Estimation Of Measurement Uncertainty Research Articles

An Efficient LC–HRMS-Based Approach to Evaluate Pesticide Contamination in Water Bodies with Measurement Uncertainty Considerations

Over recent decades, the global occurrence of pesticide residues in aquatic environments has been a pivotal issue; however, their trace-level concentrations necessitate the establishment of ultra-sensitive and reliable analytical approaches. To this end, the present study describes the optimization and validation of an LC-HRMS-based method for the accurate determination of 18 pesticides in river and sea water, accompanied by a measurement uncertainty estimation. This method was applied to analyze 17 real samples from agriculture and aquaculture-impacted areas in Greece and Albania. Different solid-phase extraction (SPE) protocols were tested. For the analysis, cutting-edge Orbitrap MS technology and MS/MS fragmentation, along with the use of matrix-matched calibration curves, provided unprecedented accuracy (<5 ppm) and sensitivity for the confirmation of positive detections. Regarding method performance, exceptional linearity was obtained; the limits of quantification ranged from 1.7 ng L−1 to 90 ng L−1, recoveries varied from 61% to 96% in river water, while slightly higher recoveries (60–111%) were observed in seawater. In all cases, repeatability and intra-laboratory reproducibility were below 15%. The measurement expanded uncertainty (U′, k = 2) was estimated considering precision and bias. MU% values were lower than 50% in all cases, as recommended in SANTE guidelines and applied to the quantified results. The matrix effect study exhibited negative values (<20%) for all compounds. Application to real samples showed a low pesticide contamination load that should not be underestimated.

GGR Handbook of Rock and Mineral Analysis Chapter 1 (Part 2) Sampling as Part of the Measurement Process

This chapter (Sampling as Part of the Measurement Process) is a contribution to the Geostandards and Geoanalytical Research Handbook of Rock and Mineral Analysis – an online textbook that is a fully revised and updated edition of A Handbook of Silicate Rock Analysis (P. J. Potts, 1987, Blackie, Glasgow).Chapter 1 (Part 2) forms part of Section 1 of the handbook dealing with fundamentals of measurement and instrument design. The geochemical measurement process is considered to begin when the primary sample is taken from the sampling target, rather than when that sample arrives at the laboratory. This integration of sampling within the measurement procedure enables both sampling and chemical analysis to be optimised in order to achieve a measurement procedure that is fit for its intended geochemical purpose. The key metric in judging this fitness for purpose, and hence validating a measurement procedure, is the uncertainty of each measurement value. This measurement uncertainty is explained, together with methods to estimate and express it in a way that includes the contribution from sampling, with a worked example. The resultant more realistic estimates of measurement uncertainty are shown to improve the reliability of the geochemical interpretation of measurement values.

A New Correlation for Estimating Solid Particle Erosion in Elbows

Solid particle erosion prediction models have been developed previously based on limited data and without consideration of uncertainties involved in measurements. In this study, a new correlation is developed to estimate the maximum erosion rate caused by solid particles in standard elbow geometries. The novel development process of this correlation includes uncertainty estimation of erosion measurements. In order to estimate uncertainties in an erosion database, it is imperative to have a model that could be used to calculate accurate erosion values to have reliable references. For this purpose, a database of repeated erosion measurements for gas-sand flows at low-pressure collected by previous researchers is used that includes standard elbow geometries with 0.0762 m and 0.1016 m internal pipe diameter, sand particles with mean diameters of 75 and 300 μm. Then, the erosion values in this database are adjusted to agree with physical behaviors expected in erosion process. Finally, based on the adjusted erosion values, a new correlation is developed that accounts for important paramters such as pipe and particle diameters, and gas velocity. The results and comparison of this new model with other correlations/models in the literature show that this correlation performs very well in predicting solid-particle erosion values for elbow geometry with a RMSE value of 7.96E-02 mm/kg. The effect of superficial liquid velocity is also investigated and modeled based on a database of gas-liquid-sand erosion and the correlation is updated for predicting erosion in two-phase flow conditions. Furthermore, CFD results for higher pressure fluids and larger pipe diameters of 0.1524 m and 0.2032 m and mean particle sizes of 25, 75, 150 and 300 μm, are used to further develop and validate the correlation for larger pipe size and high-pressure fluids flows. In summary, three correlations have been developed in this research; one for low-pressure flows with application in uncertainty estimation, one for predicting erosion in two-phase flow conditions, and one for cases with larger pipe diameters or high-pressure fluids.

USING RETROSPECTIVE DATA TO ASSESS THE UNCERTAINTY OF INDICATORS OF BIOLOGICAL SAFETY OF FOOD AND FEED RAW MATERIALS

The results of the analysis of the advantages and disadvantages of the use of retrospective data for the implementation of the evaluation of uncertainty in the measurement of indicators of biological safety of food and feed raw materials are given. The model measurement procedure used quantitative determination of genetically modified organisms by means of polymerase chain reaction in real time 250 measurement results of certified reference material with a content of 0.1% genetically modified soybean line obtained under conditions of intra-laboratory reproducibility and 10 results of relevant inter-laboratory comparisons with the participation accredited provider. The suitability of retrospective data was assessed by the Shapiro-Wilk criterion and statistical controllability analysis using standardized score charts and modified Shewhart charts, uncertainty by 4 methods described in general and branch international guidelines and regulations. The results of using a combination of modified Shewhart maps demonstrate the acceptability of this approach for establishing the suitability of retrospective measurement results as input data for uncertainty assessment. By integrating additional "fitness limits" to a set of standardized control limits, this analysis acquires the ability to simultaneously establish not only stability, through the interpretation of geometric patterns, but also compliance with specific criteria. Using this approach, objective evidence of the suitability of retrospective data for estimating measurement uncertainty was obtained. The distribution of retrospective data obtained under conditions of intralaboratory reproducibility is assumed to be normal. As a result of the assessment of statistical controllability and compliance with the established criteria, objective evidence of the suitability of the data for uncertainty assessment was obtained. Analysis of uncertainty intervals of subgroups with the volume of 25 measurements, using 4 assessment methods, demonstrated significant variability in the results of measuring biological safety indicators. The uncertainty interval could narrow or widen by almost 100% of the value within fifty measurements. Median values obtained using different uncertainty estimation methods were 2.69%, 22.69%, 39.23, and 43.08%. This variability is due to the limited coverage of sources of uncertainty, which is inherent in each of the analyzed methods. The most optimal method is the evaluation based on the routine measurement of the certified reference material. Retrospective results of routine measurement of certified reference material and interlaboratory comparisons are an effective source of input data for assessing the uncertainty of the results of measuring biological safety indicators of agricultural raw materials. There is a need for further research to establish an assessment model that will provide an opportunity to take into account the optimal number of influential sources of uncertainty that are inherent in biological systems and cannot be simultaneously taken into account using existing approaches offered by standard assessment methods.

No evidence for interstellar fireballs in the CNEOS database

Context. The detection of interstellar meteors, especially meteorite-dropping meteoroids, would be transformative, as this would enable direct sampling of material from other stellar systems on Earth. One candidate is the fireball observed by U.S. government sensors on January 8, 2014. It has been claimed that fragments of this meteoroid have been recovered from the ocean floor near Papua New Guinea and that they support an extrasolar origin. Based on its parameters reported in the Center for Near Earth Object Studies (CNEOS) catalog, the fireball exhibits a hyperbolic excess velocity that indicates an interstellar origin; however, the catalog does not report parameter uncertainties. Aims. To achieve a clear confirmation of the fireball’s interstellar origin, we assessed the underlying error distributions of the catalog data. Our aim was also to confirm whether the fragments of this meteoroid survived passage through the atmosphere and assess all conditions needed to unambiguously determine the fragments’ origin. Methods. We approached the investigation of the entire catalog using statistical analyses and modeling, and we provide a comprehensive analysis of the individual hyperbolic CNEOS cases. Results. We have developed several independent arguments indicating substantial uncertainties in the velocity and radiant position of the CNEOS events. We determined that all the hyperbolic fireballs exhibit significant deviations from the majority of the events in one of their velocity components, and we show that such mismeasurements can produce spurious parameters. According to our estimation of the speed measurement uncertainty for the catalog, we found that it is highly probable that such a catalog containing only Sun-bound meteors would show at least one event that appears highly unlikely to be Sun-bound. We also establish that it is unlikely that any fragments from a fireball traveling at the high inferred velocities could survive passage through the atmosphere. When assuming a much lower velocity, some fragments of this meteoroid could survive; however, they would be of a common Solar System origin and thus highly probable to be indistinguishable from the quantity of other local micrometeorites that have gradually accumulated on the sea floor. Conclusions. We conclude that there is no evidence in the CNEOS data to confirm or reject the interstellar origin of any of the nominally hyperbolic fireballs in the CNEOS catalog. Therefore, the claim of an interstellar origin for the fireball recorded over Papua New Guinea in 2014 remains unsubstantiated. We have also gathered arguments that refute the claim that the collected spherules from the sea floor originated in the body of this fireball.

Age dependence of the average refractive index of the isolated human crystalline lens.

We measured the average group refractive index (RI) of 120 isolated lenses from 120 human donors (age: 0.03 to 61 years). The average group RI was calculated from a measurement of the optical thickness of the lens using optical coherence tomography and the apparent window shift of the test chamber caused by the lens. The estimated measurement uncertainty was ±0.004. The group RI at 880 nm was converted to phase RI at 589 nm using the dispersion equation of water and protein. From 2 to 61 years, the mean value of the RI was 1.415 ± 0.002 (group index at 880 nm) and 1.406 ± 0.002 (phase index at 589 nm) independent of age (p = 0.774). Two lenses from donors of age 0.33 and 3 months had significantly lower RI (group index: 1.405 and 1.403; phase index: 1.396 and 1.394). From age 2 to 61, the average lens RI is constant with age within the measurement uncertainty (±0.004).

Statistical Modeling of Within-Laboratory Precision Using a Hierarchical Bayesian Approach.

Reproducibility has been well-studied in the field of food analysis; the relative standard deviation is said to follow the Horwitz curve with certain exceptions. However, little systematic research has been done on predicting repeatability or intermediate precision. We developed a regression method to estimate within-laboratory standard deviations using hierarchical Bayesian modeling and analyzing duplicate measurement data obtained from actual laboratory tests. The Hamiltonian Monte Carlo method was employed and implemented using R with Stan. The basic structure of the statistical model was assumed to be a chi-squared distribution, the fixed effect of the predictor was assumed to be a nonlinear function with a constant term and a concentration-dependent term, and the random effects were assumed to follow a lognormal distribution as a hierarchical prior. By analyzing over 300 instances, we obtained regression results that fit well with the assumed model, except for moisture, which was a method-defined analyte. The developed method applies to a wide variety of analytes measured using general principles, including spectroscopy, GC, and HPLC. Although the estimated precisions were within the HorRat(r) criteria, some cases using high-sensitivity detectors, such as mass spectrometers, showed standard deviations below that range. We propose utilizing the within-laboratory precision predicted by the model established in this study for internal quality control and measurement uncertainty estimation without considering the sample matrices. Performing statistical modeling on data from double analysis, which is conducted as a part of internal quality controls, will simplify the estimation of the precision that fits each analytical system in a laboratory.

Determination of Uncertainty in calibration of External Micrometer

In recent years there has been a growing awareness of measurement uncertainty, mainly for two reasons. First, the ever- increasing number of laboratory accreditations requires the evaluation of measurement uncertainty, especially in the area of calibration. Second, quality system protocols get mature with process and time. This is because manufacturers ensure the reliability of their measurements through correct calibration of their test and measuring equipment. International and national regulations require calibration and testing laboratories to provide result of measurement uncertainty. Calibration of the measuring instrument is the process in which the readings obtained from the instrument are compared with the standard values in the laboratory at several points along the scale of the instruments i.e. micrometer, gauges, calipers etc. In general, a calibration without information about the uncertainty of these estimates is incomplete. Calculating measurement uncertainty is an attempt to reasonably limit the results of measurements as referring to standard operating procedures. Since each measurement only provides a result of the outcome, the main requirement of the uncertainty estimation is to make reader confident that reading is within stated range. Proper calibration involves more than just estimating measurement uncertainty. It also requires that the estimated value is small compared to the stated accuracy of the meter

Neural networks for the analysis of 2D radio-xenon beta gamma spectra

Atmospheric traces of radioactive xenon can be a strong indicator for underground nuclear fission reactions. 131mXe, 133Xe, 133mXe and 135Xe are the primary gaseous isotopes/isomers currently used to identify and classify nuclear events. During decay, each of these radioactive species produces a unique beta-gamma energy spectra, which can be measured using beta-gamma coincidence counting. Current operational Xe beta-gamma spectrum analysis software relies on Region of Interest (ROI) counting (Bowyer et al. in J Environ Radioact 59(2):139–151, 2002). This algorithm occasionally produces mismeasurements, especially when quantifying meta-stable isomers, due to overlapping ROIs and shifts in detector calibration in fielded systems over time (Ringbom and Axelsson in Appl Radiat Isot 156:108950, 2020). In an attempt to better de-convolve overlapping isotope spectra we have developed a technique that applies a supervised neural-network implemented in TensorFlow with Keras to classify and quantify the isotopes and mixtures of isomers based on their beta-gamma spectra—similar to image recognition. From this, we have improved upon the false-positive rate for classification and regression models, however challenges remain with dealing with differing detector energy calibrations and with estimating measurement uncertainty.

A Morphological Approach to Development of a Process for Measurement Uncertainty Estimation

The problem of increasing the reliability of uncertainty estimation of measurement results is considered. The purpose of this work was to justify the application of the process approach to the formation of the algorithm of uncertainty estimation on the basis of morphological analysis. It is theoretically substantiated that from the standpoint of the system approach to achieving an acceptable degree of reliability of measurement uncertainty estimates it is necessary to implement a process approach to the formation of the estimation method as an algorithm of actions. The main stages of the estimation process are defined. It is established that each stage of the estimation process can be realized by alternative methods. The morphological box method as a realization of morphological analysis is proposed as a basis for its solution. A morphological box design of the uncertainty estimation process with an open architecture is presented, based only on commonly accepted methods and approaches for realizing each step of the process. Two aspects of the application of the morphological box method are identified. On the one hand, the morphological box allows to form an algorithm of the uncertainty assessment process, maximally acceptable for the laboratory conditions, as a combination of process steps, based on the task at hand, combining different variants of realization of these steps. On the other hand, the morphological box acts as a tool for development of new methods of realization of various stages of the uncertainty assessment process. Examples of using the morphological box method to develop alternative algorithms of the uncertainty estimation process of the same measurement method and to develop new methods of realization of different stages of the estimation process are considered.

Flow Measurements Above A DBD Plasma Actuator Array By Means Of Defocusing PTV

Lagrangian defocusing particle tracking velocimetry (DPTV) measurements are conducted in a thin, wall-parallel volume above a plasma actuator array that is applied to mimic the effect of wall oscillations by inducing alternating, wall-parallel forcing in opposite directions into the air above the actuator surface. The aim of the experiments is to capture the plasma-induced flow structures in otherwise quiescent air in order to increase the understanding of different actuation parameters. For this purpose, high-speed particle image velocimetry equipment with one camera is used in a DPTV setup, where the out-of-plane particle coordinate is obtained through the diameter of a defocused particle image. On this basis, an approach for continuous particle tracking in several consecutive frames is presented, allowing to derive three component, three dimensional velocity and acceleration data. Light reflections that occur on the adjacent actuator surface give raise to particular challenges concerning the measurement uncertainty estimation as well as the calibration procedure for the evaluation of the wall-normal coordinate of tracer particles. To overcome the latter, a calibration approach is presented for which solid particles are applied to the actuator surface and their particle image diameter is captured at different camera positions in a separate measurement. The estimation of in-plane and out-of-plane displacement measurement uncertainties is conducted following a newly-developed procedure where the deviation of particle displacements from a straight track is evaluated for measurements in quasi-quiescent air. The obtained results show the suitability of DPTV measurement technique for the practical application of the characterization of flow structures above a plasma actuator array. The measurement accuracy is found to be limited due to the available illumination, which depends on the used components. The measured flow fields together with optical and electrical measurement data allow for a further analysis of the present forcing strategy. Particularly, by recording phase-resolved, three-dimensional flow velocity and acceleration fields in the vicinity of the wall, the spatio-temporal occurrence and homogeneity of the near-wall forcing effects can be analyzed in future investigations.

Volumetric Flow Field Measurements Around A Stepped Cylinder With An Object-Aware Lagrangian Particle Tracking Approach

Instantaneous, three-dimensional flow field measurements around cylindrical objects can pose special problems for the experimental set-up due to the complex camera set-up required to image the complete measurement domain. Recently, a novel Object-aware Shake-the-Box (OA-STB) has been proposed to integrate object information in the particle triangulation step for Lagrangian particle tracking (LPT) methods. Within this conference paper, a validation experiment of this novel OA-STB implementation is presented with the motivation of providing data analysis details and to serve as a guideline for future measurements of a similar scope. The reconstruction quality of the object aware particle triangulation is analyzed with respect to the estimated measurement uncertainties. Further, a single exemplary trajectory is considered in order to investigate, whether nonphysical discontinuities occur, when a particle crosses differently imaged regions.

Analysis of target uncertainty assessment methods

For almost 25 years, mankind has been dealing with the problems of estimating measurement uncertainty. When applying uncertainty, the goal is not to determine the true value during the measurement as far as possible. That is, it is recognized that the information obtained during the measurement allows only to assign a reasonable interval of values ​​for the measured value, based on the assumption that no errors were made during the measurement. However, even the most accurate measurements cannot reduce this interval to a single value due to the finite number of details in the description of the measured value. An interval can be represented by a single value of its own, called the «measured value of the quantity». Over the years, many scientific works have been devoted to methods of estimating the uncertainty of measurements. At the same time, the main conclusion is that the value of uncertainty depends on the applied method of its assessment. In practice, the use of uncertainty has not been widely used. Accredited calibration and testing laboratories must be able to estimate measurement uncertainty. Therefore, they learn uncertainty assessment methods, develop examples. It is written in the management system that the evaluation of the uncertainty of the measurement result is provided at the request of the customer. But neither the customer nor the executor understands the purpose of its application. Therefore, now is the time for scientists, together with practitioners, to deal with the issue of establishing target uncertainty for solving specific measurement tasks, such as establishing compliance of products with specified requirements, establishing the suitability of measuring equipment after calibration, etc. Thus, for practical application, it is important to be able to determine the value of the target uncertainty - the value of uncertainty for the measured value of the quantity at which the measured value can be considered reliable for a specific practical application

A novel Zende’s-TOPSIS method towards estimation of measurement uncertainty in hole diameters

The ‘Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)’ is one of the best methods for ‘Multi-Criteria Decision-Making’ and ‘Multi-Objective Optimization’. The traditional TOPSIS method determines the best alternative under fixed conditions. However, it cannot determine the best upper limit and lowest limit values. This work explains the detailed methodology of the newly developed Zende’s-TOPSIS method which was used to estimate the measurement uncertainty in hole diameters. Four identical holes and one center hole in an industrial component were measured to investigate measurement uncertainty. According to the experimental results, Zende’s-TOPSIS method performed better than the traditional TOPSIS method. The percentage improvement in the Zende’s-TOPSIS method over the traditional TOPSIS method ranges from 0.0209% to 0.3053%. Using Zende’s-TOPSIS method, the percentage maximum measurement uncertainty for four identical holes varies from 0.8067% to 1.0222%, whereas for the center hole, it varies from 0.5261% to 0.5576%. Similarly, the percentage minimum measurement uncertainty for four identical holes varies from 0.3839% to 0.6406%, whereas for the center hole, it varies from 0.4014% to 0.4041%. The proposed method is also capable of estimating the machined tolerances of the component, which ranges from 18.0772 mm to 18.1708 mm for four identical holes and 49.2215 mm to 49.2572 mm for the center hole. The proposed method can solve various ‘Multi-Objective Optimization’ problems.

The estimation of measurement uncertainty of serum free light chain assays at Atellica NEPH630

The estimation of measurement uncertainty of serum free light chain assays at Atellica NEPH630

An uncertainty methodology for solar occultation flux measurements: ammonia emissions from livestock production

Abstract. Ammonia (NH3) emissions can negatively affect ecosystems and human health, so they should be monitored and mitigated. This study presents methodology for the estimation of uncertainties in NH3 emissions measurements using the solar occultation flux (SOF) method. The reactive nature of NH3 makes its measurement challenging, but SOF offers a reliable open-path passive method which utilizes solar spectrum data, thereby avoiding gas adsorption within the instrument. To compute NH3 gas fluxes, horizontal and vertical wind speed profiles, as well as plume height estimates and spatially resolved column measurements, are integrated. A unique aspect of this work is the first-time description of plume height estimations derived from ground and column NH3 concentration measurements aimed at uncertainty reduction. Initial validation tests indicated measurement errors between −31 % and +14 % on average, which was slightly larger than the estimated expanded uncertainty ranging from ± 12 % to ± 17 %. Application of the methodology to assess emission rates from farms of various sizes showed uncertainties between ± 21 % and ± 37 %, generally influenced by systematic wind uncertainties and random errors. The method demonstrates the capacity to measure NH3 emissions from both small (∼ 0.5–1 kg h−1) and large (∼ 100 kg h−1) sources in high-density farming areas. Generally, the SOF method provided an expanded uncertainty below 30 % in measuring NH3 emissions from livestock production, which could be further improved by adhering to best application practices. This paper's findings offer the potential for broader applications, such as measuring NH3 fluxes from fertilized fields and in the oil and gas sector. However, these applications would require further research to adapt and refine the methodologies for these specific contexts.

Nonparametric estimation of measurement uncertainty arising from sampling

BackgroundIncreasingly, measurement uncertainty has been used by pure and applied analytical chemistry to ensure decision-making in commercial transactions and technical-scientific applications. Until recently, it was considered that measurement uncertainty boiled down to analytical uncertainty; however, over the last two decades, uncertainty arising from sampling has also been considered. However, the second version of the EURACHEM guide, published in 2019, assumes that the frequency distribution is approximately normal or can be normalized through logarithmic transformations, without treating data that deviate from the normality. ResultsHere, six examples (four from Eurachem guide) were treated by classical ANOVA and submitted to an innovative nonparametric approach for estimating the uncertainty contribution arising from sampling. Based on bootstrapping method, confidence intervals were used to guarantee metrological compatibility between the uncertainty ratios arising from the results of the traditional parametric tests and the unprecedented proposed nonparametric methodology. Significance and noveltyThe present study proposed an innovative methodology for covering this gap in the literature based on nonparametric statistics (NONPANOVA) using the median absolute deviation concepts. Supplementary material based on Excel spreadsheets was developed, assisting users in the statistical treatment of their real examples.

Validation, measurement uncertainty estimation and evaluation of UHPLC greenness for simultaneous determination of metoprolol tartrate and hydrochlorothiazide in binary tablet

A novel green ultra high performance liquid chromatography (UHPLC) method was validated and estimated the measurement uncertainty for simultaneous determination of metoprolol tartrate (MET) and hydrochlorothiazide (HCT) in binary tablet. A Zorbax® SB-C18 column with isocratic elution (flow rate 0.9 mL min−1) at 25°C was used. Analytes and HCT degradation product were separated in approximately 1 min using acetonitrile:water:triethylamine (17:83:0.2, v/v) as mobile phase. Analytical curves were linear with (R 2 > 0.99 for MET and HCT) with detection limits of 2.42 and 1.05 µg mL−1 for MET and HCT, respectively. Precision measurements showed RSD% from 0.39 to 1.2% and method accuracy by recovery tests was 100 ± 2%. Measurement uncertainties using Eurachem procedure were 100.1 ± 2.8% and 100.3 ± 2.4% for MET and HCT, respectively. This UHPLC method was accurate, precise, linear and selective, making it suitable for pharmaceutical quality control. It also proved eco-friendly compared to other reported methods.

Stability, homogeneity and measurement uncertainty estimation of PVP-I solutions for the application on oro and nasopharynx against SARS-CoV-2

Aqueous solution containing different concentration (0.5, 0.6 and 1.0%) (w/v) of Polyvinyl pyrrolodon-Iodine (PVP-I) complex, a well-known antiseptic; is prepared and the stability and homogeneity of these solution is assessed as per the ICH Guidelines and International Harmonized Protocol respectively. The solutions were found to be sufficiently homogeneous and stable for a year at 25 °C (60%RH). Measurement uncertainty of the prepared PVP-I solutions were estimated by identifying possible sources of uncertainty using Ishikawa diagram and preparing uncertainty budget based on scope of calibration laboratory. The stable and homogenized PVP-I solution is to be used in a clinical trial for the application on oro and nasopharynx against novel SARS-CoV-2 Virus.

Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm

Abstract. The processes responsible for methane (CH4) emissions from boreal wetlands are complex; hence, their model representation is complicated by a large number of parameters and parameter uncertainties. The arctic-enabled dynamic global vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) is one such model that allows quantification and understanding of the natural wetland CH4 fluxes at various scales, ranging from local to regional and global, but with several uncertainties. The model contains detailed descriptions of the CH4 production, oxidation, and transport controlled by several process parameters. Complexities in the underlying environmental processes, warming-driven alternative paths of meteorological phenomena, and changes in hydrological and vegetation conditions highlight the need for a calibrated and optimised version of LPJ-GUESS. In this study, we formulated the parameter calibration as a Bayesian problem, using knowledge of reasonable parameters values as priors. We then used an adaptive Metropolis–Hastings (MH)-based Markov chain Monte Carlo (MCMC) algorithm to improve predictions of CH4 emission by LPJ-GUESS and to quantify uncertainties. Application of this method on uncertain parameters allows for a greater search of their posterior distribution, leading to a more complete characterisation of the posterior distribution with a reduced risk of the sample impoverishment that can occur when using other optimisation methods. For assimilation, the analysis used flux measurement data gathered during the period from 2005 to 2014 from the Siikaneva wetlands in Southern Finland with an estimation of measurement uncertainties. The data are used to constrain the processes behind the CH4 dynamics, and the posterior covariance structures are used to explain how the parameters and the processes are related. To further support the conclusions, the CH4 flux and the other component fluxes associated with the flux are examined. The results demonstrate the robustness of MCMC methods to quantitatively assess the interrelationship between objective function choices, parameter identifiability, and data support. The experiment using real observations from Siikaneva resulted in a reduction in the root-mean-square error (RMSE), from 0.044 to 0.023 gC m−2 d−1, and a 93.89 % reduction in the cost function value. As a part of this work, knowledge about how CH4 data can constrain the parameters and processes is derived. Although the optimisation is performed based on a single site's flux data from Siikaneva, the algorithm is useful for larger-scale multi-site studies for a more robust calibration of LPJ-GUESS and similar models, and the results can highlight where model improvements are needed.