Percentage saturation of whole human blood from subjects S1 and S2 with various noble gases and noble-gas isotope ratios under different environmental conditions (see Table 3 for details).

<p>The agreement between the measurements conducted on the two subjects demonstrates that the methods yield reproducible results.</p

Noble-gas concentrations, noble-gas isotope ratios and standard errors (at the 1σ level) measured in blood samples from two subjects (S1 and S2). ASW (S1) = noble-gas concentrations in air-saturated water at a temperature of 36.5°C, a salinity of 9 g/kg and an altitude of 225 m above sea level (corresponding to an atmospheric pressure of 986.3 hPa).

<p>ASW (S2)  =  noble-gas concentrations in air-saturated water at a temperature of 37.5°C, a salinity of 9 g/kg and an altitude of 490 m above sea level (corresponding to an atmospheric pressure of 955.5 hPa). STP  =  standard temperature (0°C) and pressure (1 atm = 1013.25 hPa).</p

Noble-gas partition coefficients between whole blood and air as determined in this study for two subjects (S1 and S2) compared with values from the relevant literature.

<p>The partition coefficients are expressed as nondimensional ratios of the gas concentration in blood (in cm³_STP of gas per cm³ of whole blood, assuming a whole blood density of 1.06 g/cm³, where 1 cm³_STP = 22414⁻¹ Mol) to the corresponding volume fraction of the gas in dry air (in vol/vol).</p>a<p>Based on the linear relationship between hematocrit and partition coefficient in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096972#pone.0096972-Hardewig1" target="_blank">[23]</a>.</p>b<p>Calculated using a linear relationship between the partition coefficients of red blood cells (40%) and plasma (60%).</p>c<p>Coefficients as calculated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096972#pone.0096972-Goto1" target="_blank">[22]</a>.</p>d<p>Errors represent the standard deviations of the original measurements.</p

Noble-gas partition coefficients between blood plasma and red blood cells as determined in this study for one subject (S1) compared with values from the relevant literature.

<p>The partition coefficients are expressed as nondimensional ratios of the gas concentration in the plasma (in cm³_STP of gas per cm³ of plasma, with an assumed plasma density of 1.025 g/cm³) to the gas concentration in the red blood cells (in cm³_STP of gas per cm³ of red blood cells, with an assumed red blood cell density of 1.125 g/cm³). Note that the values listed are based on the separation of the two phases in a single sample only and cannot therefore be considered as generally representative.</p>a<p>Measurement error for red blood cells estimated from the maximum deviation from a linear interpolation <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096972#pone.0096972-Hardewig1" target="_blank">[23]</a>.</p>b<p>Calculated using a linear relationship between the partition coefficients of red blood cells (44%) and plasma (56%).</p

Acquisition and preparation of a blood sample for noble-gas analysis.

<p>Whole blood in injected from a syringe through a hypodermic needle into a copper tube held vertically (Steps 1–2). After closing the sample with two special metal clamps (Step 3), the copper tube is cleaned (Step 4) and centrifuged at 2300 rpm in a centrifuge with a swing-out rotor (Step 5). After centrifugation, the plasma and red blood cells are separated using a third clamp (Step 6).</p

Percentage saturation of human blood plasma (white), red blood cells (black) and whole blood (gray) with noble gases relative to air-saturated water (at a temperature of 36.5°C and a salinity of 9 g/kg at an altitude of 225 m a.s.l.) measured in the sample from subject S1.

<p>For red blood cells, the saturation increases with the atomic mass of the noble gas.</p

Temporal and spatial scales of water temperature variability as an indicator for mixing in a polymictic lake

<p>We applied coarse spectral analysis to more than 2 decades of daily near-surface water temperature (WT) measurements from Müggelsee, a shallow polymictic lake in Germany, to systematically characterize patterns in WT variability from daily to yearly temporal scales. Comparison of WT with local air temperature indicates that the WT variability patterns are likely attributable to both meteorological forcing and internal lake dynamics. We identified seasonal patterns of WT variability and showed that WT variability increases with increasing Schmidt stability, decreasing Lake number and decreasing ice cover duration, and is higher near the shore than in open water. We introduced the slope of WT spectra as an indicator for the degree of lake mixing to help explain the identified temporal and spatial scales of WT variability. The explanatory power of this indicator in other lakes with different mixing regimes remains to be established.</p

Temporal variability in near-surface lake water temperature.

<p>(a) Seasonal variability in the diel temperature range for 96 Northern Hemisphere lakes with 95% confidence intervals (note that not all lakes had data for the whole year). (b) Individually normalized (zero-mean) summer average diel cycle for the lakes that had the highest (red) and lowest (blue) 10% of diel temperature ranges measured. The bold lines represent the mean diel cycle for the 10% considered and the horizontal black line indicates zero. For clarity, we excluded Jekl Bog, which had the highest diel cycle, from this figure. (c) Example of hourly-resolution near-surface lake water temperature variation at Jekl Bog (surface area 2.5 x 10³ m², red), and Sparkling Lake (surface area 6.2 x 10⁵ m², blue), both situated in Wisconsin, USA.</p

First derivatives of the fitted generalised additive model.

<p>The red line indicates those parts of the model fit that are statistically significantly changing and the shaded region shows the 95% confidence intervals.</p

Relationship between the diel range in lake surface water temperature and surface area.

<p>Relationship between the observed (light violet circles) and theoretical (red circles) diel surface temperature range with lake area during summer, with the solid line illustrating the fitted generalised additive model with 95% confidence interval shown by the shaded region; lake surface areas where the diel temperature range changes significantly (P < 0.001) are shown with a red line.</p