Lorenz Curve and Gini Coefficient: Novel tools for analysing seasonal variation of environmental radon gas

Groves-Kirkby, Chris J; Denman, Anthony R; Phillips, Paul S

doi:10.1016/j.jenvman.2009.01.003

Cited by 58 publications

(20 citation statements)

References 38 publications

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“…Correspondence to: C. J. Groves-Kirkby (chris.groves-kirkby@northampton.ac.uk) concentration may therefore be expected to vary with location, and this is found to be the case (Groves-Kirkby et al, 2009).…”

Section: Introductionmentioning

confidence: 96%

Comparison of seasonal variability in European domestic radon measurements

Groves-Kirkby

Denman

Phillips

et al. 2010

Nat. Hazards Earth Syst. Sci.

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Abstract. Analysis of published data characterising seasonal variability of domestic radon concentrations in Europe and elsewhere shows significant variability between different countries and between regions where regional data is available. Comparison is facilitated by application of the Gini Coefficient methodology to reported seasonal variation data. Overall, radon-rich sedimentary strata, particularly high-porosity limestones, exhibit high seasonal variation, while radon-rich igneous lithologies demonstrate relatively constant, but somewhat higher, radon concentrations. Highvariability regions include the Pennines and South Downs in England, Languedoc and Brittany in France, and especially Switzerland. Low-variability high-radon regions include the granite-rich Cornwall/Devon peninsula in England, and Auvergne and Ardennes in France, all components of the Devonian-Carboniferous Hercynian belt.

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Section: Introductionmentioning

confidence: 96%

Comparison of seasonal variability in European domestic radon measurements

Groves-Kirkby

Denman

Phillips

et al. 2010

Nat. Hazards Earth Syst. Sci.

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“…It is defined as the ratio of the area between the line of equal distribution and the observed Lorenz Curve to the area under the uniform distribution, and has values within the range 0 (perfectly uniform distribution) to 1 (complete in equality) [28].So this index is used to quantitate the recovery dif ference between each permeability strip under various drawdown pressures. Figure 3 shows the recovery degree and Gini coefficient curve of oil viscosities under different drawdown pressures.…”

Section: The Variation Of Oil Recovery Of Constant Pressuresmentioning

confidence: 99%

Experimental Study of Reasonable Drawdown Pressure of Horizontal Wells in Oil Reservoir With Bottom Water

Liu

Zheng

et al. 2014

Journal of Energy Resources Technology

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For the development o f oil reservoir with bottom water, it is sig nificant to analyze the impact o f drawdown pressures on post water breakthrough performance of horizontal wells. Based on a small-scale and discretized physical simulation system, the impact of different drawdown pressures and the influence o f changing drawdown pressures in different water cut stage have been dis cussed. The results show that for thin oil with relatively high vis cosity (87.8 mPa.s), keeping a relatively large drawdown pressure in medium and low water cut stage is reasonable. But enlarging drawdown pressure in high water cut stage is harmful to increase ultimate oil recovery. For oil with further lower viscosity (21.4 mPa.s), adopting a small drawdown pressure and increasing it in medium and high water cut stage is reasonable. For the heavy oil (124.1 mPa.s), it is acceptable to enlarge drawdown pressure under the condition o f low water cut period.

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“…Also the model parameters may (and probably will) be regionally different e this has not yet been investigated systematically, to our knowledge. Moreover, regional differences can strongly affect the measurements taken at the same time at different places, and the Rn seasonality in one particular building can deviate considerably from the average one (e. g., Bossew and Lettner, 2007;Groves-Kirkby et al, 2009). Seasonal variations are consequently sometimes disregarded, although these can have a significant impact, resulting in additional uncertainty of the estimates, if regarded as estimates of the annual mean.…”

Section: Various Physical Sources Of Uncertaintymentioning

confidence: 99%