Uncertainty Of Field Measurements Research Articles

CalBMP, a web-based modeling tool for evaluating pesticide offsite movement and best management practice scenarios in California agricultural land

Quantitative evaluation of best management practice (BMP) effectiveness can help stakeholders to make better watershed management decisions. However, such evaluations are always challenging as they require complex algorithms to simulate the relevant hydrological processes, crop growth and the corresponding pollutant transport pathways in order to evaluate potential BMPs and select the best one for the specific field conditions. In this study, a web-based interface (CalBMP) was developed to predict BMP effectiveness in California, focusing on pesticide modeling at the field scale. With built-in databases for soil, weather, crop, pesticides, and BMPs, users can run simulations for baseline and BMP scenarios using their site-specific field conditions by simply providing the field information, such as zip code, soil, crop management, and pesticide application data. CalBMP uses PRZM5 + , a USEPA model, to simulate pesticide transport and fate at the field edge. The CalBMP simulations were validated based on measurements from an alfalfa field study. The results indicated that the CalBMP interface could reasonably simulate the runoff and adsorbed pesticide loss leaving the field with default parameters from previously known field parameters or public databases. CalBMP underestimated sediment erosion, possibly due to uncertainties in field measurements or inaccurate simulation of the temporal distribution of flood irrigation. CalBMP is likely to underestimate pesticides with greater solubility, such as diuron, because PRZM5 + uses the simplified instantaneous equilibrium sorption model. In addition, a strawberry field study was adopted to demonstrate the capability of the CalBMP interface for simulating BMP effectiveness (pesticide reduction percentage in the main pathways) with easy-to-understand graphs and tables. The results indicated that users can easily compare and review the results from multiple scenarios, which could facilitate the decision-making process for mitigating the amount of active ingredient bifenthrin leaving the field. The CalBMP tool provides useful information on pesticide runoff potential and BMP selection at the field scale. With increasingly stringent regulations for water quality protection, CalBMP will add to the growers’ toolbox for minimizing the environmental impacts from their inevitable pesticide usage.

Measurement uncertainty in a national forest inventory: results from the northern region of the USA

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions.

How could simulated dewatering of slurry mitigate nitrous oxide emissions from fall and spring injections? – A modelling study in a Chernozem soil in Western Canada

Process-based ecosystem models, such as ecosys, can be useful tools to gain insights and accurately project nitrous oxide (N2O) inventories in national, regional and global scales, and to explore potential emission reduction strategies. Our objectives are to investigate how the ecosys model simulate the effects of fall and spring slurry injections on N2O production and if de-watering slurry could become a potential N2O mitigation strategy for both fall and spring injections. The ecosys model was used to simulate hourly N2O fluxes from 2014 to 2017 in a cropping system with and without slurry (fall and spring additions) in comparison with field measurements in Alberta, Canada. Furthermore, we performed simulations of de-watered fall and spring slurry applications in the same scenarios. Our results showed ecosys adequately simulated soil temperatures and moisture contents at 10 and 20 cm depths [correlation coefficients (r) ≥ 0.929 for temperatures; r ≥ 0.529 for moistures]. The divergences of modelled and measured soil water contents during spring thaws could be attributed to uncertainties in model inputs for soil hydrological parameters as well as uncertainties in field measurements. The model captured reasonably well the dynamics of N2O fluxes from soils receiving fall and spring slurry (r = 0.356). However, the concurrent discrepancies of N2O fluxes between modelled and measured values during the wetter spring thaw of 2017 might be a result of an unsatisfactory simulation of snowmelt infiltration and runoff. Compared to whole slurry, simulated de-watered slurry resulted in considerable reductions in cumulative N2O emissions by 16–36 and 23–29% for fall and spring slurry injections, respectively. The model results indicate that de-watering slurry would potentially be an efficient emission mitigation strategy; however, there is still a paucity of studies addressing the feasibility of dewatering as a practice and further research can focus on this knowledge gap.

Scale Invariance of Albedo‐Based Wind Friction Velocity

AbstractObtaining reliable estimates of aerodynamic roughness is necessary to interpret and accurately predict aeolian sediment transport dynamics. However, inherent uncertainties in field measurements and models of surface aerodynamic properties continue to undermine aeolian research, monitoring, and dust modeling. A new relation between aerodynamic shelter and land surface shadow has been established at the wind tunnel scale, enabling the potential for estimates of wind erosion and dust emission to be obtained across scales from albedo data. Here, we compare estimates of wind friction velocity (u*) derived from traditional methods (wind speed profiles) with those derived from the albedo model at two separate scales using bare soil patch (via net radiometers) and landscape (via Moderate Resolution Imaging Spectroradiometer [MODIS] 500 m) data sets. Results show that profile‐derived estimates of u* are highly variable in anisotropic surface roughness due to changes in wind direction and fetch. Wind speed profiles poorly estimate soil surface (bed) wind friction velocities necessary for aeolian sediment transport research and modeling. Albedo‐based estimates of u* at both scales have small variability because the estimate is integrated over a defined, fixed area and resolves the partition of wind momentum between roughness elements and the soil surface. We demonstrate that the wind tunnel‐based calibration of albedo for predicting wind friction velocities at the soil surface (us*) is applicable across scales. The albedo‐based approach enables consistent and reliable drag partition correction across scales for model and field estimates of us* necessary for wind erosion and dust emission modeling.

Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements

The Sentinel-3 mission launched its first satellite Sentinel-3A in 2016 to be followed by Sentinel-3B and Sentinel-3C to provide long-term operational measurements over Earth. Sentinel-3A and 3B are in full operational status, allowing global coverage in less than two days, usable to monitor optical water quality and provide data for environmental studies. However, due to limited ground truth data, the product quality has not yet been analyzed in detail with the fiducial reference measurement (FRM) dataset. Here, we use the fully characterized ground truth FRM dataset for validating Sentinel-3A Ocean and Land Colour Instrument (OLCI) radiometric products over optically complex Estonian inland waters and Baltic Sea coastal areas. As consistency between satellite and local data depends on uncertainty in field measurements, filtering of the in situ data has been made based on the uncertainty for the final comparison. We have compared various atmospheric correction methods and found POLYMER (POLYnomial-based algorithm applied to MERIS) to be most suitable for optically complex waters under study in terms of product accuracy, amount of usable data and also being least influenced by the adjacency effect.

Modelling canopy gap probability, foliage projective cover and crown projective cover from airborne lidar metrics in Australian forests and woodlands

Tree canopy density metrics (TCDM) derived from airborne lidar data are used in a range of crucial environmental monitoring, forestry and natural resource management applications. The derivation of spatially and temporally consistent TCDM, however, typically requires field calibration to account for differences in instrument/survey parameters. Lidar surveys with no coincident field measurements consequently will have an unknown error associated with TCDM limiting their application. In this study, we analysed an extensive set of lidar captures with coincident field data to determine the lidar TCDM that best match the canopy gap probability (Pgap), foliage projective cover (FPC) and crown projective cover (CPC). Furthermore, we developed and evaluated models designed to reduce the bias introduced by variations in lidar instrument and survey acquisition parameters. The dataset incorporated 148 field sites (100 m diameter circular plots) coincident with 13 different lidar surveys between 2008 and 2015, distributed across a range of Australian forests and woodlands. The best lidar metric for 1 − Pgap, achieving a root mean square error (RMSE) of 6.7% with 95% confidence intervals (CI) of 6.1–7.3%, was the proportion of all returns greater than a canopy height threshold (tcanopy) of 1.5 m above ground (dall). The best metric for FPC (RMSE = 6.0%, CI = 5.3–6.7%) used the proportion of returns, weighted as the fraction of the number of returns recorded from each pulse (dweighted), with tcanopy of 1.7 m. The best metric for CPC (RMSE = 7.0%, CI = 6.4–7.7%) was the proportion of 0.5 m pixels greater than 0.8 m above the ground, for an interpolated canopy height model (dinterp). Overall bias for these metrics was low (~1%), however, the bias for individual surveys varied significantly. For example, for one survey dall consistently underestimated 1 − Pgap with a bias of −8.3%, while a different survey consistently overestimated 1 − Pgap with a bias of 3.8%. Elastic net regression models, using instrument, survey and plot parameters as predictor variables, were unable to consistently remove the bias. No relationships could be discerned between lidar parameters and the bias between lidar metrics and field measurements, potentially due to complex interactions between parameters, the spatial scale of the field plots, and uncertainties in field measurements and lidar attributes. Although the bias could not be modelled, the results provide metrics to derive Pgap, FPC and CPC with less than 10% error from lidar surveys captured with similar parameters across Australia (>600,000 km2).

Investigating the Accuracy of One‐Dimensional Volcanic Plume Models using Laboratory Experiments and Field Data

AbstractDuring volcanic eruptions, model predictions of plume height are limited by the accuracy of entrainment coefficients used in many plume models. Typically, two parameters are used, α and β, which relate the entrained air speed to the jet speed in the axial and cross‐flow directions, respectively. To improve estimates of these parameters, wind tunnel experiments have been conducted for a range of cross‐wind velocities and turbulence conditions. Measurements are compared directly to computations from the 1‐D plume model, Plumeria, in the near‐field, bending region of the jet. Entrainment coefficients are determined through regression analysis, demonstrating optimal combinations of effective α and β values. For turbulent conditions, all wind speeds overlapped at a single combination, α = 0.06 and β=0.46, each of which are slightly reduced from standard values. Refined coefficients were used to model plume heights for 20 historical eruptions. Model accuracy improves modestly in most cases, agreeing to within 3 km with observed plume heights. For weak eruptions, uncertainty in field measurements can outweigh the effects of these refinements, illustrating the challenge of applying plume models in practice.

Variability and Uncertainty Challenges in Scaling Imaging Spectroscopy Retrievals and Validations from Leaves Up to Vegetation Canopies.

Imaging spectroscopy of vegetation requires methods for scaling and generalizing optical signals that are reflected, transmitted and emitted in the solar wavelength domain from single leaves and observed at the level of canopies by proximal sensing, airborne and satellite spectroradiometers. The upscaling embedded in imaging spectroscopy retrievals and validations of plant biochemical and structural traits is challenged by natural variability and measurement uncertainties. Sources of the leaf-to-canopy upscaling variability and uncertainties are reviewed with respect to: (1) implementation of retrieval algorithms and (2) their parameterization and validation of quantitative products through in situ field measurements. The challenges are outlined and discussed for empirical and physical leaf and canopy radiative transfer modelling components, considering both forward and inverse modes. Discussion on optical remote sensing validation schemes includes also description of a multiscale validation concept and its advantages. Impacts of intraspecific and interspecific variability on collected field and laboratory measurements of leaf biochemical traits and optical properties are demonstrated for selected plant species, and field measurement uncertainty sources are listed and discussed specifically for foliar pigments and canopy leaf area index. The review concludes with the main findings and suggestions as how to reduce uncertainties and include variability in scaling vegetation imaging spectroscopy signals and functional traits of single leaves up to observations of whole canopies.

How Uncertainty in Field Measurements of Ice Nucleating Particles Influences Modeled Cloud Forcing

Field and laboratory measurements using continuous flow diffusion chambers (CFDCs) have been used to construct parameterizations of the number of ice nucleating particles (INPs) in mixed-phase and completely glaciated clouds in weather and climate models. Because of flow nonidealities, CFDC measurements are subject to systematic low biases. Here, the authors investigate the effects of this undercounting bias on simulated cloud forcing in a global climate model. The authors assess the influence of measurement variability by constructing a stochastic parameterization framework to endogenize measurement uncertainty. The authors find that simulated anthropogenic longwave ice-bearing cloud forcing in a global climate model can vary up to 0.8 W m−2and can change sign from positive to negative within the experimentally constrained bias range. Considering the variability in the undercounting bias, in a range consistent with recent experiments, leads to a larger negative cloud forcing than that when the variability is ignored and only a constant bias is assumed.

Mapping the absolute magnetic field and evaluating the quadratic Zeeman-effect-induced systematic error in an atom interferometer gravimeter

Precisely evaluating the systematic error induced by the quadratic Zeeman effect is important for developing atom interferometer gravimeters aiming at an accuracy in the regime ( ). This paper reports on the experimental investigation of Raman spectroscopy-based magnetic field measurements and the evaluation of the systematic error in the Gravimetric Atom Interferometer (GAIN) due to quadratic Zeeman effect. We discuss Raman duration and frequency step size dependent magnetic field measurement uncertainty, present vector light shift (VLS) and tensor light shift (TLS) induced magnetic field measurement offset, and map the absolute magnetic field inside the interferometer chamber of GAIN with an uncertainty of 0.72 nT and a spatial resolution of 12.8 mm. We evaluate the quadratic Zeeman effect induced gravity measurement error in GAIN as . The methods shown in this paper are important for precisely mapping the absolute magnetic field in vacuum and reducing the quadratic Zeeman effect induced systematic error in Raman transition-based precision measurements, such as atomic interferometer gravimeters.

Optimization of experiment settings in ferromagnetic resonance measurements

In a ferromagnetic resonance experiment, the frequency vs resonance field data is fitted to the resonance condition formula for extraction of the effective magnetization and gyromagnetic ratio of the ferromagnetic material under test. We found that the fitting may result in significant error in some cases. We studied the influence of the number of data points, frequency range and noise level on the precision of the fittings by means of numerical simulation. The results suggest that the fitting is sensitive to the frequency range but an optimal frequency range can be estimated. The precision of the fitting is found to be proportional to the uncertainty in field measurements. As one increases the number of data points, the precision increases sharply in the beginning but the effect vanishes when the number of data points exceeds 40. The findings offer practical guidance for the design of ferromagnetic resonance experiments, which is a popular technique for ferromagnetic material characterization.

Managing Measurement Uncertainty in Building Acoustics

In general, uncertainties should preferably be determined following the principles laid down in ISO/IEC Guide 98-3, the Guide to the expression of uncertainty in measurement (GUM:1995). According to current knowledge, it seems impossible to formulate these models for the different quantities in building acoustics. Therefore, the concepts of repeatability and reproducibility are necessary to determine the uncertainty of building acoustics measurements. This study shows the uncertainty of field measurements of a lightweight wall, a heavyweight floor, a façade with a single glazing window and a façade with double glazing window that were analyzed by a Round Robin Test (RRT), conducted in a full-scale experimental building at ITC-CNR (Construction Technologies Institute of the National Research Council of Italy). The single number quantities and their uncertainties were evaluated in both narrow and enlarged range and it was shown that including or excluding the low frequencies leads to very significant differences, except in the case of the sound insulation of façades with single glazing window. The results obtained in these RRTs were compared with other results from literature, which confirm the increase of the uncertainty of single number quantities due to the low frequencies extension. Having stated the measurement uncertainty for a single measurement, in building acoustics, it is also very important to deal with sampling for the purposes of classification of buildings or building units. Therefore, this study also shows an application of the sampling included in the Italian Standard on the acoustic classification of building units on a serial type building consisting of 47 building units. It was found that the greatest variability is observed in the façade and it depends on both the great variability of window’s typologies and on workmanship. Finally, it is suggested how to manage the uncertainty in building acoustics, both for one single measurement and a campaign of measurements to determine the acoustic classification of buildings or building units.

Application of the Nordtest method for “real-time” uncertainty estimation of on-line field measurement

Field sensor measurements are becoming more common for environmental monitoring. Solutions for enhancing reliability, i.e. knowledge of the measurement uncertainty of field measurements, are urgently needed. Real-time estimations of measurement uncertainty for field measurement have not previously been published, and in this paper, a novel approach to the automated turbidity measuring system with an application for "real-time" uncertainty estimation is outlined based on the Nordtest handbook's measurement uncertainty estimation principles. The term real-time is written in quotation marks, since the calculation of the uncertainty is carried out using a set of past measurement results. There are two main requirements for the estimation of real-time measurement uncertainty of online field measurement described in this paper: (1) setting up an automated measuring system that can be (preferably remotely) controlled which measures the samples (water to be investigated as well as synthetic control samples) the way the user has programmed it and stores the results in a database, (2) setting up automated data processing (software) where the measurement uncertainty is calculated from the data produced by the automated measuring system. When control samples with a known value or concentration are measured regularly, any instrumental drift can be detected. An additional benefit is that small drift can be taken into account (in real-time) as a bias value in the measurement uncertainty calculation, and if the drift is high, the measurement results of the control samples can be used for real-time recalibration of the measuring device. The procedure described in this paper is not restricted to turbidity measurements, but it will enable measurement uncertainty estimation for any kind of automated measuring system that performs sequential measurements of routine samples and control samples/reference materials in a similar way as described in this paper.

Application of the Monte Carlo Method for the Estimation of Uncertainty in Radiofrequency Field Spot Measurements

Abstract The objective of the present work is the application of the Monte Carlo method (GUMS1) for evaluating uncertainty in electromagnetic field measurements and the comparison of the results with the ones obtained using the 'standard' method (GUM). In particular, the two methods are applied in order to evaluate the field measurement uncertainty using a frequency selective radiation meter and the Total Exposure Quotient (TEQ) uncertainty. Comparative results are presented in order to highlight cases where GUMS1 results deviate significantly from the ones obtained using GUM, such as the presence of a non-linear mathematical model connecting the inputs with the output quantity (case of the TEQ model) or the presence of a dominant nonnormal distribution of an input quantity (case of U-shaped mismatch uncertainty). The deviation of the results obtained from the two methods can even lead to different decisions regarding the conformance with the exposure reference levels.

Uncertainty of façade sound insulation in buildings by a Round Robin Test

The uncertainty of field measurements of a façade was evaluated by a Round Robin Test (RRT) conducted in a full-scale experimental building at the Construction Technologies Institute of the National Research Council of Italy (ITC-CNR). Each of the 9 teams involved in the RRT replicated the tests 5 times, for a total of 45 measurements, while reverberation time was repeated 110 times. Both for façade sound insulation and reverberation time the main variations in the one-third octave bands were found in the low frequencies range. The study was also focused on the evaluation of single number quantities (SNQs) and their uncertainties. Single number quantities were evaluated in both narrow (from 100 to 3150Hz) and extended (from 50 to 5000Hz) range. Concerning the SNQs and their uncertainties, no significant differences were observed whether the low frequencies were included or not, unlike the case of airborne sound insulation (investigated in the first part of this study). The uncertainty results were compared with the relevant standards and with literature results. Based on these comparisons, it was highlighted that the standard deviation of reproducibility of façade elements is not adequately reflected in the ISO 12999-1 and further research is needed to specify the in situ standard deviation of reproducibility for façade elements.

Fire emission uncertainties and their effect on smoke dispersion predictions: a case study at Eglin Air Force Base, Florida, USA

Prescribed burning is practiced to benefit ecosystems but the resulting emissions can adversely affect air quality. A better understanding of the uncertainties in emission estimates and how these uncertainties affect smoke predictions is critical for model-based decision making. This study examined uncertainties associated with estimating fire emissions and how they affected smoke concentrations downwind from a prescribed burn that was conducted at Eglin Air Force Base in Florida, US. Estimated variables used in the modelled emission calculation were compared with field measurements. Fuel loadings, fuel consumption and emission factors were simulated using Photo Series, Consume, and previously published values. A plume dispersion model was used to study the effect of uncertainty in emissions on ground concentration prediction. The fire emission models predicted fuel loading, fuel consumption and emission factor within 15% of measurements. Approximately 18% uncertainty in field measurements of PM2.5 emissions and 36% uncertainty attributed to variability in emission estimating models resulted respectively in 20% and 42% ground level PM2.5 concentration uncertainties in dispersion modelling using Daysmoke. Uncertainty in input emissions influences the concentrations predicted by the smoke dispersion model to the same degree as does the model’s inherent uncertainty due to turbulence.

Estimativa de incerteza em ensaios de ruído de impacto: posição dos equipamentos em medições em campo

A precisão metrológica em ensaios em campo de acústica de edifícios é uma questão atual, com necessidade ampla discussão sobre as variáveis envolvidas que podem gerar dúvidas nos resultados. Nesse contexto, este trabalho analisa as incertezas de medições de ruído de impacto em campo. O foco do trabalho é a análise da influência do posicionamento dos equipamentos. As medições foram realizadas conforme as normas ISO 140-7 e ISO 140-14 em duas salas sobrepostas, separadas por uma laje de concreto maciço de 10cm de espessura. Foram consideradas dois grupos de variações no posicionamento da máquina de impactos e do microfone: distâncias mínimas das paredes definidas nas normas ISO e pontos centralizados no piso. As variações no posicionamento dos equipamentos geraram 64 resultados de níveis sonoros na sala de recepção, divididos em quatro grupos de resultados, a partir das medições na faixa de frequência entre 100 e 3.150 Hz. Para as análises foram utilizados os métodos da norma ISO 12999-1 e do Guia RELACRE/Portugal que expressam de formas diferentes as incertezas de medições acústicas em edificações. Os resultados são apresentados na forma de exemplos de aplicação em sistemas pisos ensaiados anteriormente, com diferentes comportamentos acústicos e consequentemente, com valores distintos de níveis de ruído de impacto padronizados ponderados corrigidos pela incerteza estimada. Neste estudo foi evidenciada e quantificada a influência do posicionamento dos equipamentos nos resultados de ensaios de ruído de impacto em campo.

Evaluation of the reaction artifacts in an annular denuder-based sampler resulting from the heterogeneous ozonolysis of naphthalene

The heterogeneous ozonolysis of naphthalene adsorbed on XAD-4 resin was studied using an annular denuder technique. The experiments involved depositing a known quantity of naphthalene on the XAD-4 resin and then measuring the quantity of the solid naphthalene that reacted away under a constant flow of gaseous ozone (0.064 to 4.9ppm) for a defined amount of time. All experiments were performed at room temperature (26 to 30°C) and atmospheric pressure. The kinetic rate coefficient for the ozonolysis reaction of naphthalene adsorbed on XAD-4 resin is reported to be (10.1 ± 0.4) × 10(-19)cm(3)molecule(-1)s(-1) (error is 2σ, precision only). This value is five times greater than the currently recommended literature value for the homogeneous gas phase reaction of naphthalene with ozone. The obtained rate coefficient is used to evaluate reaction artifacts from field concentration measurements of naphthalene, acenaphthene, and phenanthrene. The observed uncertainties associated with field concentration measurements of naphthalene, acenaphthene, and phenanthrene are reported to be much higher than the uncertainties associated with the artifact reactions. Consequently, ozone reaction artifact appears to be negligible compared to the observed field measurement uncertainty results.

A statistical method for determining the volume of volcanic fall deposits

Volumes of tephra-fall deposits are difficult to determine due to the commonly poor preservation of proximal and distal areas of the deposit. Typically, these volumes are found by extrapolating thinning trends found from isopach maps drawn for the areas of the deposits that are preserved. However, the construction of isopach contours is dependent on subjective interpretation of field measurements and can be highly variable. Here, we have investigated the spatial correlation relationships of thickness measurements from fall deposits to the vent location to produce a purely statistical method to objectively determine the volume of a fall deposit without the production of isopach maps. Integration of a log linear regression model for thickness measurements with distance from the vent is applied to the field measurements without any prior interpretation, and data and model uncertainty has been accounted for using Bayesian methods. Eruption volumes calculated from our method correspond well to those previously determined by alternative approaches for the deposits of Fogo A, Azores; Askja 1875, Iceland; Santa Maria 1902, Guatemala; and Pinatubo 1991, Philippines. The quantification of uncertainty in field measurements and model error, and the removal of subjectivity incurred in the production of isopach maps suggest that the method presented here can offer benefits in determining the volumes of deposits.

Uncertainty analysis by a Round Robin Test of field measurements of sound insulation in buildings: Single numbers and low frequency bands evaluation - Airborne sound insulation

The uncertainty of field measurements of a lightweight wall and a heavy floor was analysed by Round Robin Test (RRT), conducted in a full-scale experimental building at ITC-CNR. Each of the 9 teams involved in the I-RRT replicates the tests 5 times, for a total of 45 measurements, while the repetitions of reverberation time were 110. Both for sound insulation and reverberation time the main variations are in the low frequency range. The differences between D, R', Dn and DnT and their reproducibility and repeatability standard deviations values were also analysed. The study is also focused on the single numbers evaluation: true value and uncertainty. Single numbers were evaluated in both narrow and extended range. The extension to low frequencies implies a variation in single number values that reaches its maximum in the case of X +Ctr in the extended range. This is because this index is the most influenced by low frequencies. Thus the measurement uncertainty at low frequencies has to be more deeply investigated, before including the low frequency range in the on-field measurements