scholarly journals A European-wide <sup>222</sup>Radon and <sup>222</sup>Radon progeny comparison study

2016 ◽  
Author(s):  
Dominik Schmithüsen ◽  
Scott Chambers ◽  
Bernd Fischer ◽  
Stefan Gilge ◽  
Juha Hatakka ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Ground Level ◽  
Data Sets ◽  
Correction Factors ◽  
Comparison Study ◽  
Data Set ◽  
Parallel Data ◽  
Linear Regressions ◽  
Atmospheric Transport Model

Abstract. A European-wide 222Radon/222Radon progeny comparison study has been conducted in order to determine correction factors that could be applied to existing atmospheric 222Radon data sets for quantitative use of this tracer in atmospheric transport model validation. Two compact and easy-to-transport Heidelberg Radon Monitors (HRM) were moved around to run for at least one month at each of the nine European measurement stations that were included in the comparison. Linear regressions between parallel data sets were calculated, yielding correction factors relative to the HRM ranging from 0.68 to 1.45. A calibration bias between ANSTO (Australian Nuclear Science and Technology Organisation) two-filter radon monitors and the HRM of ANSTO/HRM = 1.11 ± 0.05 was found. For continental stations, which use one-filter systems, preliminary 214Po/222Rn disequilibrium values were estimated to lie between 0.8 at mountain stations (e.g. Schauinsland) and 0.9 at non-mountain sites for sampling heights around 20 to 30 m above ground level. Respective corrections need to be applied to obtain a consistent European 222Radon data set for further applications.

scholarly journals A European-wide <sup>222</sup>radon and <sup>222</sup>radon progeny comparison study

2017 ◽  
Vol 10 (4) ◽  
pp. 1299-1312 ◽  
Author(s):  
Dominik Schmithüsen ◽  
Scott Chambers ◽  
Bernd Fischer ◽  
Stefan Gilge ◽  
Juha Hatakka ◽  
...  
Keyword(s):  
Ground Level ◽  
Trace Gas ◽  
Data Sets ◽  
Correction Factors ◽  
Comparison Study ◽  
Data Set ◽  
Measurement Systems ◽  
Activity Concentrations ◽  
Parallel Data ◽  
Systematic Biases

Abstract. Although atmospheric 222radon (222Rn) activity concentration measurements are currently performed worldwide, they are being made by many different laboratories and with fundamentally different measurement principles, so compatibility issues can limit their utility for regional-to-global applications. Consequently, we conducted a European-wide 222Rn ∕ 222Rn progeny comparison study in order to evaluate the different measurement systems in use, determine potential systematic biases between them, and estimate correction factors that could be applied to harmonize data for their use as a tracer in atmospheric applications. Two compact portable Heidelberg radon monitors (HRM) were moved around to run for at least 1 month at each of the nine European measurement stations included in this comparison. Linear regressions between parallel data sets were calculated, yielding correction factors relative to the HRM ranging from 0.68 to 1.45. A calibration bias between ANSTO (Australian Nuclear Science and Technology Organisation) two-filter radon monitors and the HRM of ANSTO ∕ HRM  =  1.11 ± 0.05 was found. Moreover, for the continental stations using one-filter systems that derive atmospheric 222Rn activity concentrations from measured atmospheric progeny activity concentrations, preliminary 214Po ∕ 222Rn disequilibrium values were also estimated. Mean station-specific disequilibrium values between 0.8 at mountain sites (e.g. Schauinsland) and 0.9 at non-mountain sites for sampling heights around 20 to 30 m above ground level were determined. The respective corrections for calibration biases and disequilibrium derived in this study need to be applied to obtain a compatible European atmospheric 222Rn data set for use in quantitative applications, such as regional model intercomparison and validation or trace gas flux estimates with the radon tracer method.

A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

2005 ◽  
Author(s):  
Jungeui Hong ◽  
Elizabeth A. Cudney ◽  
Genichi Taguchi ◽  
Rajesh Jugulum ◽  
Kioumars Paryani ◽  
...  
Keyword(s):  
Neural Network ◽  
Small Data ◽  
Data Sets ◽  
Comparison Study ◽  
Data Set ◽  
Set Size ◽  
Breast Cancer Study ◽  
Discriminant Ability ◽  
Small Data Sets ◽  
Multivariate Pattern

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis-Taguchi System and a neural network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.

scholarly journals Inverse modelling of CF<sub>4</sub> and NF<sub>3</sub> emissions in East Asia

2018 ◽  
Vol 18 (18) ◽  
pp. 13305-13320 ◽  
Author(s):  
Tim Arnold ◽  
Alistair J. Manning ◽  
Jooil Kim ◽  
Shanlan Li ◽  
Helen Webster ◽  
...  
Keyword(s):  
South Korea ◽  
East Asia ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Atmospheric Gases ◽  
Atmospheric Measurements ◽  
Small Uncertainty ◽  
Measurement Location ◽  
Atmospheric Transport Model ◽  
Good Agreement

Abstract. Decadal trends in the atmospheric abundances of carbon tetrafluoride (CF4) and nitrogen trifluoride (NF3) have been well characterised and have provided a time series of global total emissions. Information on locations of emissions contributing to the global total, however, is currently poor. We use a unique set of measurements between 2008 and 2015 from the Gosan station, Jeju Island, South Korea (part of the Advanced Global Atmospheric Gases Experiment network), together with an atmospheric transport model, to make spatially disaggregated emission estimates of these gases in East Asia. Due to the poor availability of good prior information for this study, our emission estimates are largely influenced by the atmospheric measurements. Notably, we are able to highlight emission hotspots of NF3 and CF4 in South Korea due to the measurement location. We calculate emissions of CF4 to be quite constant between the years 2008 and 2015 for both China and South Korea, with 2015 emissions calculated at 4.3±2.7 and 0.36±0.11 Gg yr−1, respectively. Emission estimates of NF3 from South Korea could be made with relatively small uncertainty at 0.6±0.07 Gg yr−1 in 2015, which equates to ∼1.6 % of the country's CO2 emissions. We also apply our method to calculate emissions of CHF3 (HFC-23) between 2008 and 2012, for which our results find good agreement with other studies and which helps support our choice in methodology for CF4 and NF3.

scholarly journals The Atmospheric Carbon and Transport (ACT) – America Mission

2021 ◽  
pp. 1-54
Author(s):  
Kenneth J. Davis ◽  
Edward V. Browell ◽  
Sha Feng ◽  
Thomas Lauvaux ◽  
Michael D. Obland ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Eastern United States ◽  
State Variables ◽  
Data Set ◽  
Spatial Gradients ◽  
Research Aircraft ◽  
In Situ Sensors ◽  
Atmospheric Carbon ◽  
Model Ensembles

AbstractThe Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five, six-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America data set and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise sub-continental GHG flux estimates.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM-MACH-GHG v.137-reg

2019 ◽  
Author(s):  
Jinwoong Kim ◽  
Saroja Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Chemical Transport Model ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high spatio-temporal resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km × 10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations, based on comparisons to surface and aircraft observations. In addition, reduced bias and standard deviation of forecast error in boreal summer are obtained by the regional model. Better representation of model topography in the regional model reduces transport and representation errors significantly compared to the global model, especially in regions of complex topography, as revealed by the more precise and detailed structure of the CO2 diurnal cycle produced at observation sites and in model space. The new regional model will form the basis of a flux inversion system that estimates regional scale fluxes of GHGs over Canada.

scholarly journals Atmospheric Transport Towards the Iberian Peninsula in the 3- to 10-Day Range

2006 ◽  
Vol 6 ◽  
pp. 1041-1047 ◽  
Author(s):  
Raquel Nieto ◽  
Luis Gimeno
Keyword(s):  
North America ◽  
Iberian Peninsula ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Day Range ◽  
Local Sources ◽  
Main Pathway ◽  
Potential Contributor ◽  
Atmospheric Transport Model

An advanced Lagrangian atmospheric transport model (FLEXTRAP) was used to identify the possible sources of middle-lived pollutants over the Iberian Peninsula. A period of 4 years, 2000—2003, was analyzed. Transatlantic transport is the main pathway of the air reaching the Iberian Peninsula in the studied range of 3—10 days; local sources are limited to 3 days of transport. The presence of North America as a source from days 6—10 of transport identifies this region as the main potential contributor to the middle-lived pollutants over the Iberian Peninsula.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM–MACH–GHG v.137-reg

2020 ◽  
Vol 13 (1) ◽  
pp. 269-295
Author(s):  
Jinwoong Kim ◽  
Saroja M. Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Spatiotemporal Resolution ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high-spatiotemporal-resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km×10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower-resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate the high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations based on comparisons to surface and aircraft observations. In addition, the bias and standard deviation of forecast error in boreal summer are reduced by the regional model. Better representation of model topography in the regional model results in improved simulation of the CO2 diurnal cycle compared to the global model at Walnut Grove, California. The new regional model will form the basis of a flux inversion system that estimates regional-scale fluxes of GHGs over Canada.

scholarly journals Spatiotemporal patterns of the fossil-fuel CO<sub>2</sub> signal in central Europe: Results from a high-resolution atmospheric transport model

2017 ◽  
Author(s):  
Yu Liu ◽  
Nicolas Gruber ◽  
Dominik Brunner
Keyword(s):  
High Resolution ◽  
Central Europe ◽  
Western Europe ◽  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Variations ◽  
Atmospheric Co2 ◽  
Fuel Component ◽  
Atmospheric Transport Model

Abstract. The emission of CO2 from the burning of fossil fuel is a prime determinant of variations in atmospheric CO2. Here, we simulate this fossil fuel signal together with the natural and background components with a regional high-resolution atmospheric transport model for central and southern Europe considering separately the emissions from different sectors and countries on the basis of emission inventories and hourly emission time functions. The simulated variations in atmospheric CO2 agree very well with observation-based estimates, although the observed variance is slightly underestimated, particularly for the fossil fuel component. Despite relatively rapid atmospheric mixing, the simulated fossil fuel signal reveals distinct annual mean structures deep into the troposphere reflecting the spatially dense aggregation of most emissions. The fossil fuel signal accounts for more than half of the total (fossil fuel + biospheric + background) temporal variations in atmospheric CO2 in most areas of northern and western central Europe, with the largest variations occurring on diurnal timescales owing to the combination of diurnal variations in emissions and atmospheric mixing/transport out of the surface layer. Their co-variance leads to a fossil-fuel diurnal rectifier effect with a magnitude as large as 9 ppm compared to a case with time-constant emissions. The spatial pattern of CO2 from the different sectors largely reflects the distribution and relative magnitude of the corresponding emissions, with power plant emissions leaving the most distinguished mark. An exception is southern and western Europe, where the emissions from the transportation sector dominate the fossil fuel signal. Most of the fossil fuel CO2 remains within the country responsible for the emission, although in smaller countries, up to 80 % of the fossil fuel signal can come from abroad. A fossil fuel emission reduction of 30 % is clearly detectable for a surface-based observing system for atmospheric CO2, while it is beyond the edge of detectability for the current generation of satellites with the exception of a few hotspot sites. Changes in variability in atmospheric CO2 might open an additional door for the monitoring and verification of changes in fossil fuel emissions, primarily for surface based systems.

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