Inter-unit Variability Research Articles

Using a Contemporary Portable Metabolic Gas Exchange System for Assessing Energy Expenditure: A Validity and Reliability Study.

There are several methods available to assess energy expenditure, all associated with inherent pros and cons that must be adequately considered for use in specific environments and populations. A requirement of all methods is that they must be valid and reliable in their capability to accurately measure oxygen consumption (VO2) and carbon dioxide production (VCO2). The purpose of this study was to evaluate the reliability and validity of the mobile CO2/O2 Breath and Respiration Analyzer (COBRA) relative to a criterion system (Parvomedics TrueOne 2400®, PARVO) with additional measurements to compare the COBRA to a portable system (Vyaire Medical, Oxycon Mobile®, OXY). Fourteen volunteers with a mean of 24 years old, body weight of 76 kg, and a VO2peak of 3.8 L∙min-1 performed four repeated trials of progressive exercises. Simultaneous steady-state measurements of VO2, VCO2, and minute ventilation (VE) by the COBRA/PARVO and OXY systems were conducted at rest, while walking (23-36% VO2peak), jogging (49-67% VO2peak), and running (60-76% VO2peak). Data collection was randomized by the order of system tested (COBRA/PARVO and OXY) and was standardized to maintain work intensity (rest to run) progression across study trials and days (two trials/day over two days). Systematic bias was examined to assess the accuracy of the COBRA to PARVO and OXY to PARVO across work intensities. Intra- and inter-unit variability were assessed with interclass correlation coefficients (ICC) and a 95% limit of agreement intervals. The COBRA and PARVO produced similar measures for VO2 (Bias ± SD, 0.01 ± 0.13 L·min-1; 95% LoA, (-0.24, 0.27 L·min-1); R2 = 0.982), VCO2 (0.06 ± 0.13 L·min-1; (-0.19, 0.31 L·min-1); R2 = 0.982), VE (2.07 ± 2.76 L·min-1; (-3.35, 7.49 L·min-1); R2 = 0.991) across work intensities. There was a linear bias across both the COBRA and OXY with increased work intensity. The coefficient of variation for the COBRA ranged from 7 to 9% across measures for VO2, VCO2, and VE. COBRA was reliable across measurements for VO2 (ICC = 0.825; 0.951), VCO2 (ICC = 0.785; 0.876), and VE (ICC = 0.857; 0.945) for intra-unit reliability, respectively. The COBRA is an accurate and reliable mobile system for measuring gas exchange at rest and across a range of work intensities.

A Computational Model of a Single Auditory Nerve Fiber for Electric-Acoustic Stimulation

Cochlear implant (CI) recipients with preserved acoustic low-frequency hearing in the implanted ear are a growing group among traditional CI users who benefit from hybrid electric-acoustic stimulation (EAS). However, combined ipsilateral electric and acoustic stimulation also introduces interactions between the two modalities that can affect the performance of EAS users. A computational model of a single auditory nerve fiber that is excited by EAS was developed to study the interaction between electric and acoustic stimulation. Two existing models of sole electric or acoustic stimulation were coupled to simulate responses to combined EAS. Different methods of combining both models were implemented. In the coupled model variant, the refractoriness of the simulated fiber leads to suppressive interaction between electrically evoked and acoustically evoked spikes as well as spontaneous activity. The second model variant is an uncoupled EAS model without electric-acoustic interaction. By comparing predictions between the coupled and the noninteracting EAS model, it was possible to infer electric-acoustic interaction at the level of the auditory nerve. The EAS model was used to simulate fiber populations with realistic inter-unit variability, where each unit was represented by the single-fiber model. Predicted thresholds and dynamic ranges, spike rates, latencies, jitter, and vector strengths were compared to empirical data. The presented EAS model provides a framework for future studies of peripheral electric-acoustic interaction.

Inter-unit reliability of IMU Step metrics using IMeasureU Blue Trident inertial measurement units for running-based team sport tasks

ABSTRACT The aim of this study was to determine the inter-unit reliability of IMU Step biomechanical load monitoring metrics using IMeasureU Blue Trident inertial measurement units in tasks common to running-based team sports. Knowledge of variability between units is required before researchers and practitioners can make informed decisions on “true” differences between limbs. Sixteen male college soccer players performed five running-based tasks, generating 224 trials and 17,012 steps. Data were analysed for each task and for the whole session, investigating six IMU Step metrics: step count; impact load; bone stimulus; and low, medium and high intensity steps. Inter-unit reliability was excellent (ICC ≥ 0.90) for 21 out of 26 metrics, and good (0.83 ≤ ICC ≤ 0.86) for all other metrics except for Yo-Yo impact load (ICC = 0.79) which was acceptable. These findings confirm the inter-unit reliability of IMU Step metrics using IMeasureU Blue Trident inertial measurement units for running-based team sports. Now that inter-unit variability has been quantified, researchers and practitioners can use this information when interpreting inter-limb differences for monitoring external biomechanical training load.

Correction of lateral response artifacts from flatbed scanners for dual-channel radiochromic film dosimetry.

In this study, we evaluated the inter-unit variability of the lateral response artifact for multiple flatbed scanners, focusing on the dual-channel method, and investigated the correction method of the lateral non-uniformity. Four scanners with A3+ paper-size and five scanners with A4 paper-size were evaluated. To generate the dose–response curves, small pieces of the Gafchromic EBT3 and EBT-XD films were irradiated, and five of the pieces were repeatedly scanned by moving them on the scanner to evaluate the lateral non-uniformity. To calculate the dose distribution accounting for the lateral non-uniformity, linear functions of the correction factor, representing the difference between the pixel values at offset position and the scanner midline, were calculated for red and blue color channels at each lateral position. Large variations of the lateral non-uniformity among the scanners were observed, even for the same model of scanner. For high dose, red color showed pixel value profiles similar to symmetric curves, whereas the profiles for low dose were asymmetric. The peak positions changed with dose. With correction of the lateral non-uniformity, the dose profiles of the pyramidal dose distribution measured at various scanner positions and that calculated with a treatment planning system showed almost identical profile shapes at all high-, middle- and low-dose levels. The dual-channel method used in this study showed almost identical dose profiles measured with all A3+ and A4 paper-size scanners at any positions when the corrections were applied for each color channel.

Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile

Integration of low-cost air quality sensors with the internet of things (IoT) has become a feasible approach towards the development of smart cities. Several studies have assessed the performance of low-cost air quality sensors by comparing their measurements with reference instruments. We examined the performance of a low-cost IoT particulate matter (PM10 and PM2.5) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM10–PM2.5 sensor (SDS011), a temperature and relative humidity sensor (BME280) and an IoT board (ESP8266/Node MCU). Field tests were conducted at three regulatory monitoring stations during the 2018 austral winter and spring seasons. The sensors at each site were operated in parallel with continuous reference air quality monitors (BAM 1020 and TEOM 1400) and a filter-based sampler (Partisol 2000i). Variability between sensor units (n = 7) and the correlation between the sensor and reference instruments were examined. Moderate inter-unit variability was observed between sensors for PM2.5 (normalized root-mean-square error 9–24%) and PM10 (10–37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM2.5 (R2 0.47–0.86) than PM10 (0.24–0.56). The correlations (R2) between the 24-h PM2.5 averages from the sensors and reference instruments were 0.63–0.87 for continuous monitoring and 0.69–0.93 for filter-based samplers. Correlation analysis revealed that sensors tended to overestimate PM concentrations in high relative humidity (RH > 75%) and underestimate when RH was below 50%. Overall, the prototype evaluated exhibited adequate performance and may be potentially suitable for monitoring daily PM2.5 averages after correcting for RH.

Inter-unit variability of multi-leaf collimator parameters for IMRT and VMAT treatment planning: a multi-institutional survey

Modern treatment machines have shown small inter-unit variability regarding beam data. Recently, vendor-provided average beam data, such as the Representative Beam Data (RBD) of the TrueBeam (Varian Medical Systems, Palo Alto, CA, USA), has been used for modeling of the Eclipse (Varian Medical Systems) treatment planning system. However, RBD does not provide multi-leaf collimator (MLC) parameters, such as MLC leaf transmission factor (LTF) and dosimetric leaf gap (DLG). We performed a web-based multi-institutional survey to investigate these parameters as well as the measurement protocols and customization of the parameters for intensity-modulated radiotherapy (IMRT) and/or volumetric modulated radiotherapy (VMAT) commissioning. We collected 69 sets of linear accelerator (linac) data from 58 institutions. In order to measure MLC parameters, most institutions used farmer-type ionization chambers with a sensitive volume of 0.6 cm3, water phantoms, source surface distance of 90 cm with 10 cm depth, and a vendor-provided plan. The LTF showed small inter-unit variabilities, although the DLG showed large variations. For optimization of the parameters for IMRT/VMAT calculations, DLG values were upwardly adjusted at many institutions, whereas the LTF values were modestly changed. We clarified that MLC parameters were measured under the same conditions at more than half of the facilities. Most institutions customized parameters in a similar manner for IMRT/VMAT. The median measured and customized values obtained in our study will be valuable to verify MLC installation accuracy and to shorten the iterative processes of finding the optimal values.

Evaluation of the accuracy and precision of a new generation indirect calorimeter in canopy dilution mode.

Indirect calorimetry (IC) is the only way to measure in real time energy expenditure (EE) and to optimize nutrition support in acutely and chronically ill patients. Unfortunately, most of the commercially available indirect calorimeters are rather complex to use, expensive and poorly accurate and precise. Therefore, an innovative device (Q-NRG®, COSMED, Rome, Italy) that matches clinicians' needs has been developed as part of the multicenter ICALIC study supported by the two academic societies ESPEN and ESICM. The aim of this study was to evaluate the accuracy and intra- and inter-unit precision of this new device in canopy dilution mode invitro and in spontaneously breathing adults. Accuracy and precision of oxygen consumption (VO2) and carbon dioxide production (VCO2) measurements were evaluated invitro and in 15 spontaneously breathing healthy adults by interchanging three Q-NRG® units in a random order. Invitro validation was performed by gas exchange simulation using high-precision gas mixture and mass flow controller. Accuracy was calculated as error of measured values against expected ones based on volume of gas infused. Respiratory coefficient (RQ) accuracy was furthermore assessed using the ethanol-burning test. To evaluate the intra- and inter-unit precisions, the coefficient of variation (CV%=SD/Mean*100) was calculated, respectively, from the mean±SD or the mean±SD of the three mean values of VO2, VCO2, RQ and EE measured by each Q-NRG® units. Invivo accuracy measurement of the Q-NRG® was assessed by simultaneous comparison with mass spectrometry (MS) gas analysis, using Bland-Altman plot, Pearson correlation and paired t-test (significance level of p=0.05). Invitro evaluation of the Q-NRG® accuracy showed measurement errors <1% for VO2, VCO2 and EE and <1.5% for RQ. Evaluation of the intra- and inter-unit precision showed CV% ≤1% for VO2 and EE and CV% ≤1.5% for VCO2 and RQ measurements, except for one Q-NRG® unit where CV% was 2.3% for VO2 and 3% for RQ. Very good inter-unit precision was confirmed invivo with CV% equal to 2.4%, 3%, 2.8% and 2.3% for VO2, VCCO2, RQ and EE, respectively. Comparison with MS showed correlation of 0.997, 0.987, 0.913 and 0.997 for VO2, VCO2, RQ and EE respectively (p≤0.05). Mean deviation of paired differences was 1.6±1.4% for VO2, -1.5±2.5% for VCO2, -3.1±2.6% for RQ and 0.9±1.4% for EE. Both invitro and invivo measurements of VO2, VCO2, RQ and EE on three Q-NRG® units showed minimal differences compared to expected values and MS and very low intra- and inter-unit variability. These results confirm the very good accuracy and precision of the Q-NRG® indirect calorimeter in canopy dilution mode in spontaneously breathing adults.

Sweat Sodium Concentration: Inter-Unit Variability of a Low Cost, Portable, and Battery Operated Sodium Analyzer.

The B-722 Laqua Twin is a low cost, portable, and battery operated sodium analyzer, which can be used for the assessment of sweat sodium concentration. The Laqua Twin is reliable and provides a degree of accuracy similar to more expensive analyzers; however, its interunit measurement error remains unknown. The purpose of this study was to compare the sodium concentration values of 70 sweat samples measured using three different Laqua Twin units. Mean absolute errors, random errors and constant errors among the different Laqua Twins ranged respectively between 1.7 mmol/L to 3.5 mmol/L, 2.5 mmol/L to 3.7 mmol/L and -0.6 mmol/L to 3.9 mmol/L. Proportional errors among Laqua Twins were all < 2%. Based on a within-subject biological variability in sweat sodium concentration of ± 12%, the maximal allowable imprecision among instruments was considered to be £ 6%. In that respect, the within (2.9%), between (4.5%), and total (5.4%) measurement error coefficient of variations were all < 6%. For a given sweat sodium concentration value, the largest observed difference in mean and lower and upper bound error of measurements among instruments were, respectively, 4.7 mmol/L, 2.3 mmol/L, and 7.0 mmol/L. In conclusion, our findings show that the interunit measurement error of the B-722 Laqua Twin is low and methodologically acceptable.

Standard concentration infusions in paediatric intensive care: the clinical approach.

To identify the most appropriate clinical concentrations required by our paediatric intensive care unit (PICU) population with regard to accuracy of delivery and overall fluid allowance. Firstly a matrix was used to balance the concentration, dose and infusion volume (weight range 1.5-50 kg). Results were further refined considering: patient fluid allowance based on fluid volume targets, infusion pump accuracy and challenging each infusion against clinical scenarios requiring administration of multiple drug infusions found in PICU. Consideration was given to the standard concentrations routinely used in adults, in order to assess whether alignment with paediatrics was possible for some of the concentrations proposed. Finally a risk assessment of the infusions was conducted using the NPSA 20 tool. Twenty-five drugs identified as the most commonly used intravenous infusions in the unit. For the majority of the medicines, three weight bands of standard concentrations were necessary to cover the children's weight ranges and kept within predefined fluid requirements and accuracy of delivery. This work shows a patient focused systematic approach for defining and evaluating standardised concentrations in intensive care children.

Pyrosequencing analysis of bacterial diversity in dental unit waterlines

Some infections cases due to exposure to output water from dental unit waterlines (DUWL) have been reported in the literature. However, this type of healthcare-associated risk has remained unclear and up until now the overall bacterial composition of DUWL has been poorly documented. In this study, 454 high-throughput pyrosequencing was used to investigate the bacterial community in seven dental offices (N = 7) and to identify potential bacterial pathogenic sequences. Dental unit waters (DUW) were collected from the tap water supplying units (Incoming Water; IW) to the output exposure point of the turbine handpiece (Output water; OW) following a stagnation period (OWS), and immediately after the last patient of the sampling day (OWA). A high bacterial diversity was revealed in DUW with 394 operational taxonomic units detected at the genus level. In addition to the inter-unit variability observed, results showed increased total bacterial cell concentration and shifts in bacterial community composition and abundance at the genus level, mainly within the Gamma- and Alpha-Proteobacteria class, as water circulated in the dental unit (DU). Results showed that 96.7%, 96.8% and 97.4% of the total sequences from IW, OWS and OWA respectively were common to the 3 defined water groups, thereby highlighting a common core microbiome. Results also suggested that stagnation and DU maintenance practices were critical to composition of the bacterial community. The presence of potentially pathogenic genera was detected, including Pseudomonas and Legionella spp. Emerging and opportunistic pathogenic genera such as Mycobacterium, Propionibacterium and Stenotrophomonas were likewise recovered in DUW. For the first time, an exhaustive evaluation of the bacterial communities present in DUW was performed taking into account the circulation of water within the DU. This study highlights an ignored diversity of the DUWL bacterial community. Our findings also contribute to a better appreciation of the potential infectious risk associated with dental care and suggest the importance of better managing microbial quality in DUW.

An expansive, cone-specific nonlinearity enabling the luminance motion system to process color-defined motion.

To conclude that there is a dedicated color motion system, the hypothesis that the luminance motion pathway is processing color motion due to some nonlinearity must be rejected. Many types of nonlinearities have been considered. Cavanagh and Anstis (1991) considered interunit variability in equiluminance, but they found that adding a color-defined modulation to a luminance-defined drifting modulation increased the contribution to motion. This color contribution to motion cannot be due to interunit variability in equiluminance alone because such a luminance artifact would increase the effective luminance contrast for some luminance-sensitive units and decrease it for the others, resulting in no additional contribution to motion on average. Cavanagh and Anstis considered this color contribution to motion as evidence of a dedicated color motion system, but here we show that such a color contribution to motion varies with the phase difference between the luminance and color modulations, which would not be expected if luminance- and color-defined motion were processed separately. Specifically, the contribution to motion was greater when the luminance and color modulations were aligned (i.e., 0 degrees or 180 degrees phase difference), than when they were not (90 degrees or 270 degrees phase difference). Such a luminance-color phase interaction was also observed when spatially interleaving luminance and color information, which suggests that the interaction occurs after some spatial integration (i.e., not at the photoreceptors). To our knowledge, this luminance-color phase interaction cannot be explained by any previously considered nonlinearity. However, it can be explained by an expansive nonlinearity occurring before the summation of the L- and M-cone pathways (i.e., before ganglion cells) and after some spatial integration (i.e., after the photoreceptors). We conclude that there is a nonlinearity that has not been considered before, enabling some color motion processing by the luminance motion system.

Variations in surgical management from a national bowel cancer screening programme

ObjectivePopulation screening for colorectal cancer (CRC) was introduced to Wales in October 2008. The aim of this study was to evaluate the early impact of screening on CRC services.DesignProspectively collected...

Inter-unit variability in two ParvoMedics TrueOne 2400 automated metabolic gas analysis systems

Knowing the inter-unit variability, especially the technological error, is important when using many physiological measurement systems, yet no such inter-unit analysis has been undertaken on duplicate automated gas analysis systems. This study investigated the inter-unit performance of two identical ParvoMedics TrueOne 2400 automated gas analysis systems during a range of submaximal steady-state exercises performed on an electromagnetic cycle ergometer. Fifteen adult males were tested on two separate days a rest, 30, 60, 90, and 120 Watts with the duplicate gas analysis units arranged (1) collaterally (2 min of steady-state expired gas was alternately passed through each system), and (2) simultaneously (identical steady-state expired gas was passed simultaneously through both systems). Total within-subject variation (biological + technological) was determined from the collateral tests, but the unique inter-unit variability (technological error between identical systems) was shown by the simultaneous tests. Absolute percentage errors (APE), coefficient of variations (CV), effect sizes and Bland–Altman analyses were undertaken on the metabolic data, including expired ventilation (V E), oxygen consumption (VO2) and carbon dioxide production (VCO2). The few statistically significant differences detected between the two duplicate systems were determined to have small or trivial effect sizes, and their magnitudes to be of little physiological importance. The total within-subject variations for VO2, VCO2 and V E each equated to a mean CV and mean APE value of ~4 and ~6 %, whilst the respective inter-unit technological errors equated to ~1.5 and ~2.1 %. The two ParvoMedics TrueOne 2400 systems demonstrated excellent inter-unit agreement.

The Inter- and Intra-Unit Variability of a Low-Cost GPS Data Logger/Receiver to Study Human Outdoor Walking in View of Health and Clinical Studies

PurposeThe present study evaluates the intra- and inter-unit variability of the GlobalSat® DG100 GPS data logger/receiver (DG100) when estimating outdoor walking distances and speeds.MethodsTwo experiments were performed using healthy subjects walking on a 400 m outdoor synthetic track. The two experiments consisted of two different outdoor prescribed walking protocols with distances ranging from 50 to 400 m. Experiment 1 examined the intra-unit variability of the DG100 (test-retest reproducibility) when estimating walking distances. Experiment 2 examined the inter-unit variability of four DG100 devices (unit to unit variability) when estimating walking distances and speeds.ResultsThe coefficient of variation [95% confidence interval], for the reliability of estimating walking distances, was 2.8 [2.5–3.2] %. The inter-unit variability among the four DG100 units tested ranged from 2.8 [2.5–3.2] % to 3.9 [3.5–4.4] % when estimating distances and from 2.7 [2.4–3.0] % to 3.8 [3.4–4.2] % when estimating speeds.ConclusionThe present study indicates that the DG100, an economical and convenient GPS data logger/receiver, can be reliably used to study human outdoor walking activities in unobstructed conditions. This device let facilitate the use of GPS in studies of health and disease.

Variability of GPS Units for Measuring Distance in Team Sport Movements

To examine the difference in distance measured by two global positioning system (GPS) units of the same model worn by the same player while performing movements common to team sports. Twenty elite Australian football players completed two trials of the straight line movement (10, 20, 40 m) at four speeds (walk, jog, stride, sprint), two trials of the changes of direction (COD) courses of two different frequencies (gradual and tight), and five trials of a team sport running simulation circuit. To assess inter-unit variability for total and high intensity running (HIR) distance measured in matches, data from eight field players were collected in three Australian Hockey League (AHL) matches during the 2009 season. Each subject wore two GPS devices (MinimaxX v2.5, Catapult, Australia) that collected position data at 5 Hz for each movement and match trial. The percentage difference ±90% confidence interval (CI) was used to determine differences between units. Differences (±90% CI) between the units ranged from 9.9 ± 4.7% to 11.9 ± 19.5% for straight line running movements and from 9.5 ± 7.2% to 10.7 ± 7.9% in the COD courses. Similar results were exhibited in the team sport circuit (11.1 ± 4.2%). Total distance (10.3 ± 6.2%) and HIR distance (10.3 ± 15.6) measured during the match play displayed similar variability. It is recommended that players wear the same GPS unit for each exercise session to reduce measurement error. The level of between-unit measurement error should be considered when comparing results from players wearing different GPS units.

Neural representations that support invariant object recognition.

Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) ‘average’ neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously.

Unit-specific calibration of Actigraph accelerometers in a mechanical setup – Is it worth the effort? The effect on random output variation caused by technical inter-instrument variability in the laboratory and in the field

BackgroundPotentially, unit-specific in-vitro calibration of accelerometers could increase field data quality and study power. However, reduced inter-unit variability would only be important if random instrument variability contributes considerably to the total variation in field data. Therefore, the primary aim of this study was to calculate and apply unit-specific calibration factors in multiple accelerometers in order to examine the impact on random output variation caused by inter-instrument variability.MethodsInstrument-specific calibration factors were estimated in 25 MTI- and 53 CSA accelerometers in a mechanical setup using four different settings varying in frequencies and/or amplitudes. Calibration effect was analysed by comparing raw and calibrated data after applying unit-specific calibration factors to data obtained during quality checks in a mechanical setup and to data collected during free living conditions.ResultsCalibration reduced inter-instrument variability considerably in the mechanical setup, both in the MTI instruments (raw SDbetween units = 195 counts*min-1 vs. calibrated SDbetween units = 65 counts*min-1) and in the CSA instruments (raw SDbetween units = 343 counts*min-1 vs. calibrated SDbetween units = 67 counts*min-1). However, the effect of applying the derived calibration to children's and adolescents' free living physical activity data did not alter the coefficient of variation (CV) (children: CVraw = 30.2% vs. CVcalibrated = 30.4%, adolescents: CVraw = 36.3% vs. CVcalibrated = 35.7%). High correlations (r = 0.99 & r = 0.98, respectively) were observed between raw and calibrated field data, and the proportion of the total variation caused by the MTI- and CSA monitor was estimated to be only 1.1% and 4.2%, respectively. Compared to the CSA instruments, a significantly increased (9.95%) mean acceleration response was observed post hoc in the batch of MTI instruments, in which a significantly reduced inter-instrumental reliability was observed over time.ConclusionThe application of unit-specific calibration factors to data collected during free living conditions had no apparent effect on inter-instrument variability. In all probability, the effect of technical calibration was primarily attenuated in the field by other more dominant sources of variation. However, routine technical assessments are still very important for determining the acceleration responses in the batch of instruments being used and, if performed after every field use, for preventing decidedly broken instruments from being returned into the field repeatedly.

Uncertainty for Data with Non-Detects: Air Toxic Emissions from Combustion

ABSTRACT Air toxic emission factor datasets often contain one or more points below a single or multiple detection limits and such datasets are referred to as “censored.” Conventional methods used to deal with censored datasets include removing non-detects, replacing the censored points with zero, half of the detection limit, or the detection limit. However, the estimated means of the censored dataset by conventional methods are usually biased. Maximum likelihood estimation (MLE) and bootstrap simulation have been demonstrated as a statistically robust method to quantify variability and uncertainty of censored datasets and can provide asymptotically unbiased mean estimates. The MLE/bootstrap method is applied to 16 cases of censored air toxic emission factors, including benzene, formaldehyde, benzo(a)pyrene, mercury, arsenic, cadmium, total chromium, chromium VI and lead from coal, fuel oil, and/or wood waste external combustion sources. The proportion of censored values in the emission factor data ranges from 4 to 80%. Key factors that influence the estimated uncertainty in the mean of censored data are sample size and inter-unit variability. The largest range of uncertainty in the mean was obtained for the external coal combustion benzene emission factor, with 95 confidence interval of the mean equal to minus 93 to plus 411%.

Development of Probabilistic Emission Inventories of Air Toxics for Jacksonville, Florida

Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum Likelihood Estimation (MLE) method or the Method of Matching Moments was used to fit parametric distributions. For data sets that contain nondetected measurements, a method based upon MLE was used for parameter estimation. To quantify the uncertainty in urban air toxic emission factors, parametric bootstrap simulation and empirical bootstrap simulation were applied to uncensored and censored data, respectively. The probabilistic emission inventories were developed based on the product of the uncertainties in the emission factors and in the activity factors. The uncertainties in the urban air toxics emission inventories range from as small as –25 to +30% for Hg to as large as –83 to +243% for As. The key sources of uncertainty in the emission inventory for each toxic are identified based upon sensitivity analysis. Typically, uncertainty in the inventory of a given pollutant can be attributed primarily to a small number of source categories. Priorities for improving the inventories and for refining the probabilistic analysis are discussed.

Quantification of Variability and Uncertainty for Air Toxic Emission Inventories with Censored Emission Factor Data

Probabilistic emission inventories were developed for urban air toxic emissions of benzene, formaldehyde, chromium, and arsenic for the example of Houston. Variability and uncertainty in emission factors were quantified for 71-97% of total emissions, depending upon the pollutant and data availability. Parametric distributions for interunit variability were fit using maximum likelihood estimation (MLE), and uncertainty in mean emission factors was estimated using parametric bootstrap simulation. For data sets containing one or more nondetected values, empirical bootstrap simulation was used to randomly sample detection limits for nondetected values and observations for sample values, and parametric distributions for variability were fit using MLE estimators for censored data. The goodness-of-fit for censored data was evaluated by comparison of cumulative distributions of bootstrap confidence intervals and empirical data. The emission inventory 95% uncertainty ranges are as small as -25% to +42% for chromium to as large as -75% to +224% for arsenic with correlated surrogates. Uncertainty was dominated by only a few source categories. Recommendations are made for future improvements to the analysis.