Radon flux maps for the Netherlands and Europe using terrestrial gamma radiation derived from soil radionuclides

Manohar, Swagath Navin; Meijer, H. A. J.; Herber, M.A.

doi:10.1016/j.atmosenv.2013.09.005

Cited by 41 publications

(21 citation statements)

References 32 publications

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“…2.2.2. The mean value of (0.63 ± 0.04) atoms cm −2 s −1 (n = 422) compares very well with the results from the modelling work by Manohar et al (2013), who reported a mean value of (0.65 ± 0.14) atoms cm −2 s −1 . The results from the process-based model (Karstens et al, 2015a) are in the same range of (0.59 ± 0.18) atoms cm −2 s −1 .…”

Section: Cbwsupporting

confidence: 80%

“…Our mean result, even after discounting the 11 high values, is a factor of 2 higher than the mean value of (0.16 ± 0.01) atoms cm −2 s −1 based on soil chamber measurements (Manohar et al, 2016) and also higher than the model-based estimate of (0.19 ± 0.12) atoms cm −2 s −1 found by Manohar et al (2013). The measurements from the soil chamber and our SPOT-EC method agree well for the majority of the events, but the higher values are not captured by the chamber method.…”

Section: Lutcontrasting

confidence: 37%

“…dropping from 100 % to almost zero emission) within hours, e.g. due to rainfall (Manohar et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Inferring 222Rn soil fluxes from ambient 222Rn activity and eddy covariance measurements of CO2

et al. 2016

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Abstract. We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222 Rn from tower-based observations of 222 Rn activity concentration, CO 2 mole fractions and direct CO 2 flux measurements from eddy covariance. For specific events, the regional ( 222 Rn) surface flux is calculated from short-term changes in ambient ( 222 Rn) activity concentration scaled by the ratio of the mean CO 2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222 Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longerterm (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222 Rn surface flux of (0.29 ± 0.02) atoms cm −2 s −1 with values > 0.5 atoms cm −2 s −1 to the south and southeast. For CBW we estimated a mean 222 Rn surface flux of (0.63 ± 0.04) atoms cm −2 s −1 . The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222 Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222 Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222 Rn surface fluxes. Practical applications furthermore include calibration of process-based 222 Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222 Rntracer method.

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Section: Cbwsupporting

confidence: 80%

Section: Lutcontrasting

confidence: 37%

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Inferring 222Rn soil fluxes from ambient 222Rn activity and eddy covariance measurements of CO2

et al. 2016

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“…A partial explanation could be higher radon emissions south-east of the Alps, which are reported by López-Coto et al (2013). But emissions are similar across the Alps in the results of Szegvary et al (2009) and Manohar et al (2013). Furthermore, near-surface radon concentrations in Milan (Sesana et al, 2003) and northern Italy (Galmarini, 2006) are similar to our measurements from Bern, making this explanation doubtful.…”

Section: Characteristics Of the Radon Distributioncontrasting

confidence: 54%

Surface-to-mountaintop transport characterised by radon observations at the Jungfraujoch

et al. 2014

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Abstract. Atmospheric composition measurements at Jungfraujoch are affected intermittently by boundary-layer air which is brought to the station by processes including thermally driven (anabatic) mountain winds. Using observations of radon-222, and a new objective analysis method, we quantify the land-surface influence at Jungfraujoch hour by hour and detect the presence of anabatic winds on a daily basis. During 2010-2011, anabatic winds occurred on 40 % of days, but only from April to September. Anabatic wind days were associated with warmer air temperatures over a large fraction of Europe and with a shift in air-mass properties, even when comparing days with a similar mean radon concentration. Excluding days with anabatic winds, however, did not lead to a better definition of the unperturbed aerosol background than a definition based on radon alone. This implies that a radon threshold reliably excludes local influences from both anabatic and non-anabatic vertical-transport processes.

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“…As water has 1.11 times as many electrons per gram compared to most soils, water is 1.11 times as effective in attenuating gamma-radiation compared to typical soils (Grasty, 1997). The expected high sensitivity of gamma spectroscopy to soil water content has triggered numerous studies which addressed a broad range of applications including soil classification (Beamish, 2013(Beamish, , 2014, radon flux mapping (Manohar et al, 2013;Szegvary et al, 2007) and snow water equivalent assessment (Carroll and Carroll, 1989;Peck and Bissell, 1973). Nevertheless, the potentialities of the method for monitoring soil moisture dynamics have been not fully explored yet (Bogena et al, 2015;Pereira, 2011), especially in the field of proximal sensing, which is foreseen to be an efficient strategy for filling the existing gap between punctual measurements, generally provided by in situ electromagnetic sensors (Walker et al, 2004), and remote measurements, typically performed by satellites (Brocca et al, 2017;Zeng et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy

Baldoncini

Albéri

Bottardi

et al. 2018

Journal of Environmental Radioactivity

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Radon flux maps for the Netherlands and Europe using terrestrial gamma radiation derived from soil radionuclides

Cited by 41 publications

References 32 publications

Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

Surface-to-mountaintop transport characterised by radon observations at the Jungfraujoch

Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy

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Radon flux maps for the Netherlands and Europe using terrestrial gamma radiation derived from soil radionuclides

Cited by 41 publications

References 32 publications

Inferring &lt;sup&gt;222&lt;/sup&gt;Rn soil fluxes from ambient &lt;sup&gt;222&lt;/sup&gt;Rn activity and eddy covariance measurements of CO&lt;sub&gt;2&lt;/sub&gt;

Inferring &lt;sup&gt;222&lt;/sup&gt;Rn soil fluxes from ambient &lt;sup&gt;222&lt;/sup&gt;Rn activity and eddy covariance measurements of CO&lt;sub&gt;2&lt;/sub&gt;

Surface-to-mountaintop transport characterised by radon observations at the Jungfraujoch

Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy

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Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>

Inferring <sup>222</sup>Rn soil fluxes from ambient <sup>222</sup>Rn activity and eddy covariance measurements of CO<sub>2</sub>