res., 100, 253-270. Rasch, P. J., J. Feichter, K. Law, N. Mahowald, J. Penner, C. Benkovitz, C. Genthon, C. Giannakopoulos, P. Kasibhatla, D. Koch, H. Levy, T. Maki, M. Prather, D. L. Roberts, G.-J. Roelofs, D. Stevenson, Z. Stockwell, S. Taguchi, M. Kritz, M. Chipperfield, D. Baldocchi, P. McMurry, L. Barrie, Y. Balkanski, R. Chatfield, E. Kjellstrom, M. Lawrence, H. N. Lee, J. Lelieveld, K. J. Noone, J. Seinfeld, G. Stenchikov, S. Schwartz, C. Walcek, D. Williamson. 2000. “A comparison of scavenging and deposition processes in global models: results from the WCRP Cambridge Workshop of 1995”, Tellus, 52B, 1025 - 1056.
49
Surface Air Stations Total Deposition Stations Radon Sampling Sites Remote Atmospheric Measurements Program Stations
Figure 1: EML’s global sampling network for measuring low-level radionuclides.
Figure 2: EML’s air sampler. Figure 3: EML’s RAMP system.
50
Figure 4: EML’s AUTORAMP system. Figure 5: EML’s Beast.
Figure 6: EML’s measurements (blue solided lines) compared to the standardized sample concentrations provided from NIST (yellow shaded areas).
51
Figure 7: EML’s Radgrabber (left figure) installed in the DOE research aircraft Grumman Gulfstream-1 (right Figure).
52 222Rn in the Atmospheric Boundary Layer: A Contrast Between Measurements Made at a Baseline Site in The Southern Ocean and a Network of Sites in East Asia
Wlodek Zahorowski, Scott Chambers and Ann Henderson-Sellers
1. INTRODUCTION
222Rn is a gaseous decay product of uranium, which is ubiquitous in most rock and soil 222 types. It has a relatively short half-life (T0.5≈3.8days), and since terrestrial Rn fluxes are 2-3 orders of magnitude greater than oceanic fluxes, there is a large contrast between 222Rn concentrations in continental and aged oceanic air masses. Consequently, 222Rn monitoring at island or coastal sites provides insight into air mass history including the extent of recent land contact. This is a desirable characteristic since most anthropogenic atmospheric pollutants are also of terrestrial origin.
222Rn is inert, and relatively unsusceptible to wet or dry atmospheric removal processes [Jacob and Prather, 1990; Li and Chang, 1996], so its predominant atmospheric sink is radioactive decay. Although the emission rate of 222Rn from terrestrial ice/snow free surfaces is often assumed to be a constant ~1 atom cm-2 s-1 [e.g. Dentener et al., 1999], there is mounting evidence to suggest that latitudinal and regional gradients exist, and need to be accounted for in simulations [e.g. Schery and Wasiolek, 1998; Conen and Robertson, 2002]. Since its half-life is comparable to the lifetimes of short-lived atmospheric pollutants (e.g. NOx, SO2, CO, O3), the residence times of water and aerosols, and the time scale of many important aspects of atmospheric dynamics, 222Rn is a particularly useful tracer at local, regional or global scales.
This presentation will focus on selected features of 222Rn measurements performed at four ground stations as part of the Aerosol Characterisation Experiment-Asia in 2001, and at Cape Grim, Tasmania.
2. SITES
The Cape Grim Baseline Air Pollution Station is located in north-western Tasmania (40°39’S, 144°43’E). The sample intake for the detector is 70 m above ground level (AGL) and about 160 m above sea level (ASL). There are three well defined fetch areas for this site: oceanic (190 0 -2800), continental (280 0 -90 0) and Tasmanian (90 0 -190 0). The Hok Tsui 222Rn detector is located on the southeastern corner of Hong Kong Island at Cape D’Aguilar (22°12’N, 114°15’E). The sample intake for the detector is 15 m AGL. The measurement site is situated on a bluff, 60 m ASL, facing the South China Sea. At this point, the Chinese coastline runs approximately south- west to north-east, such that the north-west and south-east quadrants represent primarily continental and oceanic fetch, respectively. The Gosan 222Rn detector is located on the western coast of Jeju Island, South Korea (33°18’N, 126°09’E), with the sample intake point roughly 5m AGL (50m ASL), facing the Chinese mainland, approximately 500km across the Yellow Sea. The most open oceanic fetch is from southeast to southwest of the site. The nearest land is the South Korean peninsula approximately 100km to the north, and Japan, approximately 300km to the east. The Sado detector is located on the western coast of Sado Island (38°12’ N, 138°21’ E). The sample intake for the detector is 5 m AGL (135 m ASL), facing the Sea of Japan. The Mauna Loa Observatory is situated on the northern face of the Mauna Loa volcano (19°32.3’N, 155°34.7’W), on the island of Hawaii, at an elevation of 3397 m ASL. This site, in the central Pacific Ocean, is roughly 8000 km from the east coast of China. The sample intake point is 40m AGL. Anabatic and katabatic winds influence the observations at this site on a daily basis [Mendonca, 1969]. Appropriately selected observations, within a nocturnal sampling window of 2200-0700 hours, are understood to be representative of the troposphere between 700-500 hPa (3-5.5 km) [Harris and Kahl, 1990; Perry et al., 1999], and free of most local influences.
53 The deployed 222Rn detectors are dual flow loop two filter detectors [Whittlestone and Zahorowski, 1998] with the delay volume equal to 750L (Hok Tsui, Gosan and Sado), 1,500L (Mauna Loa) and 5,000L (Cape Grim).
3. 222Rn ANGULAR DISTRIBUTION
Figure 1 shows the angular distribution of 222Rn concentration observed Cape Grim, Hok Tsui and Gosan. It is clear that sector analysis (i.e. categorisation by wind direction) provides a useful breakdown of the Cape Grim data into the three main fetch areas. A similar sector analysis is also possible at Hok Tsui. However, the ratio between minimum oceanic and maximum continental 222Rn concentrations at Hok Tsui is much higher than at Cape Grim, suggesting a higher degree of mixing of the oceanic and continental/island air in the nominally oceanic sector at Hok Tsui. In contrast to these sites, the angular distribution of 222Rn at Gosan is almost isotropic, pointing to a more complex history of air parcel trajectories. This highlights the necessity of using a tracer such as 222Rn to indicate recent land contact, in conjunction with other means to approximate geographic fetch areas, such as back trajectory analysis.
4. BACKGROUND 222Rn CONCENTRATION
Knowledge of the background 222Rn concentration is indispensable in tracer-tracer studies, which often use the background 222Rn concentration, or some related quantity, as a threshold for the selection, and subsequent analysis of, different categories of events. For instance, oceanic (baseline) events at Cape Grim can be clearly identified using a single 222Rn concentration threshold of 100 mBq m-3, irrespective of season [Gras and Whittlestone, 1992]. However, this is clearly not the case for the other stations in this study. Figure 2 shows weekly averages of the daily minimum 222Rn concentration at Hok Tsui, Gosan, Sado and Mauna Loa. The daily minimum values were calculated from 222Rn concentrations recorded within a fixed time window corresponding to the minima of the respective diurnal composite 222Rn concentration plots. These weekly averages are a close approximation of the background 222Rn concentration at each site. Regardless of particular air mass origin, the background 222Rn concentration shows a strong seasonality. As expected, the sites that exhibit the maximum and minimum amplitude seasonal cycle are the coastal site (Hok Tsui), and marine site (Mauna Loa), respectively.
The seasonal variability of background 222Rn concentration at each site clearly points to continental outflow from Asia to the Pacific. The fact that the seasonal background 222Rn signals of the south-east Asian sites are out of phase with that of Mauna Loa can be attributed to separate outflow mechanisms from the Asian continent to the Pacific. The surface sites in south-east Asia respond to the low level (boundary layer) outflow events that are linked to the monsoonal circulation pattern (offshore in winter, onshore in summer). On the other hand, MLO observations are representative of the mid-tropospheric outflow events from the Asian continent, caused by rapid westerly advection in the jet stream, which are most pronounced in winter-spring.
Another interesting feature of the seasonal change in background 222Rn concentrations at Hok Tsui, Gosan and Sado is the latitudinal dependence (Figure 2): the higher the latitude the smaller the seasonal variation of the background. Also, in summer, the time of the year when continental outflow in the boundary layer is minimal, there is a degree of overlap in background values at the three sites.
The results from south-east Asia contrast with those from Cape Grim, where background 222Rn concentrations show only a very weak seasonality. An analysis of 222Rn concentrations in air masses after a change to the oceanic sector shows that concentrations return to those typical of the oceanic fetch within 20-30 hours after the change. This is evident in Figure 3, which shows the evolution of mean 222Rn concentration (and corresponding 95% confidence intervals), in the composite oceanic event for consecutive hours after a change to the oceanic sector. Here, an oceanic event is defined as any set of consecutive hourly observations coming from the oceanic sector. The widening of the 95% confidence interval with increasing event duration is indicative of the diminishing data availability. The most prominent feature of this plot is the initial transitional
54 period. This is characterised by rapidly decreasing 222Rn concentrations, and represents a period during which mixed fetch conditions prevail. It is clear that within the first 20-30 hours of a change to the oceanic sector, 222Rn concentrations reach a range typical of that for the oceanic sector. Most importantly, for these observations at Cape Grim, neither the duration of the transitional period, or the final equilibrium oceanic concentration, depend on season.
5. 222Rn FETCH AREAS
A well-defined continental or oceanic fetch is of interest as it might provide information about the 222Rn source term and its relative contribution to the observed 222Rn concentrations.
5.1 Continental fetch (Cape Grim and Mauna Loa)
Figure 4 shows the monthly mean 222Rn concentration of air masses within the continental sector at Cape Grim, for the composite year 1987-2001. The contributing hourly 222Rn concentrations were selected based on: the sector definition; time in the sector (the first two hours in the sector were excluded); and wind speed (observations during low wind speeds were excluded). The most striking feature of this figure is a strong seasonality in the monthly means values, with a summer (Dec-Feb) minimum and late spring – early winter maximum. These results indicate that the 222Rn flux within the fetch region, which, due to changing soil moisture conditions, exhibits a summer maximum, and winter minimum [Whittlestone et al., 1998], is not the dominant factor in determining the overall 222Rn signal.
An approach based on the analysis of back trajectories was applied to the MLO 2001 222Rn record to identify any latitudinal variability in the 222Rn source in East Asia and characterise its seasonal variability. Three latitude bands were defined (20°-30°N, 30°-40°N and 40°-50°N) to span the primary band of tropospheric outflow from the Asian continent to the Pacific [20°-50°N; Talbot et al., 1997; Gregory et al., 1997; Crawford et al., 1997]. Trajectories were grouped by the latitude band within which they crossed the Asian coastline, and by season. The underlying assumption was that trajectories that cross the coast within this band remain within the band whilst over the continent for at least few days. An example of the band 30°-40°N spring trajectories is presented in Figure 5a.
The distribution of 222Rn concentrations (10th, 50th, 90th percentile) corresponding to the selected trajectories was calculated for each latitude band and season that was sufficiently well represented (Figure 5b). In each case, 222Rn concentrations were corrected for decay over the ocean, with the assumption of zero 222Rn input from below whilst the air mass was over the ocean. One pronounced feature of Figure 5b is the observed seasonality in 222Rn concentration. Within both latitude bands the lowest concentrations are observed in winter and the highest in spring. This is in agreement with other studies that have identified spring as a time of peak aerosol transport from the Asian continent to the Pacific [Merrill et al., 1989; Balkanski et al., 1992; Crawford et al., 1997; Jaffe et al., 1997]. The other striking feature is that the 222Rn signal is higher in the higher of the two latitudinal bands, whereas presently available evidence points to a reduction in 222Rn flux with latitude in this region [e.g. Conen and Robertson, 2002; Schery and Wasiolek, 1998]. In support of the Cape Grim findings, these results suggest that 222Rn flux, an important parameter in model simulations, may not be the dominant factor in the determination of seasonal variability in 222Rn concentration from a given fetch region.
5.2 Oceanic fetch (Cape Grim and Gosan)
After the initial 20-30 hours in the Cape Grim oceanic sector, mean 222Rn concentrations in the composite oceanic event do not change within the indicated confidence interval (Figure 3). This suggests that 222Rn concentrations from this portion of the composite oceanic event are minimally perturbed from those in air masses that are in equilibrium with the oceanic 222Rn flux. Based on this equilibrium concentration, and an estimated height of the marine boundary layer, a simple expression for the average oceanic 222Rn flux can be derived, and applied, to yield an experimental
55 estimate of the 222Rn flux in the Cape Grim oceanic fetch area [Zahorowski et al., 2003]. Whilst higher than most existing point measurements of oceanic 222Rn flux [Wilkening and Clements, 1975; Hoang and Servant, 1972], this estimate was in close agreement with estimates of the oceanic 222Rn flux based on modelling studies [Jacob et al., 1997; Mahowald et al., 1997].
The selection of events corresponding to the equilibrium 222Rn concentrations in the above example was based on wind direction alone. At Gosan, where the angular distribution of 222Rn concentration is nearly isotropic, a combination of 222Rn concentrations and back trajectory analysis is required to identify events corresponding to an oceanic fetch. Figure 6a shows that in spite of the influence of continental outflow events and extensive local mixing, that often result in a high background 222Rn concentration even in summer, persistent periods characterised by a significant drop in the minimum weekly 222Rn concentration can still occur. 10-day back trajectories corresponding to 222Rn concentrations below the 10th percentile value were calculated for this spring-summer period of low 222Rn concentrations. A subset of these trajectories, at 3 hourly intervals, is shown in Figure 6b, and clearly indicates a well defined oceanic fetch.
6. SOME REMARKS ABOUT EXPERIMENTAL REQUIREMENTS
The precision and accuracy of 222Rn data collected at ground stations and used for comparison with global and regional atmospheric transport models is in most cases more than adequate. At present, 222Rn detectors can routinely achieve a lower limit of detection of 20 mBq m- 3 for a one hour count [Whittlestone and Zahorowski, 1998]. Here, the lower limit of detection is defined as the 222Rn concentration at which the statistical error of the total one hour count is about 30%. However, this is not always good enough, even in regions with relatively high background 222Rn concentrations. High-resolution 222Rn concentrations in aged marine are best covered using a lower limit of detection of about 10 mBq m-3. Whilst it is possible to build such systems, it is necessary to sacrifice the compactness of the delay volume, and the low power requirements. A lower limit of detection better than 10 mBq m-3 would be required for pseudo-Lagrangian experiments over oceanic fetch regions, using paired 222Rn detectors. Although a 1 mBq m-3 detector could be developed in the foreseeable future, this might prove difficult and expensive, since the required construction materials would have to have a very low background.
Commercially available calibration sources, traceable to 226Ra standards maintained by national organizations like NIST, claim a ±4% accuracy of the 222Rn yield. At low to very low 222Rn concentrations typical of aged marine air, the measurement accuracy of 222Rn detectors is dominated by the counting error. For higher concentrations (100-500 mBq m-3, depending on the system), the measurement accuracy becomes dominated by the uncertainty of the calibration.
7. CONCLUSIONS
The simple source and sink mechanisms of atmospheric 222Rn, relatively short half-life, and large contrast between terrestrial and oceanic fluxes, make 222Rn an ideal atmospheric tracer at regional to global scales. Depending on the geography of fetch areas surrounding a site, either 222Rn sector analysis, or a combination of 222Rn thresholds and trajectory analysis are well suited to define fetch areas of most and least recent land contact. This has clear and direct implications for the potential of the corresponding air masses to be affected by natural or anthropogenic pollutants. Comparing and contrasting 222Rn observations from sites in the northern and southern hemisphere has highlighted several important issues: (i) due consideration should be given to the definition of oceanic and background 222Rn concentration ranges at each site. Although their may be periods where the values overlap, they represent potentially different types of air masses; (ii) the seasonal variability of 222Rn flux in a given fetch region may not be the dominant influence on observed seasonal 222Rn concentrations, and; (iii) contemporary 222Rn detectors perform sufficiently well for most purposes. Although applications can be envisaged that would require 222Rn detectors with better lower limits of detection, with the presently available technology, such detectors would be expensive, bulky and have high power consumption.
56 REFERENCES
Balkanski, Y.J., D.J. Jacob, R. Arimoto and M.A. Kritz. 1992. Distribution of 222Rn over the North Pacific: implications for continental influences. Journal of Atmospheric Chemistry, 14, 353-374. Conen, F. and L.B. Robertson, 2002. Latitudinal distribution of 222Rn flux from continents. Tellus, 54B, 127- 133. Crawford, J., D. Davis, G. Chen, J.D. Bradshaw, S.T. Sandholm, Y. Kondo, et al. 1997. An assessment of ozone photochemistry in the extratropical western North Pacific: Impact of continental outflow during the late winter/early spring. Journal of Geophysical Research, 102(D23), 28,469-28,487. Dentener, F., J. Feichter, and A. Jeuken. 1999. Simulation of the transport of Rn222 using on-line and off- line global models at different horizontal resolutions: a detailed comparison with measurements. Tellus, 51B, 573-602. Gras, J.L. and S. Whittlestone. 1992. 222Rn and CN: Complimentary tracers of polluted air masses at coastal and island sites. Journal of Radioanalytical and Nuclear Chemistry, 161, 293-306. Gregory, G.L., J.T. Merrill, M.C. Shipham, D.R. Blake, G.W. Sachse and H.B. Singh. 1997. Chemical characteristics of tropospheric air over the Pacific Ocean as measured during PEM-West B: Relationship to Asian outflow and trajectory history. Journal of Geophysical Research, 102(D23), 28,275-28,285. Harris, J.M. and J.D. Kahl. 1990. A descriptive atmospheric transport climatology for the Mauna Loa Observatory, using clustered trajectories. Journal of Geophysical Research, 95(D9), 13,651-13,667. Hoang, C.T. and J. Servant. 1972. 222Rn flux from the sea (in French). C. R. Acad. Sci. Paris, 274, 3157- 3160. Jacob, D.J. and M.J. Prather. 1990. 222Rn as a test of convective transport in a general circulation model. Tellus, 42(B), 118-134. Jacob, J.J., M.J. Prather, P.J. Rasch, R.-L Shia, Y.J. Balkanski, S.R. Beagley, et al. 1997. Evaluation and intercomparison of global atmospheric transport models using 222Rn and other short lived tracers. Journal of Geophysical Research, 102(D5), 5953-5970. Jaffe, D.A., A. Mahura, J. Kelley, J. Atkins, P.C. Novelli. and J.T. Merrill. 1997. Impact of Asian emissions on the remote North Pacific atmosphere: Interpretation of CO data from Shemya, Guam, Midway and Mauna Loa. Journal of Geophysical Research, 102(D23), 28,627-28,635. Li, Y. and J.S. Chang. 1996. A three-dimensional global episodic tracer transport model. 1. Evaluation of its transport processes by 222Rn simulations. Journal of Geophysical Research, 101(D20), 25,931- 25,947. Mahowald, N.M., P.J. Rasch, and B.E. Eaton. 1997. Transport of 222Rn to the remote troposphere using the Model of Atmospheric Transport and Chemistry and assimilated winds from ECMWF and the National Centre for Environmental Prediction/NCAR. Journal of Geophysical Research, 102(D23), 28,139- 28,151. Mendonca, B.G. 1969. Local wind circulation on the slopes of Mauna Loa. Journal of Applied Meteorology, 8, 533-541. Merrill, J.T., M. Uematsu and R. Bleck. 1989. Meteorological analysis of long range transport of mineral aerosols over the North Pacific. Journal of Geophysical Research, 94(D6), 8,584-8,598. Perry, K.D., T.A. Cahill, R.C. Schnell, and J.M. Harris. 1999. Long-range transport of anthropogenic aerosols to the national Oceanic and Atmospheric Administration baseline station at Mauna Loa Observatory, Hawaii. Journal of Geophysical Research, 104(D15), 18,521-18,533. Schery, S.D. and M.A. Wasiolek, 1998. Modelling 222Rn flux from the Earth’s surface. Proceedings of the 7th Tohwa University International Symposium 222Rn and thoron in the human environment, Fukuoka, Japan, 23-25 October 1997. Eds. A. Katase and M. Shimo. World Scientific, Singapore. Talbot, R.W., J.E. Dibb, B.L. Lefer, J.D. Bradshaw, S.T. Sandholm, D.R. Blake, et al. 1997. Chemical characteristics of continental outflow from Asia to the troposphere over the western Pacific Ocean during February - March 1994: Results from PEM-West B. Journal of Geophysical Research, 102(D23), 28,255-28,274.
57 Whittlestone, S. and W. Zahorowski, 1998. Baseline 222Rn detectors for shipboard use: Development and deployment in the First Aerosol Characterisation Experiment (ACE 1). Journal of Geophysical Research, 103(D13), 16,743-16,751. Whittlestone, S., W. Zahorowski and S.D. Schery, 1998. 222Rn flux variability with season and location in Tasmania, Australia. Journal of Radioanalytical and Nuclear Chemistry, 236, 213-217. Wilkening, M.H. and W.E. Clements, (1975). 222Rn from the ocean surface. Journal of Geophysical Research, 80(27), 3828-3830. Zahorowski, W., Chambers, S. and Henderson-Sellers, A. A method for the estimation of regional oceanic radon-222 fluxes. To be submitted to GRL.
Zahorowski, W., S. Chambers, T. Wang, C.-H. Kang, I. Uno, S. Poon, S.-N. Oh, S. Werczynski, J. Kim and A. Henderson-Sellers. Radon-222 in boundary layer and free tropospheric continental outflow events at three ACE-Asia sites. Submitted to Tellus B.
58 -3 (c) Radon (mBq m-3) (a) Radon (mBq m-3) (b) Radon (mBq m ) 0 0 0 4000 12000 340 20 340 3000 20 340 20 320 40 320 40 320 40 2000 8000 300 2000 60 300 60 300 60 1000 4000 280 80 280 80 280 80 0 0 0 260 100 260 100 260 100
240 120 240 120 240 120
220 140 220 140 220 140 200 160 200 160 200 160 180 180 180
Figure 1: Angular distribution of 222Rn concentration at Cape Grim, Hok Tsui and Gosan.
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-3 10000
1000
Radon (mBq m (mBq Radon
100 1 1121314151
Week of year
Figure 2: Weekly averages of minimum diurnal 222Rn concentration at the four ACE-Asia sites (note the logarithmic scale). Hok Tsui (filled circles), Gosan (open circles), Sado (open triangles) and MLO (filled triangles).
Figure 3: Mean 222Rn concentration, ±95% confidence intervals, as a function of time after change to the oceanic sector at Cape Grim (based on data 1987-2001).
59 2000
) 1500 -3
1000
Radon (mBq m (mBq Radon 500
0 JanMarMayJulSepNov
Figure 4: Mean monthly 222Rn concentration in the Cape Grim continental sector for the composite year (1987-2001).
1800 Dec-Feb Mar-May Jun-Aug Sep-Nov ) 50 -3 1200 N) 0
30 600 Radon (mBq m (mBq Radon Latitude ( MLO 0 10
100W140W 180 140E 20-30 30-40 20-30 30-40 20-30 30-40 20-30 30-40 0 Longitute Latitude Band ( N)
Figure 5: (a) The 30°-40°N band Spring 2001 back trajectories corresponding to 222Rn concentrations measured at Mauna Loa at 0000, 0300, and 0600 hours LT. (b) The seasonal distribution of 222Rn concentrations (10th, 50th, 90th percentile) corresponding to the 20°-30°N and 30°-40°N band trajectories. 222Rn concentrations were corrected for decay over the ocean.
60 2400
50 ) -3
1600 N) 0 40
30
800 ( Latitude Radon (mBq m Radon (mBq 20
0 10 20 30 40 50 10 100 120 140 Week of year Longitude (0E)
Figure 6: (a) Weekly 222Rn minima (mBq m-3) for Gosan in 2001; (b) A cluster of 10-day back trajectories at 3 hourly intervals during an oceanic event in weeks 25,26,and 27, for air masses terminating at Gosan.
60 Natural Radionuclides as Tracers in Multi-Compartment Transport Models
Johann Feichter and Gerhard Lammel
1. INTRODUCTION
Many attempts have been made in recent years to understand the physical, chemical and biological processes that constitute the Earth-atmosphere system using global numerical models. Beyond questions focusing on the physical climate system these so-called Earth-System -Models (ESM) include also model components which describe the biogeochemical cycles and their interactions with other aspects of the Earth system. This comprises the analysis of interactions of the carbon, nitrogen or sulphur cycle and biologically relevant elements, and the investigation of the feedbacks between tropospheric chemistry, the cycling of aerosol particles, and climate. ESMs are also applied to simulate dispersion and persistence of multicompartmental and slowly degrading organic substances (persistent organic pollutants POPs). These various components of the Earth system are coupled by the exchange of radiative energy, momentum and mass. The accuracy of ESMs depends directly on the quality in the representation of these exchange processes, many of which are not explicitly resolved by these models, but play a key role in the Earth system. Parameterizations of processes such as convection, turbulent exchange within the boundary layer and vertical transport in clouds, etc. rely on detailed observational studies. This paper deals with transport of gaseous and particulate mass within a compartment and the exchange between compartments and addresses the potential of radionuclides as test tracers to evaluate these transport processes. As an example for multi-compartment transport we present simulations of the global environmental fate of two pesticides.
2. TRANSPORT PROCESSES
Transport processes control the chemical composition and the life-time of specific constituents in different reservoirs. The atmosphere possesses a large spectrum of motions from planetary waves, synoptic scale disturbances, meso-scale processes to turbulent exchange. The scales of motion that are important for the transport of a specific constituent depend on the atmospheric residence time of the species in question. Generally, the distribution of highly reactive species is dominated by chemical and microscale interactions at surfaces, while that of less faster reacting species is dominated by fast mixing processes, and that of slowly reacting species by large-scale transport. On larger spatial scales the winds transport species with long lifetimes far away from the source region. Pollutants are moved across entire continents. Subgrid-scale processes, such as turbulent exchange and vertical transport in clouds, dilute quite efficiently polluted boundary layer air by mixing with free tropospheric air masses. The degree of vertical mixing controls the dry deposition at the ground, the transit time until a parcel enters a cloud or the rate of photochemical decomposition. Table 1 shows characteristic time-scales of different transport processes.
Table 1: Characteristics atmospheric transit times (Feichter, 2000). Processes Transit time Vertical transport within convective clouds 1 hour Mixing between the PBL and the free troposphere 2 - 10 days Large-scale vertical mixing in the troposphere 1 - 4 weeks Mixing within latitude belts 2 - 4 weeks Hemispheric mixing 2 - 6 months Interhemispheric exchange 1 year Stratospheric-tropospheric exchange 1-3 years Transport from the surface up to the mesosphere 5-8 years
61 Surface exchange includes upward fluxes if the vegetation, ocean and land surface is a source of the compound or deposition if the surface is a sink. The transport of contaminants in soil and plant systems depends on the properties of the contaminant, aqueous phase flow, soil properties, and size and growth of the plants. There is convective flow of the aqueous phase in soil, plant roots, and plant stems because of differences in the pressure of water. Significantly larger quantities of water are lost to the atmosphere through evapotranspiration when growing plants are present. Contaminants are transported to the soil surface in plant roots and in the soil. The rate at which contaminants are moved from the soil to the atmosphere is limited by the dissipation of water vapor into the atmosphere. Thus, when the contaminant and water move upward together, the rate is limited by the rate of evapotranspiration which is limited by the dissipation of the soil water into the air. Erickson et al. (1997) have shown that for many contaminants, plants may be used as part of a solar driven pump-and-treat system.
A fraction of contaminants find their path towards terrestrial and marine aquatic systems by removal from the atmosphere and deposition on land and ocean surfaces by precipitation. A fraction may be incorporated in the biomass or retained in soils, but other fraction reaches via surface runoff and groundwater circulation, the surface freshwater systems and the oceans. About 22% of the global precipitation falls on land. About one third of this precipitation amount is carried to the oceans by rivers and about 2% as groundwater runoff. Dispersion of chemical species in the ocean occurs on much longer time-scales than in the atmosphere and is mainly associated with the oceanic currents. Surface circulation in ocean currents transports species from low to high latitudes within about 0.5-1 year. Vertical mixing within the oceanic mixing layer (~300 m) has a typical time scale of about 20 years.
3. LONG-RANGE TRANSPORT AND MULTI-COMPARTMENT PARTITIONING OF POPS
International efforts to control the environmental effects of substances are under way leading to international environmental policy regimes (UNEP). Research is needed to scientifically based identify POP candidates. Currently, only box models are available to study the multimedia fate of semivolatile organic substances. These allow to identify tendencies but cannot quantify the exposure of the environment. For adequate account of geophysical transports, we develop and apply a multicompartment chemistry-transport model, which is based on the atmospheric general circulation model ECHAM (Roeckner et al., 1996) including an aerosol physics scheme (Feichter et al., 1996; Feichter et al., 2003) and the ocean circulation model HOPE-C (Maier-Reimer, xx). Inherent to the dynamics of intermedia mass exchange, intramedia (atmospheric) transports and the georeferenced entities (land/sea, soil, vegetation distributions) substance behaviour depends on time, location and mode of entry into the environment. The long-range transport potential of semi-volatile species is partly due to the “grasshopper effect”. Through repeated volatilization and reemission from land or ocean surface into the atmosphere and subsequent deposition such substances can travel long distances, longer than the atmospheric residence time suggests. Indicators for persistence and the long-range transport potential of substances can be derived from model results.
A first study applying our model system to the pesticides DDT and α-HCH shows that the effect of location of entry on the spatial scale of countries (400-4000 km) is significant for the compartmental distribution and the inter-compartmental mass exchange fluxes (e.g., number of atmospheric cycles, 'hops'). Location of entry introduces uncertainties in the order of a factor of 5 for the total environmental residence time. As shown in Figure 1 for the 2nd year upon entry into the environment, as turn-over time 317-1527 days are predicted for DDT and 101-463 days for α-HCH. The influence of location of entry does affect the substance ranking, i.e. we cannot simply state that DDT is more persistent than α-HCH, but for one scenario studied, application in China, the opposite is predicted. Integration of the location of entry in chemicals risk assessments is therefore recommended. However, the application for risk assessment demands a careful evaluation of the complex exchange transport processes parameterized in the model. Such an evaluation is hampered by a lack of sufficient observational data in the different compartments and by large uncertainties in the source strengths and distributions. Thus the model system has to be tested using tracers whose sources and sinks are better known.
62 4. RADIONUCLIDES AS TEST TRACERS
To examine the role of atmospheric and oceanic motions and deposition processes in the dispersal of chemical constituents, one performs model experiments using test tracers. Species used as test tracers should meet the following conditions: they should be chemically inert, sources and sinks should be well-known and sufficient observational data should be available for comparison with model results. Radionuclides, gases and particulates, are thus well-suited for evaluating specific aspects of model’s transport characteristics.
222Rn has been widely used as tracer for small scale vertical transport processes in the atmosphere (e.g. Jacob et al., 1997). Davidson and Trumbore (1995) and Ussler et al. (1994) estimate the rate of gaseous diffusion in soils and in forest canopies which affects the gas exchange with the atmosphere based on 222Rn flux measurements. Sato (2003) reports that 222Rn and 210Pb are also indicators for volcanic eruptions because significant amounts of 222Rn are released from erupting magma. Not only tracer distributions, but also the concentration ratios between different tracers should be compared to observations. For example the ratio between the radionuclides Be-7 and Be-10, both have the same source distribution in the stratosphere but very different radioactive life-times and both are removed by wet deposition, is an ideal indicator for stratospheric-tropospheric exchange. Because the life-time of 10Be in the stratosphere is much longer than for 7Be, stratospheric air is characterized by high values of Be-10/Be-7 (Land and Feichter, 2003). The ratio between tracers released near the surface and such released in the upper troposphere and stratosphere reflects the vertical exchange processes (e.g. Pb-210/Be-7).
Chemical tracers are also used to assess the simulated circulation in ocean models. Tracers that have been used in this context include tritium, chlorofluorocarbons, natural and bomb- produced radiocarbon (England and Maier-Reimer, 2001). The distribution of natural and artificial radionuclides within the sea tells us much about the ventilation of the upper ocean and about the formation of deep water. The first global survey of these distributions was made as part of the GEOSECS program (Broecker and Peng, 1982). 210Pb was used to assess transport and sedimentation in coastal water and for instance Tated et al. (2003) report a residence time of 2.1 and 0.4 years for dissolved and particulate matter, resp. Maier-Reimer and Henderson (1998) used 210Pb as tracer for the dispersion of particle-reactive elements in an ocean GCM since 210Pb attaches to biogenic particles and becomes buried in sediments. A further application of radiotracers is to estimate bioaccumulation by deriving the transfer of 137 Cs between seawater and marine species (Fievet and Plet, 2003).
5. CONCLUSIONS
This list of possible applications of radiotracers used to evaluate specific processes treated in ESMs is not exhaustive. However, our intention was to emphasize the great potential in particular of intermediate products of the 238U decay chain, like 222Rn and 210Lead, to be applied as test tracers to test a large variety of different physical processes in different compartments of the Earth-atmosphere system.
REFERENCES
Davidson, E. A. and S.E. Trumbore. 1995. Gas diffusivity and production of CO2 in deep soils of the Eastern Amazon, Tellus 47B, 550-565. England M.H. and E. Maier-Reimer. 2001. Using chemical tracers to assess ocean models, Rev. Geophs., 39, 29-70. Erickson, L. E.. “An Overview of Research on the Beneficial Effects of Vegetation in Contaminated Soil,” Annals of the New York Academy of Sciences, 829: 30-35, 1997. Feichter, J., E. Kjellström, H. Rodhe, F. Dentener, J. Lelieveld, and G. J. Roelofs. 1996. Simulation of the tropospheric sulfur cycle in a global climate model, Atmos Env, 30, 1693-1707.
63 Feichter, J., Atmospheric Chemistry and Aerosol Dynamics (2000). In: Numerical Modelling of the Global Atmosphere in the Climate System, eds. P.W. Mote and A. O'Neill, Kluver Academic Publishers, The Netherlands, pp 353-374. Feichter J., U. Lohmann, B. Liepert and E. Roeckner. 2003. Whitehouse Effect versus Greenhouse Effect: A Model Study, (in prep.) Fievet B, and D. Plet. 2003. J. Environ. Radioactive, 65, 1, 91-107. Jacob, D. J., M. J. Prather, P. J. Rasch, R.-L. Shia, et al. (1997). Intercomparison and evaluation of global atmospheric transport models using 222Rn and other short-lived tracers, J. Geophys. Res.,102D, 5953-5970. Land C. and J. Feichter. 2003. Stratosphere-troposphere exchange in a changing climate simulated with the general circulation model ECHAM4, J. Geophys. Res., 108, D12, 8523. Sato J. 2003. Natural radionuclides in volcanic activity, Appl. Radiation and Isotopes, 58, 3, 393-399. Tateda Y., F.P. Carvalho, S.W. Fowler and J.C. Miquel. 2003. Fractionation of Po-210 and Pb-210 in coastal waters of the NW Mediterranean continental margin, Cont. Shelf Res., 23, 3-4, 295-316. Ussler, W., III, J.P. Chanton, C.A. Kelley and C.S. Martens. 222Rn tracing of soil and forest canopy trace gas exchange in an open canopy boreal forest, J. Geophys. Res., 99, 1953-1963, 1994.
Figure 1: Indicators for the temporal dimension of multicompartmental fate of DDT and α-HCH, total nd environmental residence time, τoverall. Annual mean for the 2 year upon entry into the environment.
64 Simulation of the Cosmogenic Nuclide Production in the Earth Atmosphere
J. Masarik
ABSTRACT A pure physical model for the simulation of cosmic-ray particle interactions with the Earth’s atmosphere was used to investigate the production rates of cosmogenic nuclides. Analytical dependencies of the production rates 10Be and 36Cl among other radionuclides on geomagnetic modulation and solar modulation were developed. Using those relations, 10Be-, 36Cl measurements in the GRIP ice core were used to reconstruct the geomagnetic field intensity.
1. INTRODUCTION
The interactions of cosmic-ray particles with the Earth’s atmosphere leads to the production of a variety of cosmogenic nuclides. These cosmogenic nuclides have a wide range of applications in dating and tracing various events and processes in the environment. For most applications, it is extremely important to know the temporal variations of the nuclide production rates in the past.
Several distinct processes can cause changes in the production rates of cosmogenic nuclides in the Earth’s atmosphere. They include changes in the galactic cosmic-ray particle flux, changes in solar activity and variations in shielding by the Earth’s magnetic field. It is often impossible to separate the different contributions to the observed variability in production rates. Very little is known about the variation of the galactic cosmic-ray flux on time scales of a few thousand years. Changes in solar modulation are also poorly known, except those related to the 11-Schwabe cycle. Therefore, it is difficult to establish the extent to which those two processes affect the production rate. However, there is evidence that production rate variations are mainly caused by solar and geomagnetic modulation: Nuclide measurements from meteorites show that the galactic cosmic ray flux, averaged over millions of years is constant within 10%.
As both galactic and solar cosmic rays consist mainly of charged particles, a large fraction of them is deflected by the Earth’s magnetic field. Changes in the field intensity therefore control the fraction of the cosmic-ray particles that enter the Earth’s atmosphere, and consequently, the production rate of cosmogenic nuclides.
2. CALCULATIONAL MODEL
Our model for the simulation of the primary and secondary cosmic-ray particles is based on the GEANT [1] and MCNP [2] codes, which are systems of general-purpose Monte Carlo computer codes that treat the relevant physical processes of particle production and transport. In these codes, incident primary particles are transported through matter considering atomic interactions (ionization energy losses etc.) and nuclear interactions. In these nuclear interactions secondary particles are produced and subsequently transported with their interactions modeled. GEANT transports and models the interactions of all charged particles (protons, alpha particles, pions, muons, and electrons) and neutrons with energies greater than 15 MeV. Neutrons produced with energies less than 15 MeV in interactions modeled by GEANT are, by means of a special interface, written in a neutron file, which is subsequently used by MCNP as input file for further simulations of their interactions and transport to very low (subthermal) energies.
In our simulations only primary particles with energies between 10 MeV and 100 GeV were considered. The characteristic feature of the particle interactions at these energies is the production of secondary particles. Many of those particles have enough energy to initiate further inelastic interactions, which produce a next generation of secondary particles. In the atmosphere, this leads to the generation of a particle cascade.
65 For these calculations the Earth was considered as a sphere with a radius of 6378 km and a surface density of 2 g cm-2. The elemental composition of the surface was assumed to be the average terrestrial one. The Earth's atmosphere was modelled as a spherical shell with an inner radius of 6378 km and a thickness of 100 km. The following elemental composition (in weight %) was used: 75 % N, 23.2 % O, and 1.3 % Ar. The atmospheric shell was divided into 34 subshells to account for the change in the atmospheric density. The density structure of the atmosphere was in accordance with the US Standard Atmosphere model and its total thickness was 1033 g cm-2.
The production rate of a cosmogenic nuclide j at depth D in a model sphere with a radius R is ∞ P (D) = N σ (E )⋅ J (E ,D) ⋅ dE (1) j ∑ i ∑∫ ijk k k k k i k 0 where Ni is the number of atoms for target element i per kg material in the sample, σijk(Ek) is the cross section for the production of the cosmogenic nuclide j from the target element i by particles of type k with energy Ek, and Jk(Ek,D) is the flux of particles of type k with energy Ek at depth D inside the Earth's atmosphere. The particle fluxes Jk(Ek,D) were calculated by the GEANT / MCNP code system. The statistical errors of the calculations were on the level of 4 - 6 %. The systematic uncertainties of our calculated fluxes are estimated to be in the range of 10 -15 % and increase in the atmosphere with depth. For the cross sections σijk we relied on the ones evaluated by us and tested by earlier calculations
The primary cosmic-ray particle flux at the Earth's orbit consists of a galactic and a solar component. In this paper, we present only results that are based on the interactions galactic cosmic rays. As solar cosmic-ray particles have low energies, they induce interactions only in the few uppermost g cm-2 of the Earth's atmosphere and only at high latitude, where the geomagnetic field does not prevent them from entering the atmosphere. Therefore their contribution to the total average cosmogenic nuclide production is smaller than 3% [15]. The galactic cosmic-ray particles are a mixture of protons (~87 %), alpha particles (~12 %), and heavier nuclei (~1 %). More details about model can be found in [3].
3. RESULTS AND CONCLUSIONS
At first differential particle fluxes in the atmosphere as the function of altitude and latitude were calculated. The depth bin for calculations was 30 g cm-2 and the latitudinal bin was 10 degrees. The example of calculated neutron and proton fluxes fluxes is given in Figure 1. Neutrons are the most important particles for the production of nuclides in the atmosphere. They make around 90 % of total production. The principal feature of the depth-dependent total neutron flux is the maximum in the altitude range corresponding to a depth 75 -125 g cm-2 At depths in the atmosphere exceeding 150 g cm-2. the total flux shows exponential dependence with e-folding length 150 - 1760 g cm-2 (going from pole to equator). The shape of the neutron spectrum changes very slowly with the depth and latitude influence on the primary cosmic ray spectrum is reflected mainly in total neutron fluxes.
Solar Activity is one of the most pronounced factors influencing the primary cosmic-ray spectrum and flux in the vicinity of the Earth. Although the modulation process is not yet understood in detail, the experimental data show that there is an anticorelation between the level of solar activity and the intensity of GCR. In our calculations we used spectrum of GCR particles [8] accounting for the influence of solar activity, with a modulation parameter φ. The parameter φ was varied from 0, which corresponds to the absence of solar modulation, to 1000 MeV, which corresponds to strongest modulation observed. The effect of solar modulation is shown in Figure 2. Due to the approximately dipole shape of geomagnetic field, the modulation effect is strongest for high latitudes
66 P(10BE, φ=0 MeV)/ P(10BE, φ=1000 MeV) = 2.51 and weaker for equatorial region, for which the equivalent ratio is ∼1.07. For the globally averaged 10Be production rate this ratio is 1.73.
REFERENCES
[1] B. Brun, et al., GEANT3 User's guide, Rep. DD/EE/84-1, 584 pp., 1987. [2] J. F. Briesmeister, MCNP - A general Monte Carlo N-particle transport code version 4A, LA-12625-M, 693 pp., LANL, Los Alamos, 1993. [3] J. Masarik and J. Beer, “Simulation of Particle Fluxes and Cosmogenic Nuclides Production in The Earth's Atmosphere," J. Geophys. Res.104, 12 099-12 112 (1999)
1 n(30) n(150) a) 0.01 n(420) n(990) p(30) p(150) -4 10
-6 p(450) 10
-8 p(990) 10
-10 10
-12 10
-14 10 1 10 100 1000 104 105 106 Energy [MeV]
Figure 1: Differential neutron and proton fluxes in the Earths atmosphere for various depth in the atmosphere and high latitudes.
0.08 10 b) 0.07 80-90 Be 0.06 0.05 0.04
0.03 0.02 0.01 0-10 0 0 200 400 600 800 1000 Modulation Parameter Φ [MeV]
Figure 2: Dependence of 10Be production rate on latitude and solar modulation parameter for current geomagnetic field intensity.
67 Measurements of Cosmic-Ray Neutron Spectra in the Stratosphere: a Benchmark for Calculations of Cosmogenic Nuclide Production
Paul Goldhagen and John M. Clem
1. INTRODUCTION
Radionuclides such as 3H, 7Be, 10Be, 14C, and 36Cl are produced when Cosmic rays collide with atomic nuclei in the atmosphere. These cosmogenic radionuclides and their production rates are important in a variety of fields. Some of these nuclides, particularly 7Be (half-life = 53.12 d), may be useful as tracers of atmospheric mixing if their production rate is known as a function of location and time. When galactic cosmic rays penetrate the magnetic fields of the solar system and the Earth and reach the Earth’s atmosphere, they collide with atomic nuclei in air and create cascades of secondary radiation of every kind. The secondary neutrons cause the overwhelming majority of cosmogenic nuclide production (Masarik and Beer, 1999). The production rate of cosmogenic nuclides at a location in the atmosphere depends on the fluence rate and energy distribution of the secondary cosmic-ray neutrons (and of less importance, protons) at that location. Calculations of cosmogenic nuclide production rates (see Masarik and Beer (1999) and references therein) include calculated secondary neutron and proton spectra in the atmosphere. This paper presents measurements of cosmic-ray neutrons spectra in the stratosphere that can be used to verify such calculated spectra.
The intensity and energy distribution of the neutrons and other particles making up atmospheric cosmic radiation vary with altitude, location in the geomagnetic field, and time in the sun's magnetic activity cycle (Reitz, 1993; Heinrich et al., 1999; Masarik and Beer, 1999; Wilson, 2000). Atmospheric shielding at a given altitude is determined by the mass thickness of the air above, called atmospheric depth. The geomagnetic field deflects low-momentum charged particles back into space. The minimum momentum per unit charge (magnetic rigidity) an incident (often, vertically incident) particle can have and still reach a given location above the Earth is called the geomagnetic cutoff rigidity (cutoff) for that location.
Our measurements were performed primarily to improve radiation dosimetry for air crews. Cosmic-radiation dose rates at commercial aviation altitudes are such that crews working on present-day jet aircraft are an occupationally exposed group with a relatively high average effective dose (O’Brien et al., 1992; Goldhagen, 2000; Wilson, 2000). Crews of future high-speed commercial aircraft flying at higher altitudes would be even more exposed (Wilson, et al., 1995; Wilson, 2000). To help determine such exposures, the Atmospheric Ionizing Radiation (AIR) Project, an international collaboration of 15 laboratories organized by the NASA Langley Research Centre, made simultaneous radiation measurements with 14 instruments on a NASA ER-2 high- altitude aircraft (Goldhagen, 2000). This paper discusses only the neutron spectrometry. At aviation altitudes, the neutron component contributes about half of the dose equivalent, but until recently it had been difficult to accurately determine the cosmic-ray neutron spectrum in the atmosphere (Goldhagen, 2000).
The AIR ER-2 flights took place in June 1997, a time of maximum galactic cosmic radiation (solar minimum). There were five measurement flights, which all took off from and landed at the NASA Ames Research Centre (37.4°N, 122°W) in California. Flight paths and altitude profiles may be found in Goldhagen (2000) and Goldhagen et al. (2002). Overall, the flights covered latitudes from 18°N to 60°N, corresponding to vertical cutoffs from 11.8 GV to 0.4 GV, and altitudes from 16 to 21.3 km (atmospheric depths from 110 to 50 g cm-2), not including initial climb and final descent, which yield some data at lower altitudes for one latitude. (Vertical cutoff rigidities given in this paper for the measurement locations and times were calculated by Clem et al. (2003)). Neutron spectrometry data from four ER-2 locations, representing extremes of latitude and altitude, and one
68 location on the ground at sea level have been analyzed with increasingly accurate methods (Goldhagen et al., 2002; 2003; 2004).
2. THE HIGH-ENERGY MULTISPHERE NEUTRON SPECTROMETER
The primary AIR instrument was a highly sensitive extended-energy multisphere (Bonner sphere) neutron spectrometer (MNS) designed specifically for cosmic-ray measurements. A MNS (Thomas and Alevra, 2002) is a set of moderator spheres, usually polyethylene, surrounding detectors which have high efficiency for detecting thermal-energy neutrons. The larger the moderator, the higher the energy of incident neutrons for which the detector assembly has good detection efficiency. If all the detectors are exposed to the same radiation field and the efficiency as a function of energy (response function) of each of the detectors is known, the neutron energy spectrum can be determined from the detector count rates. The 14 detectors of our MNS are spherical 5.08 cm-diameter 3He-filled proportional counters, with one unshielded, one surrounded with a layer of cadmium, and the rest surrounded with high-density polyethylene spheres with diameters ranging from 6.7 to 38 cm. Moderator diameters and masses for all the detectors are given in Goldhagen et al. (2002).
Even very large Bonner spheres with standard all-plastic moderators have responses that drop to low values as the energy increases above about 30 MeV, so standard MNSs cannot be used to measure neutron spectra at energies much above that energy. To overcome this problem, we added two detectors incorporating heavy metal shells within their polyethylene moderators. One has a 25-kg lead shell; the other, an 18-kg steel shell. High-energy neutrons (and protons and other strongly interacting particles) striking the nuclei of atoms with high atomic numbers cause hadronic particle showers that include easily detected secondary neutrons, creating a rising response with increasing energy and allowing the modified MNS to measure the neutron spectrum to beyond 10 GeV.
Detector responses as a function of energy were calculated for neutrons at energies from 10-10 MeV up to 100 GeV using the Monte Carlo radiation transport code MCNPX (Waters, 2002), recently, version 2.5.d. The effects of the various materials surrounding each detector were included in the response calculations by modelling entire apparatus assemblies (Goldhagen et al., 2002). For analysis of the airborne measurements, we also calculated the effects of the airplane structure on the response functions (Goldhagen et al., 2003; 2004).
The signal processing and data acquisition electronics and methods are described in Goldhagen et al. (2002). Pulse-height spectra and live time for each proportional counter were recorded every 60 s. During analysis, neutron capture pulses were cleanly separated from electronic noise and pulses from minimum ionizing particles by pulse height. In-flight cosmic-ray neutron count rates in the detectors averaged about 4 to 32 per s, allowing statistically sound spectra to be collected in a few minutes.
Once the neutron count rates and response functions of the MNS detectors are known, a deconvolution (unfolding) computer code is applied to determine the neutron spectrum. The deconvolution process is not straightforward because information in addition to the measurement and the response functions must be applied to obtain a unique solution. We use the unfolding code MAXED (Reginatto and Goldhagen, 1998; 1999), now in version 3.1. The required a priori information is in the form of an initial (default) spectrum that represents knowledge about the spectrum before the measurement is made. Since MAXED applies no smoothing, it preserves any structure in the default spectrum that is finer than the resolution of the spectrometer. We have shown that, except for fine structure, using any of four different calculated cosmic-ray neutron spectra for the default spectrum gives essentially the same unfolded measured spectrum (Goldhagen et al., 2002; 2004). The default spectra used to unfold the measured spectra shown below came from recent calculations that were made for the locations and times of the AIR measurements we are analyzing (Clem et al. 2003; 2004; Roesler et al., 2002).
69 3. MEASURED COSMIC-RAY NEUTRON SPECTRA
Figure 1 shows our measured cosmic-ray neutron spectrum at high altitude and high northern latitude (20 km altitude, 56 g cm-2 atmospheric depth; 54°N, 117°W, 0.8 GV vertical cutoff) and a neutron spectrum calculated by Clem et al. (2003; 2004) for the same location. Neutron fluence rate (neutrons cm-2 s-1) per lethargy (the natural logarithm of energy) is plotted on the vertical axis versus neutron energy in MeV with a logarithmic scale on the horizontal axis. Fluence rate per lethargy is equivalent to E (dΦ/dE), where E is particle energy and Φ is fluence rate. The spectra have very few thermal-energy neutrons, a large “evaporation” peak centred at 1 or 2 MeV, and a smaller peak at about 100 MeV with a tail which extends up to about 10 GeV. The Clem calculated spectrum, which shows fine structure from nuclear resonances in the nitrogen and oxygen of the atmosphere, was used as the default spectrum for the unfolding. The measured and calculated spectra agree quite well, though the measured spectrum is higher at energies below 10 MeV and lower above 10 MeV. Comparisons of our measured spectra at four ER-2 locations with the calculations of Clem et al. (2004) are shown in that paper, and agreement is very good in all cases. Agreement is nearly as good with the calculations of Roesler et al. (2002).
Figure 2 shows the same measured spectrum shown in Figure 1 together with a spectrum measured near the southernmost location reached by the ER-2 (18.7°N, 127°W, 11.6 GV cutoff) at almost the same altitude (20.3 km, 53.5 g cm-2). The total neutron fluence rate at the northern location was 7.8 times the fluence rate at the southern location; the southern spectrum is shown multiplied by 7.8. The spectra have almost the same shape up to 1 GeV, but at high cutoff there is a significantly larger fraction of neutrons above 1 GeV.
Figure 3 shows cosmic-ray neutron spectra measured at three different altitudes on the ER-2 and on the ground at sea level. The shapes of the spectra at the three ER-2 altitudes are almost identical to each other. At 16.2 km, the atmospheric depth (101 g cm-2) is 1.8 times greater than at 20 km, but the total neutron fluence rate decreased only 2%. At 11.9 km (201 g cm-2) (and at a higher cutoff) the neutron fluence rate decreased by a factor of 2.9, but the shape of the spectrum did not change. The cosmic-ray neutron spectrum measured on the ground shows a distinctly different shape, because the ground (actually concrete) reflects neutrons differently than air does. As expected, a significant number of thermal neutrons was produced. Normalized to the same total fluence rate as the in-flight measurements, the ground spectrum is lower from 10-6 to 2 MeV and higher at higher energies. A spectrum calculated by Roesler et al. (2002) for this location showed a similar shape, but twice the fluence rate.
The MNS also responds to protons, pions, and nuclear ions, which produce neutrons by nuclear interactions with the metals and carbon in the detectors and their surroundings. The measured neutron spectra have been corrected for MNS counts caused by these strongly interacting charged particles. This requires calculating response functions for these particles and knowing their approximate cosmic-ray spectra. Response functions for protons, pions, and nuclear ions from deuterons to 4He ions were calculated from 10 MeV to 100 GeV using MCNPX with methods similar to those used for neutrons (Goldhagen et al., 2004). Cosmic-ray charged hadron and ion spectra were taken from the same calculations of Clem et al. (2003; 2004) used to provide the default neutron spectrum for unfolding. Figure 4 shows the measured neutron spectrum at 20 km altitude and 0.8 GV cutoff with and without the correction for charged particles. The calculated proton spectrum used for the correction and the combined spectrum of nucleons in all the light ions are also shown. Correction for pions was found to be negligible: ≤ 1% of the high-energy neutron fluence rate. The uncorrected neutron spectrum has a total fluence rate that is 13% too high and a fluence rate above 10 MeV that is more than 50% too high. The uncorrected neutron spectrum would significantly over-predict the production rate of cosmogenic nuclides such as 7Be.
The AIR MNS measurements have so far been analyzed at five locations representing extremes of latitude and altitude. The locations, atmospheric depths, and altitudes of the measurements are given in Table 1, together with the measured total cosmic-ray neutron fluence rate and the fluence rate for neutrons with E > 10 MeV. The results for the airplane measurements are obtained from measured spectra unfolded using the Clem calculated neutron spectra as default
70 spectra and their associated proton, pion, and ion spectra for corrections. The measurement on the ground was unfolded using a default spectrum from a calculation by Roesler et al. (2002).
Table 1: Cosmic-Ray Neutron Fluence Rates Measured at Various Locations.
Atmospheric Altitude Neutron E > 10 MeV E > 10 Geographic Cutoff Depth ______Fluence Rate Fluence Rate MeV Location (GV) (g cm−2) (km) (ft) (cm−2 s−1) (cm−2 s−1) Fraction
19°N, 127°W 11.6 53.5 20.3 66,500 1.24 0.31 0.25 54°N, 117°W 0.8 56 20.0 65,600 9.7 2.3 0.23 56°N, 121°W 0.7 101 16.2 53,300 9.5 2.2 0.23 38°N, 122°W 4.3 201 11.9 39,000 3.4 0.78 0.23 37°N, 76°W 2.7 1030 0 0 0.0126 0.0039 0.31
4. SUMMARY AND CONCLUSIONS
We summarize our results at the five locations analyzed so far as follows. At high altitude, geomagnetic latitude has a small but measurable effect on the shape of the spectrum and a very large effect on neutron fluence rate, which was 7.8 times higher at 0.8 GV cutoff than at 11.6 GV. The shape of the cosmic-ray neutron spectrum changes very slightly with altitude from 20 km down to 12 km (56 - 201 g cm-2 atmospheric depth), but is quite different on the ground. Measurements on the ER-2 agree with the calculations of Clem et al. (2003; 2004) and Roesler et al. (2002) within estimated systematic errors, but are a factor of two lower than calculations on the ground at sea level. The high-altitude neutron measurements are not entirely independent of cosmic ray transport calculations, because calculated cosmic-ray spectra for protons and nuclear ions are needed to make corrections for the response of the neutron spectrometer to these particles.
Only a small sample of the AIR MNS data has yet been analyzed. With further analysis, we will have a database of cosmic-ray neutron spectra at solar minimum for a wide range of latitudes at high altitude, one latitude at commercial aviation altitudes, and for several times, latitudes, and altitudes on the ground. The results can be used to verify and improve cosmic-ray transport calculations used to determine air crew doses and radiation effects on microelectronics, as well as source terms for cosmogenic nuclides.
5. ACKNOWLEDGEMENT
Analysis of the AIR neutron measurements is supported by NASA through the Living with a Star program of the Office of Space Science.
71 REFERENCES
Clem, J., G. De Angelis, P. Goldhagen, J.W. Wilson. Validation of computational procedures for a new atmospheric ionizing radiation (AIR) model, Adv. Space Res. 32, 27-33 (2003). Clem, J., G. De Angelis, P. Goldhagen, J.W. Wilson. New calculations of the atmospheric cosmic radiation field – results for neutron spectra, Radiat. Prot. Dosim., submitted for Proc. Ninth Neutron Dosimetry Symposium. (2004). Goldhagen, P. Overview of aircraft radiation exposure and recent ER-2 measurements, Health Phys.79, 526- 544 (2000). Goldhagen, P., M. Reginatto, T. Kniss, et al. Measurement of the energy spectrum of cosmic-ray induced neutrons aboard an ER-2 high-altitude airplane, Nucl. Inst.& Meth. A 476, 42-51. (2002). Goldhagen, P., J. Clem, and J.W. Wilson. Recent results from measurements of the energy spectrum of cosmic-ray induced neutrons aboard an ER-2 airplane and on the ground, Adv. Space Res. 32, 35-40 (2003). Goldhagen, P., J. Clem, and J.W. Wilson. The energy spectrum of cosmic-ray induced neutrons measured on an airplane over a wide range of altitude and latitude, Radiat. Prot. Dosim., submitted for Proc. Ninth Neutron Dosimetry Symposium (2004). Heinrich, W., S. Roesler, and H. Schraube. Physics of Cosmic Radiation Fields, Radiat. Prot. Dosim. 86, 253-258 (1999). Masarik, J. and J. Beer. Simulation of particle fluxes and cosmogenic nuclide production in the Earth's atmosphere, J. Geophys. Res., D104, 12099-13012 (1999). O’Brien, K., W. Friedberg, F.E. Duke, L. Snyder, E.B. Darden, H.H. Sauer. The exposure of aircraft crews to radiations of extraterrestrial origin, Radiat. Prot. Dosim. 45, 145-162 (1992). Reginatto, M., and P. Goldhagen. MAXED, a Computer Code for the Deconvolution of Multisphere Neutron Spectrometer Data Using the Maximum Entropy Method, Technical Report EML-595, U.S. Dept. of Energy Environmental Measurements Laboratory, New York, http://www.eml.doe.gov/publications/ reports/ (1998). Reginatto, M., and P. Goldhagen. MAXED, a computer code for maximum entropy deconvolution of multisphere neutron spectrometer data, Health Phys. 77, 579-583 (1999). Reitz, G. Radiation environment in the stratosphere, Radiat. Prot. Dosim. 48, 5-20 (1993). Roesler, S., W. Heinrich, and H. Schraube. Monte Carlo calculation of the radiation field at aircraft altitudes, Radiat. Prot. Dosim. 98, 367-388 (2002). Thomas, D.J. and A.V. Alevra. Bonner sphere spectrometers - a critical review, Nucl. Instr. and Meth. A 476, 12-20 (2002). Waters, L.S., (ed.). MCNPX User’s Manual, Version 2.3.0, Report LA-UR 02-2607, Los Alamos National Laboratory, Los Alamos, NM, USA (2002). Wilson, J. W. Overview of radiation environments and human exposures, Health Phys. 79, 470-494 (2000). Wilson, J. W., J. E. Nealy, F. A. Cucinotta, et al. Radiation Safety Aspects of Commercial High-Speed Flight Transportation, NASA TP-3524, National Technical Information Service, Springfield, VA (1995).
72
Measured )
-1 1.0 Calculated sec -2
0.5 /dE (cm /dE φ E d
0.0 10-8 10-6 10-4 10-2 100 102 104 Neutron Energy (MeV)
Figure 1: Measured cosmic-ray neutron spectrum at high altitude (20 km, 56 g cm-2) and latitude (54°N, 117°W, 0.8 GV cutoff) and a spectrum calculated by Clem et al. (2003) for the same location.
North, 0.8 GV cutoff ) -1 1.0 South, 11.6 GV cutoff x 7.8 sec -2
0.5 /dE (cm /dE φ E d
0.0 10-8 10-6 10-4 10-2 100 102 104 Neutron Energy (MeV)
Figure 2: Cosmic-ray neutron spectra measured at the same northern location as in Figure 1 and at a southern location (19°N, 127°W, 11.6 GV cutoff; 54 g cm−2) at about the same altitude. The south spectrum is shown multiplied by 7.8.
73 20 km )
-1 1.0 16 km 12 km sec
-2 x 2.9
0 km x 770 0.5 /dE (cm φ d
E
0.0 10-8 10-6 10-4 10-2 100 102 104 Neutron Energy (MeV)
Figure 3: Cosmic-ray neutron spectra measured at different altitudes on the ER-2 and on the ground at sea level. The 12 km spectrum is shown multiplied by 2.9 and the sea level spectrum by 770.
Corrected for
) protons, ions, pions -1 1.0 Not corrected sec -2 Protons Nucleons in ions
/dE (cm 0.5 φ E d
0.0 10-8 10-6 10-4 10-2 100 102 104 Energy Per Nucleon (MeV)
Figure. 4: Measured cosmic-ray neutron spectra with and without the correction for counts caused by protons, nuclear ions up to 4He, and pions. Calculated spectra (Clem et al., 2003; 2004) for protons and for nucleons in the nuclear ions are also shown.
74 7Beryllium and 222Rn as the Atmospheric Tracer - Observation at the Summit of Mt. Fuji Located in the Free Troposphere
Yasuhito Igarashi
1. INTRODUCTION
Mt. Fuji (35.4°N, 138.7°E; 3,776 m a.s.l.) is a symbolic mountain in Japan. Its summit is positioned in the free troposphere in the most of the time in a year, serving an adequate platform for the observation of atmospheric chemistry. Because the mountain has a nice conide profile, the summit seems to be relatively free from the mountain and valley winds. The long-range transport of the pollutants from the Asian continent attributable to the westerly in the free troposphere can be captured at the summit. From the viewpoint, Dokiya at Meteorological College started their study of precipitation chemistry at Mt. Fuji in 1990 and repeated short-term campaign observation of gas, aerosol, precipitation for major ionic species, etc. in summer [Dokiya et al., 1995; 2001; Sekino et al., 1997]. Tsutsumi et al. [1994] and his collaborator at Meteorological Research Institute (MRI) have continued the observation of ambient O3 at the summit since 1992 in order to investigate the background O3 feature in the middle troposphere. They have found smaller diurnal O3 concentration change at the summit of Mt. Fuji than that at Mauna Loa confirming that the summit of Mt. Fuji is less affected by the boundary layer air than Mauna Loa. The Japan Meteorological Agency (JMA) has so far maintained a weather station at the summit, electricity, some space, etc. are available for the observation.
Observations on atmospheric naturally occurring radionuclides, which have definite sources, along with other chemical species could provide useful information on emission, transport and removal processes, etc. For the purpose, 7Be and 222Rn seem most useful to know about the free tropospheric processes. Since 1994 we have organized and joined campaign observations and measured 7Be along with other species [Tsutsumi et al.,1998]. The 222Rn monitor was newly installed at the summit of Mt. Fuji in September 2002 and time series of 222Rn have been obtained since then.
In this work, the interrelationship between the species observed at the summit of Mt. Fuji is described, referring 7Be as a tracer for the upper air and 222Rn as a tracer for the boundary layer air and trying to give noble insights on the atmospheric chemistry.
2. EXPERIMENTAL
As of the spring in 2003, there are monitoring of at least 9 chemical species including 7Be and 222Rn at the summit of Mt. Fuji, as listed in Table 1. Other species than 7Be are automatically monitored by use of PC controlled instruments. Manual sample change is required only for high volume sampling (700-1,000 L/min) for 7Be. Aerosols are collected onto a quartz fiber filter and analyzed for 7Be by γ-spectrometry by using Ge detector after send the sample back to the laboratory. At the campaign observation high time resolution of 4 h is applied, while at routine observation time resolution of one day to a week is applied. The campaign observation samples were in particular measured at the Ogoya Underground Laboratory under extremely low background condition (Komura, 1997; 2000; Igarashi et al., 1999), where the DL level of a few mBq of 7Be is achieved. A continuous Rn monitor developed by Iida et al. (1996) is used in the work. This monitor employs the electrostatic collection of Rn progeny (218Po) produced in the decay chamber followed by α-spectrometry using a Si detector, which is capable of supplying 1 h averaged data for 222Rn in air. The 222Rn monitor is calibrated by using 222Rn emanated from 226Ra solution at Nagoya University (Iida et al., 1996).
75 3. RESULTS AND DISCUSSION
3.1 Beryllium-7 application
7 Figure 1 depicts the temporal change of Be, O3 and specific humidity at the summit of Mt. Fuji during the 1998 campaign observation. The range of 7Be concentration was fairly large in the period. Beryllium-7 concentration well correlated with O3 concentration and anti-correlated with specific humidity. During July 17 to 19 one hour sampling was occasionally applied, the correlation 7 7 between Be and O3 was better. The high Be, high O3 and low specific humidity incident reflects the transport of the upper air mass after the intrusion of the stratospheric air to the troposphere associated with a corresponding low at the surface. The spatial scale of the intrusion was also well pictured in satellite image of water vapour (Figure 2). Dark region in the image corresponds to the dry air mass descending from the upper atmosphere.
7 Correlation plot for Be and O3 is given in Figure 3 for the campaign observations conducted in 1994, 1997 and 1998. In 1997 case, the Japanese islands were covered by the 7 Pacific high, both Be and O3 concentrations were low. While for campaigns for 1994 and 1998, 7 both species showed higher value and beyond about 50 ppb of O3 concentrations, Be and O3 had a good linear correlation. The intercept of O3 concentration probably indicate the photochemical component of O3 produced in the troposphere and for the higher concentration range O3 was transported from the upper atmosphere (the lowermost stratosphere and the uppermost 7 troposphere). The relationship between Be and O3 observed is expressed as follow switching x 7 axis from O3 to Be,
7 [O3]obs = [O3]photochem + Kst × [ Be]obs
where Kst is the slope of the correlation curve (Bazhanov and Rodhe, 1997). The slope 7 would primarily indicate the concentration ratio of O3 and Be in the lowermost stratosphere, 7 -3 [O3]st/[ Be] st, which was 1.5 ppb /(mBq m ) in the 1998 case. By using this relationship and assuming that tropospherically produced 7Be is negligibly small compared to the stratospheric 7 7 7 7 component ([ Be]obs = [ Be]trp+[ Be]st ≈ [ Be]st), temporal change of the photochemical component of O3 during the observation can be estimated. In Figure 4 the result of the estimation is shown. The photochemical component of O3 was fairly constant during the 1998 campaign observation. Conversely, stratospheric component of O3 changed dynamically along with the air mass descent from the stratosphere.
It seems possible to use the Kst for the estimation of flux of O3 from the stratosphere into the troposphere. As a first order approximation (a rough estimate), we can assume influx of 7Be from the stratosphere is equal to the deposition on the surface, ignoring 7Be produced in the troposphere. Annual deposition of 7Be in Tsukuba, Japan has been around 1000 Bq/m2, therefore, the O3 influx from the stratosphere would be,
7 11 -2 -1 [O3 influx] = Kst × ( Be annual deposition) ÷ year ≈ 1.3 × 10 molecule cm sec .
This rough estimate unexpectedly match with the classical estimate of O3 surface flux for the mid-latitude band in the Northern Hemisphere by Fabian and Pruchniewicz (1977), which seems intriguing. We need to, of course, take the tropospheric 7Be into the account. The partition of the production of 7Be is considered to be 70% in the stratosphere and the rest in the troposphere (Lal, 1963). By multiplying this rate for the above-mentioned estimate, the influx of O3 11 -2 -1 7 from the stratosphere would be 0.9×10 molecule cm sec . The correlation between Be and O3 7 observed would vary depending on time and place, since the Be and O3 have some different latitudinal concentration gradient in the stratosphere, thus the estimate would vary as well.
Seasonal trend of 7Be concentration at the summit of Mt. Fuji is depicted in Figure 5. Until March 2002 the sampling was weekly basis, afterwards daily sampling was carried out. It appears that 7Be concentration may have double maxima of spring and fall and minimum in summer, though the October and November samples are still under the measurement. This feature will be
76 common for the observations of O3 at the summit (Tsutsumi et al., 1994). Also, the seasonal trends will be common at the surface observation of 7Be in Japan. For instance, Abe et al. (1993) and Megumi et al. (2000) have reported that 7Be concentration exhibit the double concentration maxima in spring and fall with summer minimum. The finding by our Mt. Fuji observations may imply the influence of the lowermost stratospheric air upon the boundary layer air through the transport and mixing processes linked to synoptic scale meteorology around the Japanese islands.
3.2 222Rn application
Figure 6 shows the temporal change of 222Rn along with CO (Tsutsumi and Matsueda, 2000) and SO2 data at the summit of Mt. Fuji during December 2002. Carbon monoxide and SO2 data are 1 h average and 1 h median, respectively. They did not show typical diurnal change suggesting the small direct influence of local boundary layer air. Rather than the diurnal change, they exhibited the sporadic features due probably to the synoptic scale meteorology. In general, 222Rn and CO correlated well with each other, suggesting both coming from the boundary layer. The ratio of 222Rn and CO seems different in seasons (not shown here) reflecting the source difference. Sulfur dioxide also displays the similar temporal trend, which was not anticipated. Since SO2 is rather reactive and soon to be converted to sulfate. It seems that SO2 found at the summit 222 of Mt. Fuji arose from the same boundary layer air with Rn and CO and that SO2 might have similar life as long as 222Rn in the free troposphere (Warneck, 2000). Further meteorological analysis such as back-trajectory and so forth will clarify more for these data.
Acknowledgement
Ozone and CO data were provided by one of the author’s colleagues, Yosuke Sawa, Geochemical Research Department, Meteorological Research Institute. 222Rn data were provided by Katsuhiro Yoshioka, Shimane Prefectural Institute of Public Health and Environmental Science. Professor Kazuhisa Komura offered his expertise in measuring 7Be at the Ogoya Underground Laboratory, LLRL, Kanazawa University. Professor Yukiko Dokiya currently at Edogawa University, who was a former team leader, noticed the importance of radionuclide observation at the summit of Mt. Fuji, without which the authors could never start the present study at Mt. Fuji. The staff at the Mt. Fuji Weather Station have helped us a lot, to which the author’s thanks are due.
REFERENCES
Abe M., Kurotaki K., Shibata S., Takesita H. and S. Abe. IAEA-SM-329/8, 1993, pp.35-42, International Atomic Energy Agency, Vienna. Bazhanov, V. and H. Rodhe. 1997. J. Atmos. Chem., 28, 61-76. Dokiya, Y., K. Tsuboi, H. Sekino, T. Hosomi, Y. Igarashi, and S. Tanaka. 1995. Water Air Soil Pollut., 85, 1967-1972. Dokiya, Y., T. Yoshikawa, T. Komada, I. Suzuki, A. Naemura, K. Hayashi, H. Naoe, Y. Sawa, T. Sekiyama Y. Igarashi. 2001. Anal. Sci., 17 Suppl. i809-i812. Igarashi, Y., M. Aoyama, T. Miyao, K. Hirose, K. Komura and M. Yamamoto. 1999. Appl. Radiat. Isot., 50, 1063-1073. Iida T., Y. Ikebe, K. Suzuki, K. Ueno, Z. Wang and Y. Jin. 1996. Environ. International, 22 Suppl. 1, S139- S147. Komura, K., 1997, Proceedings of 1997 International Symposium on Environmental Symposium, Oct. 20. 1997. Tsuruga, Fukui, Japan. Komura, K. 2000. Proceedings from the International Conference on Radioactivity in the Environment, Sept. 1-5, 2002, Monaco. Lal D., 1963. On the investigations of geophysical processes using cosmic ray produced radioactivity, Earth Science and Meteoritics, pp. 115-142. North-Holland publishing company, Amsterdam. Megumi, K., T. Matsunami, N. Ito, S. Kiyoda, A. Mizohata and T. Asano. 2000. Geophys. Res. Lett., 27, 361- 364.
77 Sekino, H., C. Nara, K. Tsuboi, T. Hosomi, Y. Dokiya, Y. Igarashi, Y. Tsutsumi and S. Tanaka, 1997, J. Aerosol Res., Jpn, 12, 311-319. Tsutsumi, Y. and H. Matsueda, 2000, Atmos. Environ, 34, 553-561. Tsutsumi, Y., Y. Zaizen and Y. Makino. 1994. Geophys. Res. Lett., 21, 1727-1730. Tsutsumi, Y.,Y. Igarashi, Y. Zaizen, Y. Makino. 1998. J. Geophys. Res., D103, 16935-16951. Warneck, P., 2000. Chemistry of the Natural Atmosphere 2nd Ed., Academic Press, USA.
40 120 7Be O Spc. humidity x2 3 1998 35 Data lack
) 100 3 12h average 30 80 25
20 60
15 40 concentration(ppb) 3
10 O Be concentration Be concentration (mBq/m 7
Specific humidity (x2; g/kg air) g/kg (x2; humidity Specific 20 5
0 0 7/10 7/11 7/12 7/13 7/14 7/15 7/16 7/17 7/18 7/19 7/20 7/21 7/22 7/23 Date
7 Figure 1: Temporal variations of Be, O3 and specific humidity in air at the summit of Mt. Fuji during 1998 summer campaign observation.
Mt.Fuji
Meander of the jet = upper trough
Figure 2: Satellite water vapour image on July 14, 1998.
78
40
7
) 35 3 Be in 1998 7 30 Be in 1997 7Be in 1994 25
20 15
10
Be concentration (mBq/m concentration Be 7 5
0 0 20 40 60 80 100 120 O concentration (ppbv) 3
7 Figure 3: Scatter plot for Be and O3 during summer campaigns.
Spec. humidity x2 O observed 3 7 40 Be Estimated photochem. O 120 Data lack 3 35 12 h average 100 ) 3 30
80 25
20 60
(ppbv) 3
15 O 40 10 Be concentation (mBq/m concentation Be 7 20 humidity (x2; g/kg air) Specific 5
0 0 7/10 7/11 7/12 7/13 7/14 7/15 7/16 7/17 7/18 7/19 7/20 7/21 7/22 7/23 Date Figure 4: Temporal variation of the estimated photochemical O3 during 1998 summer campaign observation.
20 Weekly basis Daily basis 7 Be concentration 2002 ) 3 15
10
Under the 5 measurement Be concentration (mBq/m Be concentration 7
0 2002/Jan 2002/Mar 2002/May 2002/Jul 2002/Sept 2002/Nov
Month Figure 5: Temporal variation of 7Be concentration at the summit of Mt. Fuji in 2002.
79
3.5 600
Radon SO2 CO 3 500 2.5 Radon
400 CO 2
S O 2 (p p b ) 1.5 300 SO2
C O(ppb) 1 200
(BqmRadon -3), 0.5
100 0
-0.5 12/1/2002 12/2/2002 12/3/2002 12/4/2002 12/5/2002 12/6/2002 12/7/2002 12/8/2002 12/9/2002 0 12/10/2002 12/11/2002 12/12/2002 12/13/2002 12/14/2002 12/15/2002 12/16/2002 12/17/2002 12/18/2002 12/19/2002 12/20/2002 12/21/2002 12/22/2002 12/23/2002 12/24/2002 12/25/2002 12/26/2002 12/27/2002 12/28/2002 12/29/2002 12/30/2002 12/31/2002
222 Figure 6: Temporal variations of Rn, CO and SO2 concentrations at the summit of Mt. Fuji during December 2002.
Table 1: Chemical species measured at the summit of Mt. Fuji as of the spring in 2003. Species Measurement Instrument DL Precision 7Be HV-sampler Sibata HVC1000F ～0.1 mBq/m3 ～20% RSD → γ - spectrometry Ortec or Eurysis
222 Electrostatic 3 Rn Semi-home made 0.3 Bq/m ～20% RSD collection → α - spectrometry Ohyoh-Koken Co. at 1 Bq/m3 Species compared O3 Ultraviolet absorption Dylec 1007-AHJ 2 ppbv Dylec 1150 Thermo Electron CO Gas filter correlation 15 ppbv 48C Ultraviolet Thermo Electron SO 0.1 ppbv 0.1 ppbv 2 fluorescence 43C-TL Other species
measured CO2 Infrared absorption Licor 6252 0.1 ppmv Andersen Black carbon Aethalometer Instruments Aerosol sulfate HV sampler Sibata HVC1000F HP-Yokogawa or And ionic species ion chromatography → Dionex Particle number Laser particle counter Kanomax
80 14CO and its Application in Studies of Atmospheric Chemistry and Transport
Patrick Jöckel and Carl A. M. Brenninkmeijer (Contact: [email protected], [email protected])
The primary origin of atmospheric 14CO is production by cosmic radiation. High energy cosmic rays (mainly protons) induce large nucleonic particle cascades in the atmosphere and produce atmospheric neutrons. Most of them diffuse and thermalize before they are captured by nitrogen nuclei forming 14C (14N(n,p)14C). The recoil 14C atom rapidly oxidizes to 14CO, with a yield that has been determined to be approximately 95% [ Pandow et al., 1960; MacKay et al., 1963]. In this way, a natural tracer is produced throughout the atmosphere, almost equally partitioned between the stratosphere and the troposphere, however with its maximum in polar regions caused by the influence of the geomagnetic field on the primary cosmic ray particles. The average source strength is 1.6 - 2 molecules per second and per square-centimeter of the Earth's surface, corresponding to a total production of approximately 13-16 kg 14CO per year. Since the cosmic ray flux reaching the atmosphere is modulated by the solar wind intensity, the cosmogenic 14CO production rate oscillates with a phase of 11 years (solar cycle) with higher production rates during times of low solar activity.
The secondary (”biogenic”) contribution, comprising 20-25% of the total source, consists of recycled 14CO from the biosphere, entering or evolving in the atmosphere by oxidation of natural methane and higher hydrocarbons, and by biomass burning. The use of fossil fuel does not contribute to atmospheric 14CO as geological production times vastly exceed the 14C half life of about 5730 years.
The significance of 14CO is that it constitutes a natural tracer that can be used to assess the hydroxyl radical (OH) abundance, because 14 CO + OH is its main sink reaction, with an average tropospheric lifetime of 14CO of about 2-3 months.
Already before the discovery of the important role of OH in the troposphere [Levy, 1971], Weinstock [1969] estimated the residence time of CO, using 14CO measurements, or more precisely the specific activity of CO measured by MacKay et al. [1963]. The implicit assumptions of the approach of Weinstock [1969] and the implications for CO budget calculations have been discussed by Junge et al. [1971]. Volz et al. [1981] applied the 14CO concept in a systematic manner and concluded that the abundance and seasonality of 14CO is in accordance with that of OH used in a two-dimensional (2-D) atmospheric chemistry model. 14CO measurements had been exclusively performed using proportional gas counters requiring large amounts of air (~ 200 m3) to be processed.
Routine measurements of 14CO in smaller air samples with increased precision [Brenninkmeijer, 1993] became possible with the advent of accelerator mass spectrometry (AMS). Air sampling techniques suitable for isotopic analysis and extraction procedures for isolating CO from the air samples are described for instance by Brenninkmeijer and Roberts [1994], Mak and Brenninkmeijer [1994], and Brenninkmeijer [1993]. Aspects of the AMS measurements are discussed in Rom et al. [2000b]. Brenninkmeijer et al. [1992] observed lower 14CO levels in the southern hemisphere, which were attributed to higher southern hemisphere (SH) OH levels, in contradiction to ideas about higher northern hemisphere (NH) OH values due to the importance of NO in recycling OH [Crutzen and Zimmermann, 1991]. Mak et al. [1992, 1994] measured 14CO in air sampled in the free troposphere, applied two different 2-D models and concluded that apart from the NH-SH asymmetry, generally atmospheric levels seemed lower than inferred by the models employed. Quay et al. [2000] investigated various 14CO measurements with a 2-D model and concluded that either a higher horizontal mixing or a higher OH concentration in the SH is responsible for the observed inter-hemispheric asymmetry of 14CO. In the meantime, more and more 14CO measurements at surface level and in the free troposphere have become available [Mak and Southon, 1998; Tyler et al., 1999; Röckmann and Brenninkmeijer, 1997; Röckmann et
81 al., 1999; Kato et al., 2000; Rom et al., 2000a; Quay et al., 2000]. The first 14CO analysis of lower stratospheric air samples is reported by Brenninkmeijer et al. [1995].
Three independent estimates of the primary cosmogenic 14CO source distribution exist [Lingenfelter, 1963; O'Brien et al., 1991; Masarik and Beer, 1999 (see also contribution of J. Masarik on page 67 of this report)] which differ mostly according to the vertical gradient of the production rate. However, Jöckel et al. [1999] and Jöckel [2000] showed that this uncertainty is not a principle problem for the 14CO methodology. Also, the effect of the solar variation is well understood and can be taken into account when 14CO observations of different epochs are to be compared [Jöckel et al., 2000]. This lays the foundation for compiling a 14CO climatology, i.e., a zonally averaged seasonal cycle at the surface comprising 1088 14CO observations from 4 institutes [Jöckel and Brenninkmeijer, 2002]. Jöckel et al. [2002] (Jöckel [2000]) used this climatology for the evaluation of two different 3-dimensional atmospheric models and revisited the observed inter-hemispheric asymmetry of atmospheric 14CO.
REFERENCES
Brenninkmeijer, C. A. M. Measurement of the abundance of 14CO in the atmosphere and the 13C/12C and 18O/16O ratio of atmospheric CO with applications in New Zealand and Antarctica, J. Geophys. Res., 98(D6), 10595-10614, 1993. Brenninkmeijer, C. A. M., D. C. Lowe, M. R. Manning, R. J. Sparks, and P. F. J. v. Velthoven. 13 14 18 The C, C, and O isotopic composition of CO, CH4 and CO2 in the higher southern latitudes lower stratosphere, J. Geophys. Res., 100(D12), 26163-26172, 1995. Brenninkmeijer, C. A. M., M. R. Manning, D. C. Lowe, G. Wallace, R. J. Sparks, and A. Volz-Thomas. Interhemispheric asymmetry in OH abundance inferred from measurements of atmospheric 14CO, Nature, 356, 50-52, 1992. Brenninkmeijer, C. A. M. and P. A. Roberts. An air-driven pressure booster pump for aircraft-based sampling, J. Atm. Oc. Tech., 11(6), 1664-1671, 1994. Crutzen, P. J. and P. H. Zimmermann, The changing photochemistry of the troposphere, Tellus, 43AB(4), 136-151, 1991. Jöckel, P., C. A. M. Brenninkmeijer, M. G. Lawrence, A. B. M. Jeuken, and P. F.J. van Velthoven. Evaluation of stratosphere - troposphere exchange and the hydroxyl radical distribution in 3- dimensional global atmospheric models using observations of cosmogenic 14CO, J. Geophys. Res., 107(D20), 4446, doi:10.1029/2001JD001324, 2002. Jöckel, P. and C. A. M. Brenninkmeijer. The seasonal cycle of cosmogenic 14CO at the surface level: A solar cycle adjusted, zonal average climatology based on observations, J. Geophys. Res., 107(D22), 4656, doi:10.1029/2001JD001104, 2002. Jöckel, P. Cosmogenic 14CO as tracer for atmosperic chemistry and transport, Ph.D. thesis, Combined Faculties for the Natural Sciences and for Mathematics of the Rupertus Carola University of Heidelberg, Germany, 2000, (http://www.ub.uni-heidelberg.de/archiv/1426). Jöckel, P., C. A. M. Brenninkmeijer, and M. G. Lawrence. Atmospheric response time of cosmogenic 14CO to changes in solar activity, J. Geophys. Res., 105(D5), 6737-6744, 2000. Jöckel, P., M. G. Lawrence, and C. A. M. Brenninkmeijer. Simulations of cosmogenic 14CO using the three- dimensional atmospheric model MATCH: Effects of 14C production distribution and the solar cycle, J. Geophys. Res., 104(D9), 11733-11743, 1999. Junge, C., W. Seiler, and P. Warneck, The atmospheric 12CO and 14CO budget, J. Geophys. Res., 76(12), 2866-2879, 1971. Kato, S., Y. Kajii, H. Akimoto, M. Bräunlich, T. Röckmann, and C. A. M. Brenninkmeijer, Observed and modeled seasonal variation of 13C, 18O, and 14C of atmospheric CO at Happo, a remote site in Japan, and a comparison with other records, J. Geophys. Res., 105(D7), 8891-8900, 2000. Levy, H. Normal atmosphere: Large radical and formaldehyde concentrations predicted, Science, 173, 141- 143, 1971. Lingenfelter, R. E. Production of carbon 14 by cosmic-ray neutrons, Rev. Geophys., 1, 35-55, 1963.
82 MacKay, C., M. Pandow, and R. Wolfgang. On the chemistry of natural radiocarbon, J. Geophys. Res., 68, 3929-3931, 1963. Mak, J. E. and C. A. M. Brenninkmeijer. Compressed air sample technology for isotopic analysis of atmospheric carbon monoxide, J. Atm. Oc. Tech., 11(2), 1994. Mak, J. E., C. A. M. Brenninkmeijer and M. R. Manning. Evidence for a missing carbon monoxide sink based on tropospheric measurements of 14CO, J. Geophys. Res., 19(14), 1467-1470, 1992. Mak, J. E., C. A. M. Brenninkmeijer, and J. Tamaresis. Atmospheric 14CO observations and their use for estimating carbon monoxide removal rates, J. Geophys. Res., 99(D11), 22915-22922, 1994. Mak, J. E. and J. R. Southon. Assessment of tropical OH seasonality using atmospheric 14CO measurements from Barbados, Geophys. Res. Lett., 25(15), 2801-2804, 1998. Masarik, J. and J. Beer. Simulation of particle fluxes and cosmogenic nuclide production in the Earth's atmosphere, J. Geophys. Res., 104(D10), 12099-12111, 1999. O'Brien, K., A. de la Zerda Lerner, M. A. Shea, and D. F. Smart. The production of cosmogenic isotopes in the Earth's atmosphere and their inventories, In C. P. Sonett, M. S. Giampapa, and M. S. Matthews, editors, The sun in time, pages 317-342. The University of Arizona Press, Tucson, Arizona, 1991. Pandow, M., C. MacKay, and R. Wolfgang. The reaction of atomic carbon with oxygen: Significance for the natural radio-carbon cycle, J. Inorg. Nucl. Chem., 14, 153-158, 1960. Quay, P., S. King, D. White, M. Brockington, B. Plotkin, R. Gammon, S. Gerst, and J. Stutsman. Atmospheric 14CO: A tracer of OH concentration and mixing rates. J. Geophys. Res., 105(D12), 15147- 15166, 2000.
Röckmann, T. and C. A. Brenninkmeijer. CO and CO2 isotopic composition in Spitsbergen during the 1995 ARCTOC campaign, Tellus, 49B, 445-465, 1997. Röckmann, T., C. A. M. Brenninkmeijer, M. Hahn, and N. F. Elansky. CO mixing and isotope ratios across Russia; Trans-Siberian railroad expedition TROICA 3, April 1997, Chemosphere Glob. Change Sci., 1, 219-231, 1999. Rom, W., C. Brenninkmeijer, M. Bräunlich, G. R., M. Mandl, A. Kaiser, W. Kutschera, A. Priller, S. Puchegger, T. Röckmann, and P. Steier. A detailed 2-year record of atmospheric 14CO in the temperate northern hemisphere, Nucl. Instr. Meth. B, 161, 780-785, 2000a. Rom, W., C. A. M. Brenninkmeijer, C. B. Ramsey, W. Kutschera, A. Priller, S. Puchegger, T. Röckmann, and P. Steier. Methodological aspects of atmospheric 14CO measurements with AMS, Nucl. Instr. Meth. B, (Proceedings of the Eighth International Conference on Accelerator Mass Spectrometry, Vienna, Austria, September 6-10, 1999), 172, 530-536, 2000b. Tyler, S. C., G. A. Klouda, G. W. Brailsford, A. C. Manning, J. M. Conny, and A. J. T. Jull. Seasonal snapshots of the isotopic (14C, 13C) composition of tropospheric carbon monoxide at Niwot Ridge, Colorado, Chemosphere Glob. Change Sci., 1, 185-203, 1999. Volz, A., D. H. Ehhalt, and R. G. Derwent. Seasonal and latitudinal variation of 14CO and the tropospheric concentration of OH radicals, J. Geophys. Res., 86(NC6), 5163-5171, 1981. Weinstock, B., Carbon monoxide: Residence time in the atmosphere, Science, 166, 224-225, 1969.
83 Meteorological Traceability In Radionuclide Measurements Present Status and Future Challenges
Aleš Fajgelj∗
In 2001, the International Union of Pure and Applied Chemistry (IUPAC) initiated a project “Metrological Traceability of Chemical Measurement Results”. This project was initiated on the basis of the importance of metrological traceability in general and especially in border crossing measurements, and at the same time on the basis of an identified lack of common understanding of basic principles and a lack of appropriate tools for establishing metrological traceability chains. Looking closer at the metrological traceability in radionuclide measurements, one can observe a very similar situation as in other physical and chemical measurement fields. The International Committee for Radionuclide Metrology (ICRM) and its Working Groups extensively deal with all technical aspects of radionuclide measurements and determinations, covering α-, β- and γ- emitting radionuclides at all activity levels, their physical characteristics (half-time, decay schemes, etc.), chemical behaviors (chemical reactions, bounding, adsorption, etc.), as well as biological aspects (ionizing effects, dosimetry, etc.) and measurement techniques. One of the activities is also quality assurance and traceability. However, due to the number of specifics related to each radionuclide, and different measurement techniques applied, there are various pathways and concepts for establishing and demonstrating metrological traceability.
Backed-up by the International Union of Pure and Applied Physics (IUPAP), the above- mentioned project was extended in 2003 and proposed as an ICSU project. Taking into account a currently ongoing revision of the International Vocabulary of Basic and General Terms in Metrology (VIM), the project team is already elaborating a number of general traceability scenarios with supporting examples. As the final aim of the project is to bring together various international and regional organizations from the measurement field, including IAEA, WMO, WHO, BIPM, etc. in an attempt to harmonize approaches to metrological traceability of measurement results at international level, more details will be presented in this contribution.
∗ Author is the member of the IUPAC Analytical Chemistry Division Committee and the Chairman of the IUPAC Interdivisional Working Party on Harmonization of Quality Assurance Schemes.
84 ANNEX A
1ST INTERNATIONAL EXPERT MEETING/WORKSHOP ON:
SOURCES AND MEASUREMENTS OF NATURAL RADIONUCLIDES APPLIED TO CLIMATE AND AIR QUALITY STUDIES (3 – 5 June 2003, Gif sur Yvette, France)
Final Announcement
BACKGROUND AND OBJECTIVES
Observations of natural radionuclides (222Rn, 220Rn, 212Pb, 210 Pb, 10Be, 7Be etc) from terrestrial and upper atmospheric sources have been widely used in the analysis and interpretation of air chemistry measurements and in the evaluation of air quality and climate models simulating chemical transport, transformation and removal processes of gases and aerosols. Currently, the effective use of these substances is limited by the accuracy of source functions used by models and by a globally uncoordinated approach to measurements, data archiving and quality assurance. A meeting of experts is needed: 1) to document the current situation with respect to measurements of natural radionuclides and modelling of their global cycles and 2) to recommend a strategy for improving measurements and the application of measurements to climate and air quality research and modelling.
MEETING/WORKSHOP TOPICS
1. Source processes and source algorithms for natural radionuclides used in atmospheric models. 2. Measuring natural radionuclides in the atmosphere on a routine basis. 3. Quality assuring, archiving and applying radionuclide measurements in research and monitoring studies. 4. Modelling the cycles of natural radionuclides in the atmosphere and using the measurements of natural radionuclides for atmospheric climate and air quality model evaluation.
SPONSORS
World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) World Climate Research Programme (WCRP) International Atomic Energy Agency (IAEA) French Atomic Energy Commission (CEA) Environmental Measurements Laboratory (EML) -- GAW radionuclide lead agency
EXECUTIVE COMMITTEE
Leonard A. Barrie, co-chair, World Meterological Organization/GAW, Geneva, Switzerland H. N. (Sam) Lee, co-chair, Environmental Measurements Laboratory, New York, U.S.A. Michel Ramonet, CEA-CNRS, Laboratory of Science of Climate and the Environment, (LSCE), France Gabriele Voigt, International Atomic Energy Association, Vienna, Austria Gilles Sommeria-Klein, World Climate Research Program, Geneva, Switzerland
85
SCIENTIFIC ADVISORY COMMITTEE
Wlodek Zahorowski, Australian Nuclear Science and Technology Organization, Menai, NSW, Australia Yves Balkanski, Laboratory of Science of Climate and the Environment, CEA, France Yasuhito Igarashi, Meteorological Research Institute, Japan Ingeborg Levin, University of Heidelberg, Germany Johann Feichter, Max Planck Institute for Meteorology, Germany Stephen Schery, New Mexico Institute Of Mining and Technology, U.S.A. Colin Sanderson, EML, U.S.A.
LOCAL HOSTS
Michel Ramonet, LSCE, Lead Laurent Jourdheuil, LSCE
SCOPE
The meeting will consist of a day of expert presentations documenting the current situation and two days of workshop to develop a written strategy for improving the efficacy of natural radionuclide measurements and modelling. There will be a joint WMO/GAW, WCRP, IAEA report on this expert meeting/workshop published in the WMO/GAW report series.
CONTACT INFORMATION
Local Host Dr Michel Ramonet Phone: 33 1 69 08 40 14 E-mail: [email protected] http://www.radionuc.cnrs-gif.fr/
86 ANNEX B
1st INTERNATIONAL EXPERT MEETING/WORKSHOP ON
SOURCES AND MEASUREMENTS OF NATURAL RADIONUCLIDES APPLIED TO CLIMATE AND AIR QUALITY STUDIES (3 – 5 June 2003, Gif sur Yvette, France)
Agenda
Tuesday, June 3, 2003
09:00 Opening Remarks, Michel Ramonet, CNRS, France; Mitchell Erickson, EML, USA; Gabriele Voight, IAEA, Vienna 09:30 Natural Radionuclide Research and Observations in the Global Atmosphere Watch (GAW) and World Climate Research Programmes (WCRP) Leonard Barrie, WMO/GAW and Gilles Sommeria-Klein, WCRP, WMO, Switzerland.
10:00 Issues and Challenges of Using Natural Radionuclides As Tracers for Atmospheric Studies, Hsi-Na (Sam) Lee, EML, USA 10:30 Coffee/Tea Break 11:00 Variation of 222Rn flux and its implications for atmospheric tracer studies, Franz Conen (presented by Michel Ramonet or Bernard Lehmann), Univ. of Edinburgh, UK 11:30 Progress on Global 222Rn Flux Maps and Recommendations for Future Research, Steven Schery, New Mexico Inst. Of Mining and Technology, USA 12:00 EML Global Network For Measuring Radionuclides, Colin Sanderson/Hsi-Na (Sam) Lee, EML, USA 12:30 Lunch 14:00 222Rn in the Atmospheric Boundary Layer: A Contrast Between Measurements Made at a Baseline Site in the Southern Ocean and a Network of Sites in East Asia, Wlodek Zahorowski, Australian Nuclear Science and Technology Organization, Australia 14:30 222Rn Airborne Measurements, Dominique Filippi, LSCE, France 15:00 Assessment of Laboratory Performance by Interlaboratory Comparison – the IAEA Approach, Zbigniew Radecki, IAEA 15:30 Coffee/Tea Break 16:00 Natural Radionuclides as Tracers in Multi-Compartment Transport Models, Johann Feichter, Max Planck Institute For Meteorology, Germany 16:30 Cosmogenic Radionuclide Production in the Earth Atmosphere: Numerical Simulation, Jozef Masarik, Komensky University, Slovakia
87 17:00 Measurements of Cosmic-Ray Neutron Spectra in the Stratosphere: a Benchmark for Calculations of Cosmogenic Nuclide Production (pre-recorded presentation), Paul Goldhagen, EML, USA
17:10 Part I: Effect of Model Grid Resolution and Nudging Winds on the Simulated Distribution of 222Rn and Part II: The Importance of the Different Terms of Wet Scavenging in the Atmospheric Burden and Vertical Distribution of Pb-210, Yves Balkanski, LSCE, France
17:40 Adjourn for the day
Wednesday, June 4, 2003
09:00 Workshop Discussions Break into three working groups (i.e., Source processes and Source Algorithm, Measurements and QA/QC, Modelling and Other Applications) (Distribute a set of focus questions prepared by the members of Executive and Scientific Advisory Committees for each working group) 10:30 Coffee/Tea Break 12:20 Lunch 13:40 Reports and recommendations from each working group to the workshop 15:30 Coffee/Tea Break 16:00 Discussions of reports and recommendations
18:00 Adjourn for the day
Thursday, June 5, 2003
09:00 Writing of final recommendations by group rapporteurs 10:30 Coffee/Tea Break 11:00 Review of draft document and recommendations 12:20 Lunch 13:40 Continuation on review of draft document and recommendations 15:30 Coffee/Tea Break 16:00 Discussion of action items, implementation plan 17:00 Close of meeting/workshop
88 ANNEX C
1ST INTERNATIONAL EXPERT MEETING/WORKSHOP ON
SOURCES AND MEASUREMENTS OF NATURAL RADIONUCLIDES APPLIED TO CLIMATE AND AIR QUALITY STUDIES (3 - 5 June 2003, Gif sur Yvette, France)
List of Contributors and Participants
Ales Fajgelj Yves Balkanski Laboratory of Science of Climate and the International Atomic Energy Agency IAEA PO Box 100 Environment (LSCE) Joint Research Unit CEA-CNRS Wagramer Strasse 5 CEA/Saclay, Bât. 709, Orme des Merisiers A-1400 Vienna Austria F-91191 Gif-sur-Yvette Cedex France Tel: +43 1 2600 28233 Tel: +33 1 69 08 77 25 Fax: +43 1 2600-28222 Email: [email protected] Fax: +33 1 69 08 77 16
E-mail: [email protected] Johann Feichter Max Planck Institute for Meteorology Leonard A. Barrie Bundesstr. 55 Chief Environment Division, AREP D-20146 Hamburg World Meteorological Organization Germany 7 bis, Avenue de la Paix Tel: +43 40 41173 317 BP2300, 1211 Geneva 2 Fax: +43 40 41173 298 Switzerland E-mail: [email protected] Tel +41 (0) 22 730 82 40 Fax +41 (0) 22 730 80 49 Email: [email protected] Dominique Filippi Laboratory of Science of Climate and the Franz Conen Environment (LSCE) University of Edinburgh Joint Research Unit CEA-CNRS Darwin Building CEA Saclay, Bât. 709, Orme des Merisiers Mayfield Road F-91191 Gif-sur-Yvette Cedex Edinburgh EH9 3JU , France UK Tel: +33 1 69 08 38 91 Tel.: +44 131 650 7723 Fax: +33 1 69 08 77 16 E-mail: [email protected] E-mail: [email protected]
Mitchell Erickson U. S. Department of Homeland Security Metodi Gelev Director Head Environmental Measurements Laboratory of Radiation Protection Laboratory in INRNE, 201 Varick St., 5th Floor 72, Tzarigradsko chaussee Blvd New York, N.Y. 10014-7447 1784 Sofia USA Bulgaria Tel: +212 620-3619 Email: [email protected] Fax: +212 620-3651 E-mail: [email protected]
89 Yasuhito Igarashi Hsi-Na (Sam) Lee Geochemical Research Department U. S. Department of Homeland Security Meteorological Research Institute Environmental Measurements Laboratory 1-1 Nagamine, Tsukuba 201 Varick St., 5th Floor Ibaraki 305-0052 New York, N.Y. 10014-7447 Japan USA Tel: +81-298-53-8726 Tel: +212 620-6607 Fax: +81-298-53-8728 Fax: +212 620-3600 E-mail: [email protected] E-mail: [email protected]
Bernhard E. Lehmann Patrick Jöckel Physics Institute, University of Bern Max Planck Institute for Chemistry Sidlerstr.5 Department for Atmospheric Chemistry CH-3012 Bern P.O. Box 3060, 55020 Mainz Switzerland Germany Tel: +41 (0) 31 631 85 30 Tel: +49 - 6131 - 305452 Fax: +41 (0) 631 87 42 Fax: +49 - 6131 - 305436 E-mail: [email protected] E-mail: [email protected] Jozef Masarik Faculty of Mathematics and Physics, Komensky Beatrice Josse University Meteo France Department of Nuclear Physics CNRM/GMGEC/ERAM, Mlynska dolina F/1, 42 av. G. Coriolis, SK-842 15 Bratislava 31057 - Toulouse Cedex 1 Slovakia France. Tel: +421-7-65424000 Email: [email protected] Fax: +421-7-65425882 E-mail: [email protected]
Laurent Jourdheuil
Laboratory of Science of Climate and the Marie Antionette Melieres Environment (LSCE) Joint Research Unit CEA-CNRS Laboratoire de Glaciologie et Geophysique de l’Environnement CEA Saclay, Bât. 709, Orme des Merisiers 54, rue Moliere F-91191 Gif-sur-Yvette Cedex, France BP 96 38402 St Martin d’Heres Cedex Tel: +33 1 69 08 87 29 France Fax: +33 1 69 08 77 16 Tel: +33 4 76 82 42 11 E-mail: [email protected] Fax: +33 4 76 82 42 01 Email :[email protected] Victor Kazan Laboratory of Science of Climate and the Environment (LSCE) Jussi Paatero Joint Research Unit CEA-CNRS Finnish Meteorological Institute CEA Saclay, Bât. 709, Orme des Merisiers Sahaajankatu 20E F-91191 Gif-sur-Yvette Cedex, Fin-00810 Helsinki France Finland Tel: +358-9-1929-5495 Fax: +358-9-1929-5403 Casper Labuschagne E-mail: [email protected] Cape Point GAW Station South African Weather Service Zbigniew Radecki C/o CSIR Analytical Quality Control Services PO Box 320 Chemistry Unit Stellenbosch 7599 International Atomic Energy Agency South Africa Agency's Laboratories Seibersdorf Tel: +27 21 888 2636 A-2444 Seibersdorf Fax: +27 21 888 2688 Austria Email: [email protected] Tel: + 43 1 2600 28226 Fax: + 43 1 2600 28222 E-mail: [email protected]
90 Michel Ramonet Khrum Velchev Laboratory of Science of Climate and the National Institute of Meteorology and Hydrology Environment (LSCE) Bulgarian Academy of Sciences Joint Research Unit CEA-CNRS Department of Air and Water Pollution CEA/Saclay, Bât. 709, Orme des Merisiers 66 Tzarigradsko chaussee F-91191 Gif-sur-Yvette Cedex, 1784 Sofia France Bulgaria Tel: +33 1 69 08 40 14 Tel: +359 2 975 39 86 Fax: +33 1 69 08 77 16 Fax: +359 2 988 44 94 E-mail: [email protected] Home: +359 2 74 99 48 Mobille: +359 89 21 85 17 Colin G. Sanderson E-mail: [email protected] U. S. Department of Homeland Security E-mail: [email protected] Environmental Measurements Laboratory 201 Varick St., 5th Floor Gabriele Voigt New York, N.Y. 10014-7447 International Atomic Energy Agency USA Director Agency's Laboratories Seibersdorf Tel: +212 620-3642 Wagramer Strasse 5, P.O.Box 200 Fax: +212 620-3651 A-1400 Vienna E-mail: [email protected] Austria Tel: +43 1 2600 28248 Stephen D. Schery Fax: +43 1 2600 28222 Physics Department E-mail: [email protected] New Mexico Institute of Mining and Technology Socorro, NM 87801 Hiromi Yamazawa USA Department of Nuclear Engineering, Graduate Tel: +505-835-5341 School of Engineering, E-mail: [email protected] Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 Japan Gilles Sommeria Tel: +81-52-789-3781 World Meteorological Organization Fax: +81-52-789-3782 World Climate Research Program E-mail: [email protected] Geneva Switzerland Wlodek Zahorowski Tel: +41 22 730 8247 Leader, Atmospheric Radioactivity E-mail: [email protected] Australian Nuclear Science and Technology Organization PMB 1, Menai, NSW 2234 Thomas Steinkopff Australia Deutscher Wetterdienst Tel: +61 2 9717 3804 Abt.Messnetze und Daten Fax: +61 2 9717 9260 Referat TI24 E-mail: [email protected] Frankfurter Straße 135 63067 Offenbach Germany Tel: +49 69 8062 2774 Fax: +49 69 8062 3782 E-mail: [email protected]
Shochi Taguchi National Institute of Advanced Industrial Science and Technology Tsukuba West 16-1 Onogawa, Tsukuba, 305-8569 Japan Tel: +81-298-61-8384 Fax: +81-298-61-8358 E-mail: [email protected]
91 GLOBAL ATMOSPHERE WATCH REPORT SERIES
1. Final Report of the Expert Meeting on the Operation of Integrated Monitoring Programmes, Geneva, 2-5 September 1980.
2. Report of the Third Session of the GESAMP Working Group on the Interchange of Pollutants Between the Atmosphere and the Oceans (INTERPOLL-III), Miami, USA, 27-31 October 1980.
3. Report of the Expert Meeting on the Assessment of the Meteorological Aspects of the First Phase of EMEP, Shinfield Park, U.K., 30 March - 2 April 1981.
4. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at April 1981.
5. Report of the WMO/UNEP/ICSU Meeting on Instruments, Standardization and Measurements Techniques for Atmospheric CO2, Geneva, 8-11; September 1981.
6. Report of the Meeting of Experts on BAPMoN Station Operation, Geneva, 23-26 November, 1981.
7. Fourth Analysis on Reference Precipitation Samples by the Participating World Meteorological Organization Laboratories by Robert L. Lampe and John C. Puzak, December 1981.
8. Review of the Chemical Composition of Precipitation as Measured by the WMO BAPMoN by Prof. Dr. Hans-Walter Georgii, February 1982.
9. An Assessment of BAPMoN Data Currently Available on the Concentration of CO2 in the Atmosphere by M.R. Manning, February 1982.
10. Report of the Meeting of Experts on Meteorological Aspects of Long-range Transport of Pollutants, Toronto, Canada, 30 November - 4 December 1981.
11. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at May 1982.
12. Report on the Mount Kenya Baseline Station Feasibility Study edited by Dr. Russell C. Schnell.
13. Report of the Executive Committee Panel of Experts on Environmental Pollution, Fourth Session, Geneva, 27 September - 1 October 1982.
14. Effects of Sulphur Compounds and Other Pollutants on Visibility by Dr. R.F. Pueschel, April 1983.
15. Provisional Daily Atmospheric Carbon Dioxide Concentrations as Measured at BAPMoN Sites for the Year 1981, May 1983.
16. Report of the Expert Meeting on Quality Assurance in BAPMoN, Research Triangle Park, North Carolina, USA, 17-21 January 1983.
17. General Consideration and Examples of Data Evaluation and Quality Assurance Procedures Applicable to BAPMoN Precipitation Chemistry Observations by Dr. Charles Hakkarinen, July 1983.
93 18. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at May 1983.
19. Forecasting of Air Pollution with Emphasis on Research in the USSR by M.E. Berlyand, August 1983.
20. Extended Abstracts of Papers to be Presented at the WMO Technical Conference on Observation and Measurement of Atmospheric Contaminants (TECOMAC), Vienna, 17-21 October 1983.
21. Fifth Analysis on Reference Precipitation Samples by the Participating World Meteorological Organization Laboratories by Robert L. Lampe and William J. Mitchell, November 1983.
22. Report of the Fifth Session of the WMO Executive Council Panel of Experts on Environmental Pollution, Garmisch-Partenkirchen, Federal Republic of Germany, 30 April - 4 May 1984 (WMO TD No. 10).
23. Provisional Daily Atmospheric Carbon Dioxide Concentrations as Measured at BAPMoN Sites for the Year 1982. November 1984 (WMO TD No. 12).
24. Final Report of the Expert Meeting on the Assessment of the Meteorological Aspects of the Second Phase of EMEP, Friedrichshafen, Federal Republic of Germany, 7-10 December 1983. October 1984 (WMO TD No. 11).
25. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at May 1984. November 1984 (WMO TD No. 13).
26. Sulphur and Nitrogen in Precipitation: An Attempt to Use BAPMoN and Other Data to Show Regional and Global Distribution by Dr. C.C. Wallén. April 1986 (WMO TD No. 103).
27. Report on a Study of the Transport of Sahelian Particulate Matter Using Sunphotometer Observations by Dr. Guillaume A. d'Almeida. July 1985 (WMO TD No. 45).
28. Report of the Meeting of Experts on the Eastern Atlantic and Mediterranean Transport Experiment ("EAMTEX"), Madrid and Salamanca, Spain, 6-8 November 1984.
29. Recommendations on Sunphotometer Measurements in BAPMoN Based on the Experience of a Dust Transport Study in Africa by Dr. Guillaume A. d'Almeida. September 1985 (WMO TD No. 67).
30. Report of the Ad-hoc Consultation on Quality Assurance Procedures for Inclusion in the BAPMoN Manual, Geneva, 29-31 May 1985.
31. Implications of Visibility Reduction by Man-Made Aerosols (Annex to No. 14) by R.M. Hoff and L.A. Barrie. October 1985 (WMO TD No. 59).
32. Manual for BAPMoN Station Operators by E. Meszaros and D.M. Whelpdale. October 1985 (WMO TD No. 66).
33. Man and the Composition of the Atmosphere: BAPMoN - An international programme of national needs, responsibility and benefits by R.F. Pueschel, 1986.
34. Practical Guide for Estimating Atmospheric Pollution Potential by Dr. L.E. Niemeyer. August 1986 (WMO TD No. 134).
94 35. Provisional Daily Atmospheric CO2 Concentrations as Measured at BAPMoN Sites for the Year 1983. December 1985 (WMO TD No. 77).
36. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1984. Volume I: Atmospheric Aerosol Optical Depth. October 1985 (WMO TD No. 96).
37. Air-Sea Interchange of Pollutants by R.A. Duce. September 1986 (WMO TD No. 126).
38. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at 31 December 1985. September 1986 (WMO TD No. 136).
39. Report of the Third WMO Expert Meeting on Atmospheric Carbon Dioxide Measurement Techniques, Lake Arrowhead, California, USA, 4-8 November 1985. October 1986.
40. Report of the Fourth Session of the CAS Working Group on Atmospheric Chemistry and Air Pollution, Helsinki, Finland, 18-22 November 1985. January 1987.
41. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1982, Volume II: Precipitation chemistry, continuous atmospheric carbon dioxide and suspended particulate matter. June 1986 (WMO TD No. 116).
42. Scripps reference gas calibration system for carbon dioxide-in-air standards: revision of 1985 by C.D. Keeling, P.R. Guenther and D.J. Moss. September 1986 (WMO TD No. 125).
43. Recent progress in sunphotometry (determination of the aerosol optical depth). November 1986.
44. Report of the Sixth Session of the WMO Executive Council Panel of Experts on Environmental Pollution, Geneva, 5-9 May 1986. March 1987.
45. Proceedings of the International Symposium on Integrated Global Monitoring of the State of the Biosphere (Volumes I-IV), Tashkent, USSR, 14-19 October 1985. December 1986 (WMO TD No. 151).
46. Provisional Daily Atmospheric Carbon Dioxide Concentrations as Measured at BAPMoN Sites for the Year 1984. December 1986 (WMO TD No. 158).
47. Procedures and Methods for Integrated Global Background Monitoring of Environmental Pollution by F.Ya. Rovinsky, USSR and G.B. Wiersma, USA. August 1987 (WMO TD No. 178).
48. Meeting on the Assessment of the Meteorological Aspects of the Third Phase of EMEP IIASA, Laxenburg, Austria, 30 March - 2 April 1987. February 1988.
49. Proceedings of the WMO Conference on Air Pollution Modelling and its Application (Volumes I-III), Leningrad, USSR, 19-24 May 1986. November 1987 (WMO TD No. 187).
50. Provisional Daily Atmospheric Carbon Dioxide Concentrations as Measured at BAPMoN Sites for the Year 1985. December 1987 (WMO TD No. 198).
51. Report of the NBS/WMO Expert Meeting on Atmospheric CO2 Measurement Techniques, Gaithersburg, USA, 15-17 June 1987. December 1987.
52. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1985. Volume I: Atmospheric Aerosol Optical Depth. September 1987.
95 53. WMO Meeting of Experts on Strategy for the Monitoring of Suspended Particulate Matter in BAPMoN - Reports and papers presented at the meeting, Xiamen, China, 13-17 October 1986. October 1988.
54. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1983, Volume II: Precipitation chemistry, continuous atmospheric carbon dioxide and suspended particulate matter (WMO TD No. 283).
55. Summary Report on the Status of the WMO Background Air Pollution Monitoring Network as at 31 December 1987 (WMO TD No. 284).
56. Report of the First Session of the Executive Council Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry, Hilo, Hawaii, 27-31 March 1988. June 1988.
57. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1986, Volume I: Atmospheric Aerosol Optical Depth. July 1988.
58. Provisional Daily Atmospheric Carbon Dioxide Concentrations as measured at BAPMoN sites for the years 1986 and 1987 (WMO TD No. 306).
59. Extended Abstracts of Papers Presented at the Third International Conference on Analysis and Evaluation of Atmospheric CO2 Data - Present and Past, Hinterzarten, Federal Republic of Germany, 16-20 October 1989 (WMO TD No. 340).
60. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1984 and 1985, Volume II: Precipitation chemistry, continuous atmospheric carbon dioxide and suspended particulate matter.
61. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data for 1987 and 1988, Volume I: Atmospheric Aerosol Optical Depth.
62. Provisional Daily Atmospheric Carbon Dioxide Concentrations as measured at BAPMoN sites for the year 1988 (WMO TD No. 355).
63. Report of the Informal Session of the Executive Council Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry, Sofia, Bulgaria, 26 and 28 October 1989.
64. Report of the consultation to consider desirable locations and observational practices for BAPMoN stations of global importance, Bermuda Research Station, 27-30 November 1989.
65. Report of the Meeting on the Assessment of the Meteorological Aspects of the Fourth Phase of EMEP, Sofia, Bulgaria, 27 and 31 October 1989.
66. Summary Report on the Status of the WMO Global Atmosphere Watch Stations as at 31 December 1990 (WMO TD No. 419).
67. Report of the Meeting of Experts on Modelling of Continental, Hemispheric and Global Range Transport, Transformation and Exchange Processes, Geneva, 5-7 November 1990.
68. Global Atmospheric Background Monitoring for Selected Environmental Parameters. BAPMoN Data For 1989, Volume I: Atmospheric Aerosol Optical Depth.
69. Provisional Daily Atmospheric Carbon Dioxide Concentrations as measured at Global Atmosphere Watch (GAW)-BAPMoN sites for the year 1989 (WMO TD No. 400).
96 70. Report of the Second Session of EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry, Santiago, Chile, 9-15 January 1991 (WMO TD No. 633).
71. Report of the Consultation of Experts to Consider Desirable Observational Practices and Distribution of GAW Regional Stations, Halkidiki, Greece, 9-13 April 1991 (WMO TD No. 433).
72. Integrated Background Monitoring of Environmental Pollution in Mid-Latitude Eurasia by Yu.A. Izrael and F.Ya. Rovinsky, USSR (WMO TD No. 434).
73. Report of the Experts Meeting on Global Aerosol Data System (GADS), Hampton, Virginia, 11 to 12 September 1990 (WMO TD No. 438).
74. Report of the Experts Meeting on Aerosol Physics and Chemistry, Hampton, Virginia, 30 to 31 May 1991 (WMO TD No. 439).
75. Provisional Daily Atmospheric Carbon Dioxide Concentrations as measured at Global Atmosphere Watch (GAW)-BAPMoN sites for the year 1990 (WMO TD No. 447).
76. The International Global Aerosol Programme (IGAP) Plan: Overview (WMO TD No. 445).
77. Report of the WMO Meeting of Experts on Carbon Dioxide Concentration and Isotopic Measurement Techniques, Lake Arrowhead, California, 14-19 October 1990.
78. Global Atmospheric Background Monitoring for Selected Environmental Parameters BAPMoN Data for 1990, Volume I: Atmospheric Aerosol Optical Depth (WMO TD No. 446).
79. Report of the Meeting of Experts to Consider the Aerosol Component of GAW, Boulder, 16 to 19 December 1991 (WMO TD No. 485).
80. Report of the WMO Meeting of Experts on the Quality Assurance Plan for the GAW, Garmisch-Partenkirchen, Germany, 26-30 March 1992 (WMO TD No. 513).
81. Report of the Second Meeting of Experts to Assess the Response to and Atmospheric Effects of the Kuwait Oil Fires, Geneva, Switzerland, 25-29 May 1992 (WMO TD No. 512).
82. Global Atmospheric Background Monitoring for Selected Environmental Parameters BAPMoN Data for 1991, Volume I: Atmospheric Aerosol Optical Depth (WMO TD No. 518).
83. Report on the Global Precipitation Chemistry Programme of BAPMoN (WMO TD No. 526).
84. Provisional Daily Atmospheric Carbon Dioxide Concentrations as measured at GAW-BAPMoN sites for the year 1991 (WMO TD No. 543).
85. Chemical Analysis of Precipitation for GAW: Laboratory Analytical Methods and Sample Collection Standards by Dr Jaroslav Santroch (WMO TD No. 550).
86. The Global Atmosphere Watch Guide, 1993 (WMO TD No. 553).
87. Report of the Third Session of EC Panel/CAS Working Group on Environmental Pollution and Atmospheric Chemistry, Geneva, 8-11 March 1993 (WMO TD No. 555).
88. Report of the Seventh WMO Meeting of Experts on Carbon Dioxide Concentration and Isotopic Measurement Techniques, Rome, Italy, 7 - 10 September 1993, (edited by Graeme I. Pearman and James T. Peterson) (WMO TD No. 669).
97 89. 4th International Conference on CO2 (Carqueiranne, France, 13-17 September 1993) (WMO TD No. 561).
90. Global Atmospheric Background Monitoring for Selected Environmental Parameters GAW Data for 1992, Volume I: Atmospheric Aerosol Optical Depth (WMO TD No. 562).
91. Extended Abstracts of Papers Presented at the WMO Region VI Conference on the Measurement and Modelling of Atmospheric Composition Changes Including Pollution Transport, Sofia, 4 to 8 October 1993 (WMO TD No. 563).
92. Report of the Second WMO Meeting of Experts on the Quality Assurance/Science Activity Centres of the Global Atmosphere Watch, Garmisch-Partenkirchen, 7-11 December 1992 (WMO TD No. 580).
93. Report of the Third WMO Meeting of Experts on the Quality Assurance/Science Activity Centres of the Global Atmosphere Watch, Garmisch-Partenkirchen, 5-9 July 1993 (WMO TD No. 581).
94. Report on the Measurements of Atmospheric Turbidity in BAPMoN (WMO TD No. 603).
95. Report of the WMO Meeting of Experts on UV-B Measurements, Data Quality and Standardization of UV Indices, Les Diablerets, Switzerland, 25-28 July 1994 (WMO TD No. 625).
96. Global Atmospheric Background Monitoring for Selected Environmental Parameters WMO GAW Data for 1993, Volume I: Atmospheric Aerosol Optical Depth.
97. Quality Assurance Project Plan (QAPjP) for Continuous Ground Based Ozone Measurements (WMO TD No. 634).
98. Report of the WMO Meeting of Experts on Global Carbon Monoxide Measurements, Boulder, USA, 7-11 February 1994 (WMO TD No. 645).
99. Status of the WMO Global Atmosphere Watch Programme as at 31 December 1993 (WMO TD No. 636).
100. Report of the Workshop on UV-B for the Americas, Buenos Aires, Argentina, 22-26 August 1994.
101. Report of the WMO Workshop on the Measurement of Atmospheric Optical Depth and Turbidity, Silver Spring, USA, 6-10 December 1993, (edited by Bruce Hicks) (WMO TD No. 659).
102. Report of the Workshop on Precipitation Chemistry Laboratory Techniques, Hradec Kralove, Czech Republic, 17-21 October 1994 (WMO TD No. 658).
103. Report of the Meeting of Experts on the WMO World Data Centres, Toronto, Canada, 17-18 February 1995, (prepared by Edward Hare) (WMO TD No. 679).
104. Report of the Fourth WMO Meeting of Experts on the Quality Assurance/Science Activity Centres (QA/SACs) of the Global Atmosphere Watch, jointly held with the First Meeting of the Coordinating Committees of IGAC-GLONET and IGAC-ACE, Garmisch-Partenkirchen, Germany, 13 to 17 March 1995 (WMO TD No. 689).
98 105. Report of the Fourth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry (Garmisch, Germany, 6-11 March 1995) (WMO TD No. 718).
106. Report of the Global Acid Deposition Assessment (edited by D.M. Whelpdale and M-S. Kaiser) (WMO TD No. 777).
107. Extended Abstracts of Papers Presented at the WMO-IGAC Conference on the Measurement and Assessment of Atmospheric Composition Change (Beijing, China, 9-14 October 1995) (WMO TD No. 710).
108. Report of the Tenth WMO International Comparison of Dobson Spectrophotometers (Arosa, Switzerland, 24 July - 4 August 1995).
109. Report of an Expert Consultation on 85Kr and 222Rn: Measurements, Effects and Applications (Freiburg, Germany, 28-31 March 1995) (WMO TD No. 733).
110. Report of the WMO-NOAA Expert Meeting on GAW Data Acquisition and Archiving (Asheville, NC, USA, 4-8 November 1995) (WMO TD No. 755).
111. Report of the WMO-BMBF Workshop on VOC Establishment of a “World Calibration/Instrument Intercomparison Facility for VOC” to Serve the WMO Global Atmosphere Watch (GAW) Programme (Garmisch-Partenkirchen, Germany, 17-21 December 1995) (WMO TD No. 756).
112. Report of the WMO/STUK Intercomparison of Erythemally-Weighted Solar UV Radiometers, Spring/Summer 1995, Helsinki, Finland (WMO TD No. 781).
113. The Strategic Plan of the Global Atmosphere Watch (GAW) (WMO TD No. 802).
114. Report of the Fifth WMO Meeting of Experts on the Quality Assurance/Science Activity Centres (QA/SACs) of the Global Atmosphere Watch, jointly held with the Second Meeting of the Coordinating Committees of IGAC-GLONET and IGAC-ACEEd, Garmisch- Partenkirchen, Germany, 15-19 July 1996 (WMO TD No. 787).
115. Report of the Meeting of Experts on Atmospheric Urban Pollution and the Role of NMSs (Geneva, 7-11 October 1996) (WMO TD No. 801).
116. Expert Meeting on Chemistry of Aerosols, Clouds and Atmospheric Precipitation in the Former USSR (Saint Petersburg, Russian Federation, 13-15 November 1995).
117. Report and Proceedings of the Workshop on the Assessment of EMEP Activities Concerning Heavy Metals and Persistent Organic Pollutants and their Further Development (Moscow, Russian Federation, 24-26 September 1996) (Volumes I and II) (WMO TD No. 806).
118. Report of the International Workshops on Ozone Observation in Asia and the Pacific Region (IWOAP, IWOAP-II), (IWOAP, 27 February-26 March 1996 and IWOAP-II, 20 August-18 September 1996) (WMO TD No. 827).
119. Report on BoM/NOAA/WMO International Comparison of the Dobson Spectrophotometers (Perth Airport, Perth, Australia, 3-14 February 1997), (prepared by Robert Evans and James Easson) (WMO TD No. 828).
120. WMO-UMAP Workshop on Broad-Band UV Radiometers (Garmisch-Partenkirchen, Germany, 22 to 23 April 1996) (WMO TD No. 894).
99 121. Report of the Eighth WMO Meeting of Experts on Carbon Dioxide Concentration and Isotopic Measurement Techniques (prepared by Thomas Conway) (Boulder, CO, 6-11 July 1995) (WMO TD No. 821).
122. Report of Passive Samplers for Atmospheric Chemistry Measurements and their Role in GAW (prepared by Greg Carmichael) (WMO TD No. 829).
123. Report of WMO Meeting of Experts on GAW Regional Network in RA VI, Budapest, Hungary, 5 to 9 May 1997.
124. Fifth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry, (Geneva, Switzerland, 7-10 April 1997) (WMO TD No. 898)
125. Instruments to Measure Solar Ultraviolet Radiation, Part 1: Spectral Instruments (lead author G. Seckmeyer) (WMO TD No. 1066)
126. Guidelines for Site Quality Control of UV Monitoring (lead author A.R. Webb) (WMO TD No. 884).
127. Report of the WMO-WHO Meeting of Experts on Standardization of UV Indices and their Dissemination to the Public (Les Diablerets, Switzerland, 21-25 July 1997) (WMO TD No. 921).
128. The Fourth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and Data Reporting, (Rome, Italy, 22-25 September 1996) (WMO TD No. 918).
129. Guidelines for Atmospheric Trace Gas Data Management (Ken Masarie and Pieter Tans), 1998 (WMO TD No. 907).
130. Jülich Ozone Sonde Intercomparison Experiment (JOSIE, 5 February to 8 March 1996), (H.G.J. Smit and D. Kley) (WMO TD No. 926).
131. WMO Workshop on Regional Transboundary Smoke and Haze in Southeast Asia (Singapore, 2 to 5 June 1998) (Gregory R. Carmichael). Two volumes.
132. Report of the Ninth WMO Meeting of Experts on Carbon Dioxide Concentration and Related Tracer Measurement Techniques (Edited by Roger Francey), (Aspendale, Vic., Australia).
133. Workshop on Advanced Statistical Methods and their Application to Air Quality Data Sets (Helsinki, 14-18 September 1998) (WMO TD No. 956).
134. Guide on Sampling and Analysis Techniques for Chemical Constituents and Physical Properties in Air and Precipitation as Applied at Stations of the Global Atmosphere Watch. Carbon Dioxide (WMO TD No. 980).
135. Sixth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry (Zurich, Switzerland, 8-11 March 1999) (WMO TD No.1002).
136. WMO/EMEP/UNEP Workshop on Modelling of Atmospheric Transport and Deposition of Persistent Organic Pollutants and Heavy Metals (Geneva, Switzerland, 16-19 November 1999) (Volumes I and II) (WMO TD No. 1008).
137. Report and Proceedings of the WMO RA II/RA V GAW Workshop on Urban Environment (Beijing, China, 1-4 November 1999) (WMO-TD. 1014) (Prepared by Greg Carmichael).
100 138. Reports on WMO International Comparisons of Dobson Spectrophotometers, Parts I – Arosa, Switzerland, 19-31 July 1999, Part II – Buenos Aires, Argentina (29 Nov. – 12 Dec. 1999 and Part III – Pretoria, South Africa (18 March – 10 April 2000) (WMO TD No. 1016).
139. The Fifth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and Data Reporting (Halkidiki, Greece, September 1998)(WMO TD No. 1019).
140. WMO/CEOS Report on a Strategy for Integrating Satellite and Ground-based Observations of Ozone (WMO TD No. 1046).
141. Report of the LAP/COST/WMO Intercomparison of Erythemal Radiometers (Thessaloniki, Greece, 13-23 September 1999) (WMO TD No. 1051).
142. Strategy for the Implementation of the Global Atmosphere Watch Programme (2001-2007), A Contribution to the Implementation of the Long-Term Plan (WMO TD No.1077).
143. Global Atmosphere Watch Measurements Guide (WMO TD No. 1073).
144. Report of the Seventh Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry and the GAW 2001 Workshop (Geneva, Switzerland, 2 to 5 April 2001) (WMO TD No. 1104).
145. WMO GAW International Comparisons of Dobson Spectrophotometers at the Meteorological Observatory Hohenpeissenberg, Germany (21 May – 10 June 2000, MOHp2000-1), 23 July – 5 August 2000, MOHp2000-2), (10 – 23 June 2001, MOHp2001-1) and (8 to 21 July 2001, MOHp2001-2). Prepared by Ulf Köhler (WMO TD No. 1114).
146. Quality Assurance in monitoring solar ultraviolet radiation: the state of the art. (WMO TD No. 1180).
147. Workshop on GAW in RA VI (Europe), Riga, Latvia, 27-30 May 2002 (WMO TD No. 1206).
148. Report of the Eleventh WMO/IAEA Meeting of Experts on Carbon Dioxide Concentration and Related Tracer Measurement Techniques (Tokyo, Japan, 25-28 September 2001) (WMO TD No 1138).
149. Comparison of Total Ozone Measurements of Dobson and Brewer Spectrophotometers and Recommended Transfer Functions (prepared by J. Staehelin, J. Kerr, R. Evans and K. Vanicek) (WMO TD No. 1147).
150. Updated Guidelines for Atmospheric Trace Gas Data Management (Prepared by Ken Maserie and Pieter Tans (WMO TD No. 1149).
151. Report of the First CAS Working Group on Environmental Pollution and Atmospheric Chemistry (Geneva, Switzerland, 18-19 March 2003) (WMO TD No. 1181).
152. Current Activities of the Global Atmosphere Watch Programme (as presented at the 14th World Meteorological Congress, May 2003). (WMO TD No. 1168).
153. WMO/GAW Aerosol Measurement Procedures: Guidelines and Recommendations. (WMO TD No. 1178).
154. WMO/IMEP-15 Trace Elements in Water Laboratory Intercomparison. (WMO TD No. 1195).
101