Empirical Calibration Research Articles

A Rapid Method to Noninvasively Measure the Viscoelastic Properties of Synthetic Polymers Using Mechanical Vibrations and Photonics

Noninvasive measurement of the viscoelastic properties of both natural and synthetic polymers is important for the analysis of implant design and performance as well as in industrial material development. In this study, we used vibrational optical coherence tomography (VOCT) to compare the elastic and viscoelastic properties of silicone polymers with standard tensile stress–strain measurements. VOCT uses acoustic vibrations and infrared light to measure the resonant frequency of viscoelastic materials. The elastic modulus was calculated from the in-phase deformation of the material at fixed frequencies using an empirical calibration curve. Viscous loss was measured after pulsing the samples based on the ratio of mechanovibrational peak widths to heights. The results showed that the optimal cure time and modulus values obtained using VOCT were like those obtained using conventional tensile testing. VOCT could capture results that were comparable to conventional testing while not destroying the material, suggesting its usefulness for in vivo and in situ measurements as well as for early quality control environments during end-use application and fabrication experiments. We conclude that VOCT is a new technique that is comparable to conventional testing for noninvasively and nondestructively measuring the viscoelastic properties of polymers.

Data-Driven Calibration Algorithm and Pre-Launch Performance Simulations for the SWOT Mission

The Surface Water and Ocean Topography (SWOT) mission will be affected by various sources of systematic errors, which are correlated in space and in time. Their amplitude before calibration might be as large as tens of centimeters, i.e., able to dominate the mission error budget. To reduce their magnitude, we developed so-called data-driven (or empirical) calibration algorithms. This paper provided a summary of the overall problem, and then presented the calibration framework used for SWOT, as well as the pre-launch performance simulations. We presented two complete algorithm sequences that use ocean measurements to calibrate KaRIN globally. The simple and robust Level-2 algorithm was implemented in the ground segment to control the main source of error of SWOT’s hydrology products. In contrast, the more sophisticated Level-3 (multi-mission) algorithm was developed to improve the accuracy of ocean products, as well as the one-day orbit of the SWOT mission. The Level-2 algorithm yielded a mean inland error of 3–6 cm, i.e., a margin of 25–80% (of the signal variance) with respect to the error budget requirements. The Level-3 algorithm yielded ocean residuals of 1 cm, i.e., a variance reduction of 60–80% with respect to the Level-2 algorithm.

Improvement of suspension-assisted total reflection X-ray fluorescence analysis of ores using wet grinding and empirical calibrations

In this study, the suspension-assisted total-reflection X-ray fluorescence analysis of ores was improved using the wet grinding procedure to produce ultra-fine suspended powder mixed with internal standard solution in aqueous media. The advantages of the proposed technique were demonstrated by the example of the determination of S, Fe, Ni, and Cu in sulfide copper‑nickel ores containing various ratios of sulfide and silicate minerals. We showed that the powerful mixing of 100 mg of ore powder and 4 mL of ultra-pure water as a dispersing medium with 20 g of grinding balls of 1 mm in diameter leads to the preparation of homogeneous suspension with monomodal particle size distribution having 90% of the particle size <6 μm. The suspension after wet grinding was diluted up to 50 mL with ultra-pure water to obtain a final concentration of the suspended powder of 2 mg/mL. Relative precision of the described sample preparation technique calculated from duplicate pairs of suspensions was 16% for S, 9% for Fe, 15% for Ni and 10% for Cu. Three spectral data processing techniques were further compared with respect to the quantification accuracy of target elements: internal standard, univariate and multivariate regressions. It was shown that the two latter methods can be used to improve the trueness of the internal standard method, especially for Cu and Fe.

Assessing the predictive capability of the empirical Shale Gouge Ratio–buoyancy pressure calibration: implications for estimating CO 2 column heights

Abstract Current workflows for estimating the maximum height of sequestrated CO 2 trapped by fault-rock seal are based on an empirically derived predictive relationship between fault-zone shale content estimated using the Shale Gouge Ratio (SGR) algorithm and buoyancy pressure. The predictive capability of this relationship has been assessed using observed in-place column height data from 25 fault-bounded traps containing gas or oil only. Two-thirds of gas-only traps have an observed trapped column that is more than 67% of the maximum predicted column height. By contrast, only 14% of oil-only traps have an observed column height of more than 67% of the maximum predicted column height. The existing SGR–buoyancy pressure calibration relationship is more optimal for low density (&lt;450 kg m −3 ) buoyant fluids but is less so for higher density fluids (&gt;650 kg m −3 ) such as oil. A new SGR–buoyancy pressure relationship has been derived for oil-only data. Fault seal envelopes for oil-only data exhibit a ‘reclined’ trend which implies a limited increase in seal strength and hence column height, with increasing SGR. As sequestrated CO 2 is likely to have fluid properties (interfacial tension, wettability and density) similar to that of oil in the subsurface, an empirical calibration relationship based on oil-only data should be used as a first-order predictor for CO 2 column heights.

A Deep Learning Model for Improved Wind and Consequent Wave Forecasts

Abstract The paper presents a combined numerical–deep learning (DL) approach for improving wind and wave forecasting. First, a DL model is trained to improve wind velocity forecasts by using past reanalysis data. The improved wind forecasts are used as forcing in a numerical wave forecasting model. This novel approach, used to combine physics-based and data-driven models, was tested over the Mediterranean. The correction to the wind forecast resulted in ∼10% RMSE improvement in both wind velocity and wave height over reanalysis data. This significant improvement is even more substantial at the Aegean Sea when Etesian winds are dominant, improving wave height forecasts by over 35%. The additional computational costs of the DL model are negligible compared to the costs of either the atmospheric or wave numerical model by itself. This work has the potential to greatly improve the wind and wave forecasting models used nowadays by tailoring models to localized seasonal conditions, at negligible additional computational costs. Significance Statement Wind and wave forecasting models solve a set of complicated physical equations. Improving forecasting accuracy is usually achieved by using a higher-resolution, empirical coefficients calibration or better physical formulations. However, measurements are rarely used directly to achieve better forecasts, as their assimilation can prove difficult. The presented work bridges this gap by using a data-driven deep learning model to improve wind forecasting accuracy, and the resulting wave forecasting. Testing over the Mediterranean Sea resulted in ∼10% RMSE improvement. Inspecting the Aegean Sea when the Etesian wind is dominant shows an outstanding 35% improvement. This approach has the potential to improve the operational atmospheric and wave forecasting models used nowadays by tailoring models to localized seasonal conditions, at negligible computational costs.

An update of the 3D analytical solution for the design of barricades made of waste rocks

Stope backfilling is increasingly used in underground mines. Barricades are necessary to retain slurried backfill poured in mine stopes . In Canada, waste rock barricades (WRB) have been becoming more and more popular to retain paste backfill in stopes. A few solutions have been developed to size the WRB. Among them, a solution developed by Yang and coworkers in 2017 is particularly relevant. However, this solution was calibrated and validated by 2D numerical modeling . Its validity in 3D conditions remains unknown. In addition, the local stability analysis was made by considering a horizontal sliding plane while their numerical modeling clearly showed an inclined plane. In this study, the validity of the Yang et al. solution is first evaluated against a few numerical results obtained with FLAC3D. The subjectivity in evaluating the instability onset of a structure in numerical modeling is further reduced by considering the first occurrence between displacement jump and coalescence of current yield zones passing through a WRB structure from the downstream to upstream slopes. The results show that both the global and local stability analysis equations of the Yang et al. solution need to be updated. For the global stability analysis, the value of the earth pressure coefficient needs to be modified while an inclined sliding plane needs to be considered for the local stability analysis. These considerations result in a considerable improvement because the updated solution does not contain any empirical calibration coefficient. Good agreements are obtained between the results obtained with numerical simulations and those predicted by the updated 3D analytical solution. The proposed solution is then further validated by an experimental result recently available in the literature. It can be used to design WRB to retain fluid-like paste backfill at the preliminary stage of a project.

CladeDate: Calibration information generator for divergence time estimation

Abstract Time‐scaled phylogenetic trees are essential tools in modern biology and node‐based calibrations have been the main approach to time‐tree estimation. But methods for generating the required calibration information are scarce and difficult to parameterize. Here, I present CladeDate, an R package for the generation of empirical calibration information from the fossil record. CladeDate uses simple mathematical models to estimate the age of a clade and its uncertainty based on fossil times. Using a Monte Carlo approach, CladeDate generates empirical densities representing the uncertainty associated with the age of the clade and fits standard probability density functions that can be used in time‐tree inference software such as BEAST2, MrBayes and MCMCtree. I show with simulations that the calibration information generated with CladeDate produces accurate time‐trees and compares favourably with more complex methods. I demonstrate the use CladeDate for the generation of calibration information, including point estimates, upper bounds and calibration densities, for passerine birds. CladeDate is particularly suited for groups with limited fossil information or when assumptions of more complex methods are not met, and provides a general and practical solution to the problem of generating calibration information for divergence time estimation.

A systematic review of the agent-based modelling/simulation paradigm in mobility transition

Simulations and agent-based modelling (ABM) have gained momentum as techniques in the transport, energy, and technology diffusion literature to analyse the mobility transition as a complex emergent phenomenon. This study systematically reviews the application of the ABM paradigm in 86 mobility transition studies. The study reveals several research gaps and proposes avenues for future research. Our review highlights that (i) the field has considerably matured in studying the diffusion of electric vehicles, (ii) both price-based and preference-based scenarios for mobility transition should be considered in future research, (iii) most of the empirical model calibrations have been confined to Western countries. Not only will the literature benefit from similar research in other Western regions, but also from non-Western nations with their unique mobility transition pathways, (iv) the conceptual modelling framework of studies can be divided into the two categories of theory-driven and heuristic models. The theory-driven models, which include psychological and non-psychological (e.g., activity-based travel) models, tend to use well-established behavioural rules, (v) most of the models have used the random utility maximization concept, social psychological models, and other simple assumptions/thresholds for the decision-making process of agents, (vi) half of the studies did not validate their models, and (vii) two-thirds of studies omitted to discuss interaction topology among agents. Major remaining challenges and gaps are identified in the review.

Modelling wave attenuation through submerged vegetation canopies using a subgrid canopy flow model

Coastal canopies formed by aquatic vegetation can significantly modify nearshore wave processes, which has motivated numerous laboratory and field studies investigating how wave attenuation occurs for a wide range of canopies as a function of wave conditions and canopy properties. To predict wave dissipation by canopies, numerous formulations have been derived to describe canopy drag through use of empirical drag coefficients. In many cases, drag coefficients are used as a tuning parameter to account for complex processes that govern how wave-driven flows interact with individual plants within canopies. This approach, however, can greatly limit the predictive capabilities of both empirical and numerical models. In this study, we extend a non-hydrostatic (phase-resolving) depth-integrated wave model (XBeach non-hydrostatic) with an efficient and robust subgrid canopy flow model to account for the important properties of submerged canopy flows that govern canopy drag forces and wave dissipation. A combination of wave heights, velocities and direct canopy force measurements, as well as data obtained from literature, were used to validate the model, showing the model has good skill in capturing the governing flow dynamics for both rigid and flexible vegetation canopies. By incorporating the canopy flow dynamics, the extended model allows for application of well-established drag coefficients for individual canopy elements to accurately predict wave attenuation over submerged vegetation canopies, rather than relying on empirical formulations or calibration. With the current extension, the model remains computationally efficient, allowing for use on coastal (∼km) scales. • A canopy flow subgrid model was implemented in the open-source XBeach model. • The model was verified using observed wave heights, velocities and canopy forces. • It can accurately predict wave evolution over rigid and flexible submerged canopies. • The model is robust and computationally efficient for use in large scale applications. • Not accounting for canopy flow can lead to substantial errors in wave predictions.

Empirical calibration of earthquake magnitudes for the Tell Atlas (Northern Algeria)

Empirical calibration of earthquake magnitudes for the Tell Atlas (Northern Algeria)

Simultaneous determination of Os, Ir, Pt and Au in sorbent phases by total reflection X-ray fluorescence

Simultaneous determination of trace and ultra-trace noble metal (NM) contents is a challenging analytical problem. Quantification of NMs in a solid sorbent phase by total reflection X-ray fluorescence (TXRF) was propounded to exclude the problematic stage of analytes desorption. In this study, line overlapping and spectra processing were discussed, theoretical upper limit of area-related mass of the sorbent on a reflector was evaluated, and different quantification procedures were compared. A procedure for the simultaneous determination of Os, Ir, Pt and Au in the solid sorbent phase was developed. This procedure includes sorption of NMs from a diluted solution of a digested sample, TXRF determination of analytes directly in the sorbent phase and data processing using empirical calibration or multivariate regression algorithms (principal component regression, projection on latent structures or partial least squares regression). The procedure allows determining Os, Ir, Pt, Au with a relative error of 15%. Calculated limits of quantification (LOQ) for rocks, considering our sample decomposition procedure, were equal to 0.43, 0.39, 0.43 and 0.31 μg g−1 for Os, Ir, Pt and Au, respectively. The procedure was verified using certificated reference materials and ICP-MS as a reference method.

Energy Calibration of Nonlinear Microcalorimeters with Uncertainty Estimates from Gaussian Process Regression.

The nonlinear energy response of cryogenic microcalorimeters is usually corrected through an empirical calibration. X-ray or gamma-ray emission lines of known shape and energy anchor a smooth function that generalizes the calibration data and converts detector measurements to energies. We argue that this function should be an approximating spline. The theory of Gaussian process regression makes a case for this functional form. It also provides an important benefit previously absent from our calibration method: a quantitative uncertainty estimate for the calibrated energies, with lower uncertainty near the best-constrained calibration points.

COol Companions ON Ultrawide orbiTS (COCONUTS). III. A Very Red L6 Benchmark Brown Dwarf around a Young M5 Dwarf

We present the third discovery from the COol Companions ON Ultrawide orbiTS (COCONUTS) program, the COCONUTS-3 system, composed of the young M5 primary star UCAC4 374−046899 and the very red L6 dwarf WISEA J081322.19−152203.2. These two objects have a projected separation of (1891 au) and are physically associated given their common proper motions and estimated distances. The primary star, COCONUTS-3A, has a mass of 0.123 ± 0.006 M ⊙, and we estimate its age as 100 Myr to 1 Gyr based on its stellar activity (via Hα and X-ray emission), kinematics, and spectrophotometric properties. We derive its bulk metallicity as 0.21 ± 0.07 dex using empirical calibrations established by older and higher-gravity M dwarfs and find that this [Fe/H] could be slightly underestimated according to PHOENIX models given COCONUTS-3A’s younger age. The companion, COCONUTS-3B, has a near-infrared spectral type of L6 ± 1 int-g, and we infer physical properties of T eff = K, = dex, R Jup, and M Jup using its bolometric luminosity, its host star’s age, and hot-start evolution models. We construct cloudy atmospheric model spectra at the evolution-based physical parameters and compare them to COCONUTS-3B’s spectrophotometry. We find that this companion possesses ample condensate clouds in its photosphere (f sed = 1) with the data–model discrepancies likely due to the models using an older version of the opacity database. Compared to field-age L6 dwarfs, COCONUTS-3B has fainter absolute magnitudes and a 120 K cooler T eff. Also, the J − K color of this companion is among the reddest for ultracool benchmarks with ages older than a few hundred megayears. COCONUTS-3 likely formed in the same fashion as stellar binaries given the companion-to-host mass ratio of 0.3 and represents a valuable benchmark to quantify the systematics of substellar model atmospheres.

Assessing the effectiveness of empirical calibration under different bias scenarios

BackgroundEstimations of causal effects from observational data are subject to various sources of bias. One method for adjusting for the residual biases in the estimation of treatment effects is through the use of negative control outcomes, which are outcomes not believed to be affected by the treatment of interest. The empirical calibration procedure is a technique that uses negative control outcomes to calibrate p-values. An extension of this technique calibrates the coverage of the 95% confidence interval of a treatment effect estimate by using negative control outcomes as well as positive control outcomes, which are outcomes for which the treatment of interest has known effects. Although empirical calibration has been used in several large observational studies, there is no systematic examination of its effect under different bias scenarios.MethodsThe effect of empirical calibration of confidence intervals was analyzed using simulated datasets with known treatment effects. The simulations consisted of binary treatment and binary outcome, with biases resulting from unmeasured confounder, model misspecification, measurement error, and lack of positivity. The performance of the empirical calibration was evaluated by determining the change in the coverage of the confidence interval and the bias in the treatment effect estimate.ResultsEmpirical calibration increased coverage of the 95% confidence interval of the treatment effect estimate under most bias scenarios but was inconsistent in adjusting the bias in the treatment effect estimate. Empirical calibration of confidence intervals was most effective when adjusting for the unmeasured confounding bias. Suitable negative controls had a large impact on the adjustment made by empirical calibration, but small improvements in the coverage of the outcome of interest were also observable when using unsuitable negative controls.ConclusionsThis work adds evidence to the efficacy of empirical calibration of the confidence intervals in observational studies. Calibration of confidence intervals is most effective where there are biases due to unmeasured confounding. Further research is needed on the selection of suitable negative controls.

Bismuth fire assay preconcentration and empirical coefficient LA-ICP-MS for the determination of ultra-trace Pt and Pd in geochemical samples

In this work, a novel method of solid sample pretreatment technique of bismuth fire assay (Bi-FA) combined with solid sample determination by laser ablation ICP-MS (LA-ICP-MS) was reported for the determination of ultra-trace Pt and Pd in geochemical samples. Bismuth oxide (Bi2O3) was used as fire assay collector to directly enrich Pt and Pd from solid samples, and Ag protection cupellation was employed to generate Ag granules. After cleaning, weighing and annealing, the Ag granules were compressed into thin slices and determined by LA-ICP-MS for 195Pt, 105Pd and 109Ag (109Ag was selected as the internal standard isotope). Bi2O3 provided exceptionally low blanks compared to nickel oxide and lead oxide commonly employed in fire assay procedures, and could be applied directly without purification. Different from traditional empirical coefficient method, the Chinese Certified Reference Materials (CRMs) for Pt and Pd were treated by the same procedure to obtain completely matrix matched Ag slices. And then modified empirical coefficient method and internal standard calibration strategy was used to reduce the instability of LA-ICP-MS, and random multipoint laser ablation was employed to further reduce analytical variation resulting from heterogeneity of Pt and Pd in the Ag slice. Under optimal conditions, excellent calibration curves for Pt and Pd were obtained (0.407–2958 μg g−1 and 0.407–2636 μg g−1, respectively), with correlation coefficients exceeding 0.9996. The method detection limits for Pt and Pd were 0.074 and 0.037 ng g−1, respectively. The established method was applied successfully to analysis of real geochemical samples, with determined values in good agreement with the results of traditional Pb-FA graphite furnace atomic absorption spectrometry (GF-AAS), and spiked recoveries between 87.8 and 125.0%.

Vaccine Safety Surveillance Using Routinely Collected Healthcare Data-An Empirical Evaluation of Epidemiological Designs.

Background: Routinely collected healthcare data such as administrative claims and electronic health records (EHR) can complement clinical trials and spontaneous reports to detect previously unknown risks of vaccines, but uncertainty remains about the behavior of alternative epidemiologic designs to detect and declare a true risk early. Methods: Using three claims and one EHR database, we evaluate several variants of the case-control, comparative cohort, historical comparator, and self-controlled designs against historical vaccinations using real negative control outcomes (outcomes with no evidence to suggest that they could be caused by the vaccines) and simulated positive control outcomes. Results: Most methods show large type 1 error, often identifying false positive signals. The cohort method appears either positively or negatively biased, depending on the choice of comparator index date. Empirical calibration using effect-size estimates for negative control outcomes can bring type 1 error closer to nominal, often at the cost of increasing type 2 error. After calibration, the self-controlled case series (SCCS) design most rapidly detects small true effect sizes, while the historical comparator performs well for strong effects. Conclusion: When applying any method for vaccine safety surveillance we recommend considering the potential for systematic error, especially due to confounding, which for many designs appears to be substantial. Adjusting for age and sex alone is likely not sufficient to address differences between vaccinated and unvaccinated, and for the cohort method the choice of index date is important for the comparability of the groups. Analysis of negative control outcomes allows both quantification of the systematic error and, if desired, subsequent empirical calibration to restore type 1 error to its nominal value. In order to detect weaker signals, one may have to accept a higher type 1 error.

The Low-Redshift Lyman Continuum Survey

Aims. Combining 66 ultraviolet (UV) spectra and ancillary data from the recent Low-Redshift Lyman Continuum Survey (LzLCS) and 23 LyC observations by earlier studies, we form a statistical sample of star-forming galaxies at z ∼ 0.2 − 0.4 with which we study the role of cold interstellar medium (ISM) gas in the leakage of ionizing radiation. We also aim to establish empirical relations between the H I neutral and low-ionization state (LIS) absorption lines with different galaxy properties. Methods. We first constrain the massive star content (stellar ages and metallicities) and UV attenuation by fitting the stellar continuum with a combination of simple stellar population models. The models, together with accurate LyC flux measurements, allow us to determine the absolute LyC photon escape fraction for each galaxy (fescabs). We then measure the equivalent widths and residual fluxes of multiple H I and LIS lines, and the geometrical covering fraction of the UV emission, adopting the picket-fence model. Results. The LyC escape fraction spans a wide range, with a median fescabs (0.16, 0.84 quantiles) of 0.04 (0.02, 0.20), and 50 out of the 89 galaxies detected in the LyC (1σ upper limits of fescabs ≲ 0.01 for non-detections, typically). The H I and LIS line equivalent widths scale with the UV luminosity and attenuation, and inversely with the residual flux of these lines. Additionally, Lyα equivalent widths scale with both the H I and LIS residual fluxes, but anti-correlate with the corresponding H I or LIS equivalent widths. The H I and LIS residual fluxes are correlated, indicating that the neutral gas is spatially traced by the low-ionization transitions. We find that the observed trends of the absorption lines and the UV attenuation are primarily driven by the geometric covering fraction of the gas. The observed nonuniform gas coverage also demonstrates that LyC photons escape through low-column-density channels in the ISM. The equivalent widths and residual fluxes of both the H I and LIS lines strongly correlate with fescabs: strong LyC leakers (highest fescabs) show weak absorption lines, low UV attenuation, and large Lyα equivalent widths. We provide several empirical calibrations to estimate fescabs from UV absorption lines. Finally, we show that simultaneous UV absorption line and dust attenuation measurements can, in general, predict the escape fraction of galaxies. We apply our method to available measurements of UV LIS lines of 15 star-forming galaxies at z ∼ 4 − 6 (plus 3 high-z galaxy composites), finding that these high-redshift, UV-bright galaxies (MUV ≲ −21) may have low escape fractions, fescabs ≲ 0.1. Conclusions. UV absorption lines trace the cold ISM gas of galaxies, which governs the physics of the LyC escape. We show that, with some assumptions, the absolute LyC escape can be statistically predicted using UV absorption lines, and the method can be applied to study galaxies across a wide redshift range, including in the epoch of cosmic reionization.

Dual energy CT for a small animal radiation research platform using an empirical dual energy calibration

Objective. Dual energy computed tomography (DECT) has been shown to provide additional image information compared to conventional CT and has been used in clinical routine for several years. The objective of this work is to present a DECT implementation for a Small Animal Radiation Research Platform (SARRP) and to verify it with a quantitative analysis of a material phantom and a qualitative analysis with an ex-vivo mouse measurement. Approach. For dual energy imaging, two different spectra are required, but commercial small animal irradiators are usually not optimized for DECT. We present a method that enables dual energy imaging on a SARRP with sequential scanning and an Empirical Dual Energy Calibration (EDEC). EDEC does not require the exact knowledge of spectra and attenuation coefficients; instead, it is based on a calibration. Due to the SARRP geometry and reconstruction algorithm, the calibration is done using an artificial CT image based on measured values. The calibration yields coefficients to convert the measured images into material decomposed images. Main results. To analyze the method quantitatively, the electron density and the effective atomic number of a material phantom were calculated and compared with theoretical values. The electron density showed a maximum deviation from the theoretical values of less than 5% and the atomic number of slightly more than 6%. For use in mice, DECT is particularly useful in distinguishing iodine contrast agent from bone. A material decomposition of an ex-vivo mouse with iodine contrast agent was material decomposed to show that bone and iodine can be distinguished and iodine-corrected images can be calculated. Significance. DECT is capable of calculating electron density images and effective atomic number images, which are appropriate parameters for quantitative analysis. Furthermore, virtual monochromatic images can be obtained for a better differentiation of materials, especially bone and iodine contrast agent.

Experimental and Simulated Spectral Gamma-Ray Response of a NaI(Tl) Scintillation Detector used in Airborne Gamma-Ray Spectrometry

Abstract. The objective of this work is to simulate the spectral gamma-ray response of NaI(Tl) scintillation detectors for airborne gamma-ray spectrometry (AGRS) using the state-of-the-art multi-purpose Monte Carlo code FLUKA. The study is based on a commercial airborne gamma-ray spectrometry detector system with four individual NaI(Tl) scintillation crystals and a total volume of 16.8 L. To validate the developed model, radiation measurements were conducted using 57Co, 60Co, 88Y, 109Cd, 133Ba, 137Cs and 152Eu calibration point sources with known activities and source-detector geometries under laboratory conditions. In addition, empirical calibration and resolution functions were derived from these measurements combined with additional radiation measurements adopting natural uranium, thorium and potassium volume sources. The simulation results show superior accuracy and precision compared to previous AGRS simulation models with a median relative spectral error &lt; 10 % for most of the radiation sources. Moreover, the implementation of a lower level discriminator model and detailed modelling of the laboratory result in a significant improvement in model accuracy for spectral energies &lt; 100 keV compared to previous studies. Yet thorough statistical analysis incorporating statistical and systematic uncertainty estimates revealed statistically significant deviations between the simulated and measured spectra in the spectral region around the Compton edge, which could be attributed to the scintillator non-proportionality. These findings imply that the linear energy deposition model applied in this and previously developed AGRS simulation models should be revised and considered to be replaced by more accurate non-proportional models.

Measuring Floating Thick Seep Oil from the Coal Oil Point Marine Hydrocarbon Seep Field by Quantitative Thermal Oil Slick Remote Sensing

Remote sensing techniques offer significant potential for generating accurate thick oil slick maps critical for marine oil spill response. However, field validation and methodology assessment challenges remain. Here, we report on an approach to leveraging oil emissions from the Coal Oil Point (COP) natural marine hydrocarbon seepage offshore of southern California, where prolific oil seepage produces thick oil slicks stretching many kilometers. Specifically, we demonstrate and validate a remote sensing approach as part of the Seep Assessment Study (SAS). Thick oil is sufficient for effective mitigation strategies and is set at 0.15 mm. The brightness temperature of thick oil, TBO, is warmer than oil-free seawater, TBW, allowing segregation of oil from seawater. High spatial-resolution airborne thermal and visible slick imagery were acquired as part of the SAS; including along-slick “streamer” surveys and cross-slick calibration surveys. Several cross-slick survey-imaged short oil slick segments that were collected by a customized harbor oil skimmer; termed “collects”. The brightness temperature contrast, ΔTB (TBO − TBW), for oil pixels (based on a semi-supervised classification of oil pixels) and oil thickness, h, from collected oil for each collect provided the empirical calibration of ΔTB(h). The TB probability distributions provided TBO and TBW, whereas a spatial model of TBW provided ΔTB for the streamer analysis. Complicating TBW was the fact that streamers were located at current shears where two water masses intersect, leading to a TB discontinuity at the slick. This current shear arose from a persistent eddy down current of the COP that provides critical steering of oil slicks from the Coal Oil Point. The total floating thick oil in a streamer observed on 23 May and a streamer observed on 25 May 2016 was estimated at 311 (2.3 bbl) and 2671 kg (20 bbl) with mean linear floating oil 0.14 and 2.4 kg m−1 with uncertainties by Monte Carlo simulations of 25% and 7%, respectively. Based on typical currents, the average of these two streamers corresponds to 265 g s−1 (~200 bbl day−1) in a range of 60–340 bbl day−1, with significant short-term temporal variability that suggests slug flow for the seep oil emissions. Given that there are typically four or five streamers, these data are consistent with field emissions that are higher than the literature estimates.