scholarly journals Comparison of VOC measurements made by PTR-MS, Adsorbent Tube/GC-FID-MS and DNPH-derivatization/HPLC during the Sydney Particle Study, 2012: a contribution to the assessment of uncertainty in current atmospheric VOC measurements

Author(s):  
Erin Dunne ◽  
Ian E. Galbally ◽  
Min Cheng ◽  
Paul Selleck ◽  
Suzie B. Molloy ◽  
...  

Abstract. Understanding uncertainty is essential for utilizing atmospheric VOC measurements in robust ways to develop atmospheric science. This study describes an inter-comparison of the VOC data, and the derived uncertainty estimates, measured with three independent techniques (PTR-MS, AT-GC-FID and DNPH-HPLC) during the Sydney Particle Study campaigns in 2012. The compounds and compound classes compared, based on objective selection criteria from the available data, were: benzene, toluene, C8 aromatics, isoprene, formaldehyde, acetaldehyde and acetone. Bottom-up uncertainty analyses were undertaken for each compound and each measurement system. Top-down uncertainties were quantified via the inter-comparisons. Four metrics were used for the inter-comparisons: the slope and intercept as determined by reduced major axis regression, the correlation, and the root mean standard deviation of the observation from the regression line. In all seven comparisons the correlations between independent measurement techniques were high with R2 values of median 0.93 (range: 0.72–0.98) and small root mean standard deviations of the observations from the regression line with a median of 0.13 (range: 0.04–0.23 ppb). These results give a high degree of confidence that for each comparison the response of the two independent techniques are dominated by the same constituents. The slope and intercept as determined by reduced major axis regression gives a different story. The slopes varied considerably with a median of 1.23 and range 1.08 to 2.03. The intercepts varied with a median of 0.02 and range −0.07 to 0.31 ppb. An ideal comparison would give a slope of 1.00 and an intercept of zero. This analysis identified some poorly understood and poorly quantified sources of uncertainty in the measurement techniques including: the contributions of non-target compounds to the measurement of the target compound for benzene, toluene and isoprene by PTR-MS; and, the under-reporting of formaldehyde, acetaldehyde and acetone by the DNPH technique. As well as these, this study has identified a specific interference of liquid water with acetone measurements by the DNPH technique. These relationships reported for Sydney 2012 were incorporated into a larger analysis with 61 other published inter-comparison studies for the same compounds. Overall for the light aromatics, isoprene and the C1–C3 carbonyls the uncertainty in a set of measurements varies by a factor of between 1.5 and two. These uncertainties (~50 %) are significantly higher than uncertainties estimated using standard propagation of error methods, which in this case were ~22 % or less, and are the result of the presence of poorly understood or neglected processes that affect the measurement and its uncertainty. The uncertainties in VOC measurements identified here should be considered when: assessing the reliability of VOC measurements from individual instruments; when utilising VOC data to constrain and inform air quality and climate models; when using VOC observations for human exposure studies; and, when comparing ambient VOC data with satellite retrievals.

2018 ◽  
Vol 11 (1) ◽  
pp. 141-159 ◽  
Author(s):  
Erin Dunne ◽  
Ian E. Galbally ◽  
Min Cheng ◽  
Paul Selleck ◽  
Suzie B. Molloy ◽  
...  

Abstract. Understanding uncertainty is essential for utilizing atmospheric volatile organic compound (VOC) measurements in robust ways to develop atmospheric science. This study describes an inter-comparison of the VOC data, and the derived uncertainty estimates, measured with three independent techniques (PTR-MS, proton-transfer-reaction mass spectrometry; GC-FID-MS, gas chromatography with flame-ionization and mass spectrometric detection; and DNPH–HPLC, 2,4-dinitrophenylhydrazine derivatization followed by analysis by high-performance liquid chromatography) during routine monitoring as part of the Sydney Particle Study (SPS) campaign in 2012. Benzene, toluene, C8 aromatics, isoprene, formaldehyde and acetaldehyde were selected for the comparison, based on objective selection criteria from the available data. Bottom-up uncertainty analyses were undertaken for each compound and each measurement system. Top-down uncertainties were quantified via the inter-comparisons. In all seven comparisons, the correlations between independent measurement techniques were high with R2 values with a median of 0.92 (range 0.75–0.98) and small root mean square of the deviations (RMSD) of the observations from the regression line with a median of 0.11 (range 0.04–0.23 ppbv). These results give a high degree of confidence that for each comparison the response of the two independent techniques is dominated by the same constituents. The slope and intercept as determined by reduced major axis (RMA) regression gives a different story. The slopes varied considerably with a median of 1.25 and a range of 1.16–2.01. The intercepts varied with a median of 0.04 and a range of −0.03 to 0.31 ppbv. An ideal comparison would give a slope of 1.00 and an intercept of 0. Some sources of uncertainty that are poorly quantified by the bottom-up uncertainty analysis method were identified, including: contributions of non-target compounds to the measurement of the target compound for benzene, toluene and isoprene by PTR-MS as well as the under-reporting of formaldehyde, acetaldehyde and acetone by the DNPH technique. As well as these, this study has identified a specific interference of liquid water with acetone measurements by the DNPH technique. These relationships reported for Sydney 2012 were incorporated into a larger analysis with 61 similar published inter-comparison studies for the same compounds. Overall, for the light aromatics, isoprene and the C1–C3 carbonyls, the uncertainty in a set of measurements varies by a factor of between 1.5 and 2. These uncertainties (∼50 %) are significantly higher than uncertainties estimated using standard propagation of error methods, which in this case were ∼22 % or less, and are the result of the presence of poorly understood or neglected processes that affect the measurement and its uncertainty. The uncertainties in VOC measurements identified here should be considered when assessing the reliability of VOC measurements from routine monitoring with individual, stand-alone instruments; when utilizing VOC data to constrain and inform air quality and climate models; when using VOC observations for human exposure studies; and for comparison with satellite retrievals.


Author(s):  
William V. Harper ◽  
David J. Stucki ◽  
Thomas A. Bubenik ◽  
Clifford J. Maier ◽  
David A. R. Shanks ◽  
...  

The importance of comparing in-line inspection (ILI) calls to excavation data should not be underestimated. Neither should it be undertaken without a solid understanding of the methodologies being employed. Such a comparison is not only a key part of assessing how well the tool performed, but also for an API 1163 evaluation and any subsequent use of the ILI data. The development of unity (1-1) plots and the associated regression analysis are commonly used to provide the basis for predicting the likelihood of leaks or failures from unexcavated ILI calls. Combining such analysis with statistically active corrosion methods into perhaps a probability of exceedance (POE) study helps develop an integrity maintenance plan for the years ahead. The theoretical underpinnings of standard regression analysis are based on the assumption that the independent variable (often thought of as x) is measured without error as a design variable. The dependent variable (often labeled y) is modeled as having uncertainty or error. Pipeline companies may run their regressions differently, but ILI to field excavation regressions often use the ILI depth as the x variable and field depth as the y variable. This is especially the case in which a probability of exceedance analysis is desired involving transforming ILI calls to predicted depths for a comparison to a threshold of interest such as 80% wall thickness. However, in ILI to field depth regressions, both the measured depths can have error. Thus, the underlying least squares regression assumptions are violated. Often one common result is a regression line that has a slope much less than the ideal 1-1 relationship. Reduced Major Axis (RMA) Regression is specifically formulated to handle errors in both the x and y variables. It is not commonly found in the standard literature but has a long pedigree including the 1995 text book Biometry by Sokal and Rohlf in which it appears under the title of Model II regression. In this paper we demonstrate the potential improvements brought about by RMA regression. Building on a solid comparison between ILI data and excavations provides the foundation for more accurate predictions and management plans that reliably provide longer range planning. This may also result in cost savings as the time between ILI runs might be lengthened due to a better analysis of such important data.


1984 ◽  
Vol 62 (10) ◽  
pp. 1897-1905 ◽  
Author(s):  
W. E. Ricker

A bivariate array of naturally variable observations can take many different forms, depending on the relative lengths of the measurement units used. Each of these has a different central trend or major axis. In a standard presentation the major axis has a slope of ± 1 obtained when 1 standard deviation (s) of each variate, Y and X, occupies the same distance on its coordinate axis. With any other presentation the position of the standard trend is indicated by a line whose slope is the ratio of the standard deviations; it is called the standard (or reduced) major axis, or geometric mean regression line (GMR). The GMR is symmetrical, invariant with change of scale, and "robust." Besides indicating the central trend, it is a suitable line for estimating Y from X, or X from Y, in two common situations where ordinary regressions fail: (i) when the sampling procedure was not random with respect to the entire population (but was random with respect to its standard trend); (ii) when the population sampled departs seriously from a bivariate normal configuration. In the latter case an alternative "Schnute" line is appropriate if components of the population may have different sY/sX ratios.


1984 ◽  
Vol 56 (2) ◽  
pp. 536-539 ◽  
Author(s):  
D. L. Sherrill ◽  
G. D. Swanson

The ventilatory response to changes in alveolar (arterial) CO2 is widely used as an index of respiratory control behavior. Methods for estimating these response slopes should incorporate the possibility that there may be errors in both the independent (partial pressure of CO2) and dependent (ventilation) variables. In a recent paper Daubenspeck and Ogden (J. Appl. Physiol. Respirat. Environ. Exercise Physiol. 45:823–829, 1978) have suggested problems inherent in the traditional technique of reduced major axis and have suggested a more contemporary technique of directional statistics. We have previously analyzed both techniques and developed a method to overcome the problems of reduced major axis and problems inherent in the use of directional statistics. Under the assumption of a bivariate normal distribution, we demonstrate that our slope estimate is similar to the maximum likelihood estimate proposed by Mardia et al. (J. Appl. Physiol.: Respirat. Environ. Exercise Physiol. 54: 309–313, 1983) for this problem. In addition, we demonstrate a bootstrap statistical approach when the distributions are not normally distributed. These concepts are illustrated using O2-CO2 interaction data.


2017 ◽  
Vol 17 (7) ◽  
pp. 4451-4475 ◽  
Author(s):  
Ilissa B. Ocko ◽  
Paul A. Ginoux

Abstract. Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud–Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.


2012 ◽  
Vol 166-169 ◽  
pp. 1895-1899
Author(s):  
Xiao Gang Wang ◽  
De Ming Zhong

Area loss of severely weakened rebar cross sections is a crucial variable in assessment of structural deterioration for corroded concrete structures, which is hard to be measured or estimated precisely in conventional methods. In this paper, rebar samples were taken from naturally corroded RC slabs. Their virtual models were built using 3D laser scanning technique to facilitate geometric measurement. From these models seriously weakened sections were screened out as analyzing samples, and residual areas as well as profiles of the cross-sections were derived and investigated consequently. Shown by the results, corrosion was non-uniformly distributed on rebar surface, and profiles of the residual cross-sections can hardly be formulated efficiently. However, they can be simplified into ellipse with minor axis of minimum residual diameter and major axis of diameter in perpendicular direction. This model has been proved to give an conservative approximation of residual sectional area with 4.27% underestimation and 89.2% degree of confidence.


1997 ◽  
Vol 119 (1) ◽  
pp. 57-60
Author(s):  
S. Qin ◽  
G. E. O. Widera

When performing inservice inspection on a large volume of identical components, it becomes an almost impossible task to inspect all those in which defects may exist, even if their failure probabilities are known. As a result, an appropriate sample size needs to be determined when setting up an inspection program. In this paper, a probabilistic analysis method is employed to solve this problem. It is assumed that the characteristic data of components has a certain distribution which can be taken as known when the mean and standard deviations of serviceable and defective sets of components are estimated. The sample size can then be determined within an acceptable assigned error range. In this way, both false rejection and acceptance can be avoided with a high degree of confidence.


2012 ◽  
Vol 27 (2) ◽  
pp. 13
Author(s):  
L. A. Salcido -Guevara ◽  
F. Arreguín -Sánchez ◽  
L. Palmeri ◽  
A. Barausse

We tested the hypothesis that ecosystem metabolism follows a quarter power scaling relation, analogous to organisms. Logarithm of Biomass/Production (B/P) to Trophic Level (TL) relationship was estimated to 98 trophic models of aquatic ecosystems. A normal distribution of the slopes gives a modal value of 0.64, which was significantly different of the theoretical value of 0.75 (p0.05). We also tested for error in both variables, Log (B/P) and TL, through a Reduced Major Axis regression with similar results, with a modal value of 0.756 (p>0.05). We also explored a geographic distribution showing no significant relation (p>0.05) to latitude and between different regions of the world. We conclude that: a) ecosystem metabolism follows the quarter-power scaling rule; b) transfer efficiency between TL plays a relevant role characterizing local attributes to ecosystem metabolism; and c) there is neither latitudinal nor geographic differences. These findings confirm the existence of a metabolic scaling regularity in aquatic ecosystems. Regularidad del escalamiento metabólico en ecosistemas acuáticos Se contrastó la hipótesis de que el metabolismo de un ecosistema sigue una relación de escalamiento análoga a la existente en los organismos. La relación entre el logaritmo de la razón Producción/Biomasa (B/P) y el nivel trófico (TL) se estimó para 98 modelos tróficos de los ecosistemas acuáticos. Una distribución normal de las pendientes de esta relación produjo un valor modal de 0.64 que es significativamente diferente del valor teórico de 0.75 (p0.05) similar al teórico esperado. También se contrastó la hipótesis de existencia de error en ambas variables, logaritmo (B/P) y TL, a través de la técnica de regresión denominada “Reduced Major Axis”, con resultados similares según el valor modal de 0.756, sin diferencia estadísticamente significativa (p>0.05) del valor teórico. Se exploró la existencia de algún patrón en la distribución geográfica, sin obtenerse relación significativa (p>0.05) con la latitud, o con diferentes regiones del mundo. Las conclusiones son: a) el metabolismo del ecosistema sigue la regla de escalamiento metabólico de 3/4; b) la eficiencia de la transferencia entre TL desempeña un papel relevante, representando los atributos locales del metabolismo del ecosistema; c) no hay una diferencias latitudinal o geográfica. Estos resultados confirman la existencia de una regularidad en el escalamiento metabólico en ecosistemas acuáticos.


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