Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

Numerical analysis of an incremented statistical sampling procedure in MCNP

MCNP has stood so far as one of the main Monte Carlo radiation transport codes. Its use, as any other Monte Carlo based code, has increased as computers perform calculations faster and become more affordable along time. However, the use of Monte Carlo method to tally events in volumes which represent a small fraction of the whole system may turn to be unfeasible, if a straight analogue transport procedure (no use of variance reduction techniques) is employed and precise results are demanded. Calculations of reaction rates in activation foils placed in critical systems turn to be one of the mentioned cases. The present work takes advantage of the fixed source representation from MCNP to perform the above mentioned task in a more effective sampling way (characterizing neutron population in the vicinity of the tallying region and using it in a geometric reduced coupled simulation). An extended analysis of source dependent parameters is studied in order to understand their influence on simulation performance and on validity of results. Although discrepant results have been observed for small enveloping regions, the procedure presents itself as very efficient, giving adequate and precise results in shorter times than the standard analogue procedure. (C) 2007 Elsevier Ltd. All rights reserved.

Insights into the dynamics and sources of atmospheric lead and particulate matter in Sao Paulo, Brazil, from high temporal resolution sampling

We present the first results of a study investigating the processes that control concentrations and sources of Pb and particulate matter in the atmosphere of Sao Paulo City Brazil Aerosols were collected with high temporal resolution (3 hours) during a four-day period in July 2005 The highest Pb concentrations measured coincided with large fireworks during celebration events and associated to high traffic occurrence Our high-resolution data highlights the impact that a singular transient event can have on air quality even in a megacity Under meteorological conditions non-conducive to pollutant dispersion Pb and particulate matter concentrations accumulated during the night leading to the highest concentrations in aerosols collected early in the morning of the following day The stable isotopes of Pb suggest that emissions from traffic remain an Important source of Pb in Sao Paulo City due to the large traffic fleet despite low Pb concentrations in fuels (C) 2010 Elsevier BV All rights reserved

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Versatile microanalytical system with porous polypropylene capillary membrane for calibration gas generation and trace gaseous pollutants sampling applied to the analysis of formaldehyde, formic acid, acetic acid and ammonia in outdoor air

The analytical determination of atmospheric pollutants still presents challenges due to the low-level concentrations (frequently in the mu g m(-3) range) and their variations with sampling site and time In this work a capillary membrane diffusion scrubber (CMDS) was scaled down to match with capillary electrophoresis (CE) a quick separation technique that requires nothing more than some nanoliters of sample and when combined with capacitively coupled contactless conductometric detection (C(4)D) is particularly favorable for ionic species that do not absorb in the UV-vis region like the target analytes formaldehyde formic acid acetic acid and ammonium The CMDS was coaxially assembled inside a PTFE tube and fed with acceptor phase (deionized water for species with a high Henry s constant such as formaldehyde and carboxylic acids or acidic solution for ammonia sampling with equilibrium displacement to the non-volatile ammonium ion) at a low flow rate (8 3 nLs(-1)) while the sample was aspirated through the annular gap of the concentric tubes at 25 mLs(-1) A second unit in all similar to the CMDS was operated as a capillary membrane diffusion emitter (CMDE) generating a gas flow with know concentrations of ammonia for the evaluation of the CMDS The fluids of the system were driven with inexpensive aquarium air pumps and the collected samples were stored in vials cooled by a Peltier element Complete protocols were developed for the analysis in air of NH(3) CH(3)COOH HCOOH and with a derivatization setup CH(2)O by associating the CMDS collection with the determination by CE-C(4)D The ammonia concentrations obtained by electrophoresis were checked against the reference spectrophotometric method based on Berthelot s reaction Sensitivity enhancements of this reference method were achieved by using a modified Berthelot reaction solenoid micro-pumps for liquid propulsion and a long optical path cell based on a liquid core waveguide (LCW) All techniques and methods of this work are in line with the green analytical chemistry trends (C) 2010 Elsevier B V All rights reserved

Simultaneous determination of chromium and manganese in alumina by slurry sampling graphite furnace atomic absorption spectrometry using NbC and NaF as modifiers

This paper reports a method for the direct and simultaneous determination of Cr and Mn in alumina by slurry sampling graphite furnace atomic absorption spectrometry (SiS-SIMAAS) using niobium carbide (NbC) as a graphite platform modifier and sodium fluoride (NaF) as a matrix modifier. 350 mu g of Nb were thermally deposited on the platform surface allowing the formation of NbC (mp 3500 degrees C) to minimize the reaction between aluminium and carbon of the pyrolytic platform, improving the graphite tube lifetime up to 150 heating cycles. A solution of 0.2 mol L(-1) NaF was used as matrix modifier for alumina dissolution as cryolite-based melt, allowing volatilization during pyrolysis step. Masses (c.a. 50 mg) of sample were suspended in 30 ml of 2.0% (v/v) of HNO(3). Slurry was manually homogenized before sampling. Aliquots of 20 mu l of analytical solutions and slurry samples were co-injected into the graphite tube with 20 mu l of the matrix modifier. In the best conditions of the heating program, pyrolysis and atomization temperatures were 1300 degrees C and 2400 degrees C, respectively. A step of 1000 degrees C was optimized allowing the alumina dissolution to form cryolite. The accuracy of the proposed method has been evaluated by the analysis of standard reference materials. The found concentrations presented no statistical differences compared to the certified values at 95% of the confidence level. Limits of detection were 66 ng g(-1) for Cr and 102 ng g(-1) for Mn and the characteristic masses were 10 and 13 pg for Cr and Mn, respectively.

Feasibility of using in situ fusion for the determination of Co, Cr and Mn in Portland cement by direct solid sampling graphite furnace atomic absorption spectrometry

In situ fusion on the boat-type graphite platform has been used as a sample pretreatment for the direct determination of Co, Cr and Mn in Portland cement by solid sampling graphite furnace atomic absorption spectrometry (SS-GF AAS). The 3-field Zeeman technique was adopted for background correction to decrease the sensitivity during measurements. This strategy allowed working with up to 200 mu g of sample. The in situ fusion was accomplished using 10 mu L of a flux mixture 4.0% m/v Na(2)CO(3) + 4.0% m/v ZnO + 0.1% m/v Triton (R) X-100 added over the cement sample and heated at 800 degrees C for 20 s. The resulting mould was completely dissolved with 10 mu L of 0.1% m/v HNO(3). Limits of detection were 0.11 mu g g(-1) for Co, 1.1 mu g g(-1) for Cr and 1.9 mu g g(-1) for Mn. The accuracy of the proposed method has been evaluated by the analysis of certified reference materials. The values found presented no statistically significant differences compared to the certified values (Student`s t-test, p<0.05). In general, the relative standard deviation was lower than 12% (n = 5). (C) 2009 Elsevier B.V. All rights reserved.

Environmental formaldehyde analysis by active diffusive sampling with a bundle of polypropylene porous capillaries followed by capillary zone electrophoretic separation and contactless conductivity detection

Compared to other volatile carbonylic compounds present in outdoor air, formaldehyde (CH2O) is the most toxic, deserving more attention in terms of indoor and outdoor air quality legislation and control. The analytical determination of CH2O in air still presents challenges due to the low-level concentration (in the sub-ppb range) and its variation with sampling site and time. Of the many available analytical methods for carbonylic compounds, the most widespread one is the time consuming collection in cartridges impregnated with 2,4-dinitrophenylhydrazine followed by the analysis of the formed hydrazones by HPLC. The present work proposes the use of polypropylene hollow porous capillary fibers to achieve efficient CH2O collection. The Oxyphan (R) fiber (designed for blood oxygenation) was chosen for this purpose because it presents good mechanical resistance, high density of very fine pores and high ratio of collection area to volume of the acceptor fluid in the tube, all favorable for the development of air sampling apparatus. The collector device consists of a Teflon pipe inside of which a bundle of polypropylene microporous capillary membranes was introduced. While the acceptor passes at a low flow rate through the capillaries, the sampled air circulates around the fibers, impelled by a low flow membrane pump (of the type used for aquariums ventilation). The coupling of this sampling technique with the selective and quantitative determination of CH2O, in the form of hydroxymethanesulfonate (HMS) after derivatization with HSO3-, by capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-(CD)-D-4) enabled the development of a complete analytical protocol for the CH2O evaluation in air. (C) 2008 Published by Elsevier B.V.

Direct determination of iron in sand using solid sampling graphite furnace atomic absorption spectrometry

A fast and reliable method for the direct determination of iron in sand by solid sampling graphite furnace atomic absorption spectrometry was developed. A Zeeman-effect 3-field background corrector was used to decrease the sensitivity of spectrometer measurements. This strategy allowed working with up to 200 mu g of samples, thus improving the representativity. Using samples with small particle sizes (1-50 mu m) and adding 5 mu g Pd as chemical modifier, it was possible to obtain suitable calibration curves with aqueous reference solutions. The pyrolysis and atomization temperatures for the optimized heating program were 1400 and 2500 degrees C, respectively. The characteristic mass, based on integrated absorbance, was 56 pg, and the detection limits, calculated considering the variability of 20 consecutive measurements of platform inserted without sample was 32 pg. The accuracy of the procedure was checked with the analysis of two reference materials (IPT 62 and 63). The determined concentrations were in agreement with the recommended values (95% confidence level). Five sand samples were analyzed, and a good agreement (95% confidence level) was observed using the proposed method and conventional flame atomic absorption spectrometry. The relative standard deviations were lower than 25% (n = 5). The tube and boat platform lifetimes were around 1000 and 250 heating cycles, respectively.

Application of solid sampling device for direct determination of chromium and nickel in lubricating oils by graphite furnace atomic absorption spectrometry

One method using a solid sampling device for the direct determination of Cr and Ni in fresh and used lubricating oils by graphite furnace atomic absorption spectrometry are proposed. The high organic content in the samples was minimized using a digestion step at 400 degrees C in combination with an oxidant mixture 1.0% (v v(-1)) HNO3+15% (v v(-1)) H2O2+0.1% (m v(-1)) Triton X-100 for the in situ digestion. The 3-field mode Zeeman-effect allowed the spectrometer calibration up to 5 ng of Cr and Ni. The quantification limits were 0.86 mu g g(-1) for Cr and 0.82 mg g(-1) for Ni, respectively. The analysis of reference materials showed no statistically significant difference between the recommended values and those obtained by the proposed methods.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.