Mapping terrestrial -dose rate in Europe based on routine monitoring data

Szegvary, T.; Conen, Franz; Stöhlker, U.; Dubois, Grégoire; Bossew, Peter; Vries, G. de

doi:10.1016/j.radmeas.2007.09.002

Cited by 55 publications

(48 citation statements)

References 19 publications

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“…We first tested the effect of the change of large scale transport using tagged simulations from 30 • × 30 • regions over Europe to determine the so called foot print or catchment area of the site. Enhanced emissions in southwestern Europe (Szegvary et al, 2007(Szegvary et al, , 2009 (Dörr and Münnich, 1990), consistent with the seasonality in modelled mismatch. This seasonality is thought to be driven by changes in soil moisture, which could also provide a mechanism for interannual changes in radon flux.…”

Section: Emissionssupporting

confidence: 70%

“…Various 222 Rn flux distributions have been proposed including an exhalation rate distribution based on multiple factors, such as radium content in the soil, grain size of the soil (Schery and Wasiolek, 1998) a flux distribution with a decrease with latitude north of 30 • N (Connen and Robertson, 2002), and a spatially and temporally resolved exhalation rate map over Europe using gamma dose rate (Szegvary et al, 2007(Szegvary et al, , 2009. A flux distribution over ocean was estimated using radium content in the sea-water and wind speed dependency of the gas transfer velocity between air and the sea (Schery and Huang, 2004).…”

Section: Introductionmentioning

confidence: 99%

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TransCom continuous experiment: comparison of 222Rn transport at hourly time scales at three stations in Germany

et al. 2011

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Abstract. Fourteen global atmospheric transport models were evaluated by comparing the simulation of 222 Rn against measurements at three continental stations in Germany: Heidelberg, Freiburg and Schauinsland. Hourly concentrations simulated by the models using a common 222 Rn-flux without temporal variations were investigated for 2002 and 2003. We found that the mean simulated concentrations in Heidelberg are related to the diurnal amplitude of boundary layer height in each model. Summer mean concentrations simulated by individual models were negatively correlated with the seasonal mean of diurnal amplitude of boundary layer height, while in winter the correlation was positive. We also found that the correlations between simulated and measured concentrations at Schauinsland were higher when the simulated concentrations were interpolated to the station altitude in most models. Temporal variations of the mismatch between simulated and measured concentrations suggest that there are significant interannual variations in the 222 Rn exhalation rate in this region. We found that the local inversion layer during daytime in summer in Freiburg has a significant effect on 222 Rn concentrations. We recommend Freiburg concentrations for validation of models that resolve local stable layers and those at Heidelberg for models without this capability.

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Section: Emissionssupporting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

TransCom continuous experiment: comparison of 222Rn transport at hourly time scales at three stations in Germany

et al. 2011

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“…Probe related information provided by the network operators to AIRDOS is derived from the results of the EURADOS inter-comparison exercises and the Schauinsland inter-calibration site. Szegvary [13] applied corrections to the EURDEP data based on the AIRDOS: self-effect-corrections, correction of the cosmic radiation with empirical functions depending on the altitude asl; subtraction of the artificial radiation (mostly derived from the Chernobyl accident 1986); geometry of the measurement (e.g. height above ground).…”

Section: Adjusting Network For the Validation Of Climate Modelsmentioning

confidence: 99%

“…Where applicable, an artificial component from 137 Cs was subtracted based on data in de Cort et al [1]. Kriging methods developed within INTAMAP project are used for spatial interpolation between monitoring stations provided European maps of terrestrial GDR [13], which have then been transformed in 222 Rn flux maps for use in atmospheric transport applications using the empirical relation between terrestrial GDR and 222 Rn flux described in Szegvary et al [5]. These maps are available at http://radon.unibas.ch/.…”

Section: Adjusting Network For the Validation Of Climate Modelsmentioning

confidence: 99%

Inter-calibration of gamma dose rate detectors on the European scale

et al. 2009

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Abstract.A project to compare the response of different detector types was started in 1996 at the Schauinsland mountain (1200 m above sea level) close to Freiburg, Germany, where the German office for radiation protection (BfS) runs a trace analysis laboratory since about 50 years. The aim of this inter-calibration experiment is to compare different gamma dose rate detector types over long periods and under rather unfavorable climatic conditions. This allows to characterise different probe types under environmental conditions and it complements the EURADOS inter-comparison exercises, which a carried out every 2 to 3 years. Both projects dealing with the harmonization of gamma dose rate data in the EU are used to derive terrestrial dose rate from the raw data. Using interpolation techniques provided by INTAMAP seasonal maps of the terrestrial dose rate could be generated. It is shown, that this information can be used for the calibration of satellite based soil moisture methods as well for the calculation of radon emission maps on the European scale, which are of interest for the research community, since Radon is used as a passive tracer in atmospheric research to examine transport processes on synoptic time scales.

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“…We combine the emissions from an improved version of the high-resolution emission model of the (Szegvary et al, 2007), with the Stochastic Time-Inverted Lagrangian Transport (STILT) model transport Bringing together results from different research communities, this study especially aims at illustrating how combining information from different fields, i.e. emissions estimates, regional modelling and observations, including tracers for source apportionment or atmospheric mixing, can increase our understanding of the future challenges that will have to be jointly addressed by the different research communities.…”

Section: Introductionmentioning

confidence: 99%

Can we evaluate a fine-grained emission model using high-resolution atmospheric transport modelling and regional fossil fuel CO2 observations?

Vogel¹,

Tiruchittampalam²,

Theloke³

et al. 2013

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Quantifying carbon dioxide emissions from fossil fuel burning (FFCO 2 ) is a crucial task to assess continental carbon fluxes and to track anthropogenic emissions changes in the future. In the present study, we investigate potentials and challenges when combining observational data with simulations using high-resolution atmospheric transport and emission modelling. These challenges concern, for example, erroneous vertical mixing or uncertainties in the disaggregation of national total emissions to higher spatial and temporal resolution. In our study, the hourly regional fossil fuel CO 2 offset (DFFCO 2 ) is simulated by transporting emissions from a 5 min)5 min emission model (IER2005) that provides FFCO 2 emissions from different emission categories. Our Lagrangian particle dispersion model (STILT) is driven by 25 km)25 km meteorological data from the European Center for Medium-Range Weather Forecast (ECMWF). We evaluate this modelling framework (STILT/ECMWF ' IER2005) for the year 2005 using hourly DFFCO 2 estimates derived from 14 C, CO and 222 Radon ( 222 Rn) observations at an urban site in south-western Germany (Heidelberg). Analysing the mean diurnal cycles of DFFCO 2 for different seasons, we find that the large seasonal and diurnal variation of emission factors used in the bottom-up emission model (spanning one order of magnitude) are adequate. Furthermore, we show that the use of 222 Rn as an independent tracer helps to overcome problems in timing as well as strength of the vertical mixing in the transport model. By applying this variability correction, the model-observation agreement is significantly improved for simulated DFFCO 2 . We found a significant overestimation of DFFCO 2 concentrations during situations where the air masses predominantly originate from densely populated areas. This is most likely caused by the spatial disaggregation methodology for the residential emissions, which to some extent relies on a constant per capita-based distribution. In the case of domestic heating emissions, this does not appear to be sufficient.

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Mapping terrestrial -dose rate in Europe based on routine monitoring data

Cited by 55 publications

References 19 publications

TransCom continuous experiment: comparison of <sup>222</sup>Rn transport at hourly time scales at three stations in Germany

TransCom continuous experiment: comparison of <sup>222</sup>Rn transport at hourly time scales at three stations in Germany

Inter-calibration of gamma dose rate detectors on the European scale

Can we evaluate a fine-grained emission model using high-resolution atmospheric transport modelling and regional fossil fuel CO<sub>2</sub> observations?

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Mapping terrestrial -dose rate in Europe based on routine monitoring data

Cited by 55 publications

References 19 publications

TransCom continuous experiment: comparison of &lt;sup&gt;222&lt;/sup&gt;Rn transport at hourly time scales at three stations in Germany

TransCom continuous experiment: comparison of &lt;sup&gt;222&lt;/sup&gt;Rn transport at hourly time scales at three stations in Germany

Inter-calibration of gamma dose rate detectors on the European scale

Can we evaluate a fine-grained emission model using high-resolution atmospheric transport modelling and regional fossil fuel CO<sub>2</sub> observations?

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TransCom continuous experiment: comparison of <sup>222</sup>Rn transport at hourly time scales at three stations in Germany

TransCom continuous experiment: comparison of <sup>222</sup>Rn transport at hourly time scales at three stations in Germany