Estimation Of Mass Concentration Research Articles

Improving Aerosol Characterization Using an Optical Particle Counter Coupled with a Quartz Crystal Microbalance with an Integrated Microheater.

Aerosols, as well as suspended particulate matter, impact atmospheric pollution, the climate, and human health, directly or indirectly. Particle size, chemical composition, and other aerosol characteristics are determinant factors for atmospheric pollution dynamics and more. In the last decade, low-cost devices have been widely used in instrumentation to measure aerosols. However, they present some issues, such as the problem of discriminating whether the aerosol is composed of liquid particles or solid. This issue could lead to errors in the estimation of mass concentration in monitoring environments where there is fog. In this study, we investigate the use of an optical particle counter (OPC) coupled to a quartz crystal microbalance with an integrated microheater (H-QCM) to enhance measurement performances. The H-QCM was used not only to measure the collected mass on its surface but also, by using the integrated microheater, it was able to heat the collected mass by performing heating cycles. In particular, we tested the developed system with aerosolized saline solutions of sodium chloride (NaCl), with three decreasing concentrations of salt and three electronic cigarette solutions (e-liquid), with different concentrations of propylene glycol and glycerin mixtures. The results showed that the OPC coherently counted the salt dilution effects, and the H-QCM output confirmed the presence of liquid and solid particles in the aerosols. In the case of e-liquid aerosols, the OPC counted the particles, and the HQCM output highlighted that in the aerosol, there were no solid particles but a liquid phase only. These findings contribute to the refinement of aerosol measurement methodologies by low-cost sensors, fostering a more comprehensive understanding.

Mass concentration estimates of long-range-transported Canadian biomass burning aerosols from a multi-wavelength Raman polarization lidar and a ceilometer in Finland

Abstract. A quantitative comparison study for Raman lidar and ceilometer observations, and for model simulations of mass concentration estimates of smoke particles is presented. Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios (PDRs) of this plume were measured to be 0.08±0.02 at 355 nm and 0.05±0.01 at 532 nm, suggesting the presence of partly coated soot particles or particles that have mixed with a small amount of dust or other non-spherical aerosol type. The layer-mean PDR at 355 nm (532 nm) decreased during the day from ∼0.11 (0.06) in the morning to ∼0.05 (0.04) in the evening; this decrease with time could be linked to the particle aging and related changes in the smoke particle shape properties. Lidar ratios were derived as 47±5 sr at 355 nm and 71±5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 ceilometer is presented from a sensor-provided attenuated backscatter coefficient to particle mass concentration (including the water vapor correction for high latitude for the first time). Aerosol backscatter coefficients (BSCs) were measured at four wavelengths (355, 532, 1064 nm from PollyXT and 910 nm from CL51). Two methods, based on a combined lidar and sun-photometer approach, are applied for mass concentration estimations from both PollyXT and the ceilometer CL51 observations. In the first method, no. 1, we used converted BSCs at 532 nm (from measured BSCs) by corresponding measured backscatter-related Ångström exponents, whereas in the second method, no. 2, we used measured BSCs at each wavelength independently. A difference of ∼12 % or ∼36 % was found between PollyXT and CL51 estimated mass concentrations using method no. 1 or no. 2, showing the potential of mass concentration estimates from a ceilometer. Ceilometer estimations have an uncertainty of ∼50 % in the mass retrieval, but the potential of the data lies in the great spatial coverage of these instruments. The mass retrievals were compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust (as indicated by MERRA-2 data) in the retrieved mass concentration is negligible considering the uncertainties, which also shows that ceilometer observations for mass retrievals can be used even without exact knowledge of the composition of the smoke-dominated aerosol plume in the troposphere.

Parametric Model for Estimation of Mass Concentration based on Particle Count Distribution for Ambient Air Monitoring

The application of optical based instrument in particulate matter monitoring has gained interest among researchers in recent years due to their high degree automation in providing real time reading of particulate matter concentrations. Such instrument usually comes in compact form making it compatible for in-situ monitoring especially for dense monitoring network. Theoretically, optical based instrument is unable to measure the mass concentration of particulate matter which is the key parameter in air quality monitoring. Instead, the mass concentration is calculated based on particle size distribution under assumptions that all particles is spherical using a known density. This being said, the accuracy of the reported mass concentration by optical instrument can be easily deteriorated if one of these assumptions is violated. Therefore, there is a need for a thorough evaluation on the particle to mass conversion factor in order to improve the accuracy of the reported mass concentrations by an optical instrument. In this study, the reported mass concentration from an optical based instrument as a function of particle distribution through random air sampling was investigated. The obtained data was then used to develop a parametric model for calculation of particulate mass concentration based on particle count distribution. The model developed was evaluated at several site and reported a good accuracy with high correlation (R2 > 0.97) in estimation of mass concentration.

Sources of error and variability in particulate matter sensor network measurements

The quality of mass concentration estimates from increasingly popular networks of low-cost particulate matter sensors depends on accurate conversion of sensor output (e.g., voltage) into gravimetric-equivalent mass concentration, typically using a calibration procedure. This study evaluates two important sources of variability that lead to error in estimating gravimetric-equivalent mass concentration: the temporal changes in sensor calibration and the spatial and temporal variability in gravimetric correction factors. A 40-node sensor network was deployed in a heavy vehicle manufacturing facility for 8 months. At a central location in the facility, particulate matter was continuously measured with three sensors of the network and a traditional, higher-cost photometer, determining the calibration slope and intercept needed to translate sensor output to photometric-equivalent mass concentration. Throughout the facility, during three intensive sampling campaigns, respirable mass concentrations were measured with gravimetric samplers and photometers to determine correction factors needed to adjust photometric-equivalent to gravimetric-equivalent mass concentration. Both field-determined sensor calibration slopes and intercepts were statistically different than those estimated in the laboratory (α = 0.05), emphasizing the importance of aerosol properties when converting voltage to photometric-equivalent mass concentration and the need for field calibration to determine slope. Evidence suggested the sensors’ weekly field calibration slope decreased and intercept increased, indicating the sensors were deteriorating over time. The mean correction factor in the cutting and shot blasting area (2.9) was substantially and statistically lower than that in the machining and welding area (4.6; p = 0.01). Therefore, different correction factors should be determined near different occupational processes to accurately estimate particle mass concentrations.

Assessment of Particle Oxidative Potential as an Air Pollution Exposure Metric: A Systematic Review

Ambient particulate air pollution is linked to numerous acute and chronic health outcomes. The standard approach to measuring particulate exposure has been to estimate particle mass concentration. New measures account for oxidative potential, the ability of particles to cause oxidative stress in the body. There has been no systematic comparison of particulate air pollution exposure assessment methods between those that incorporate oxidative potential and those that do not. The aim of this review is to determine if associations between particulate air pollution exposure and health outcomes are stronger when oxidative potential is used as the exposure metric, in comparison to particle mass concentration. The databases Medline and Embase were searched from inception to 28 March 2018 for studies that reported an association between particulate air pollution exposure and a health outcome in a human population, and in which exposure was measured by both particle mass concentration and oxidative potential. Study quality was assessed using a US National Toxicology Program instrument. We identified 18 publications meeting the selection criteria. The most common oxidative potential assay was antioxidant depletion in synthetic respiratory tract lining fluid, used in 12 articles. The rate of consumption of dithiothreitol was also frequently used as an oxidative potential assay and appeared in 5 studies. The dithiothreitol assay most consistently produced stronger effect estimates, as 10/14 endpoints showed higher point estimates of associations compared to particle mass concentration estimates. Other assays showed mixed results. To date there is no consistent evidence that oxidative potential is more strongly associated with health outcomes than particle mass concentrations; however, these assays do have the advantage of not treating all particles as equally harmful and further work should explore which specific assays are most relevant to evaluating air pollution health risks.

Evaluating droplet digital PCR for the quantification of human genomic DNA: converting copies per nanoliter to nanograms nuclear DNA per microliter.

The highly multiplexed polymerase chain reaction (PCR) assays used for forensic human identification perform best when used with an accurately determined quantity of input DNA. To help ensure the reliable performance of these assays, we are developing a certified reference material (CRM) for calibrating human genomic DNA working standards. To enable sharing information over time and place, CRMs must provide accurate and stable values that are metrologically traceable to a common reference. We have shown that droplet digital PCR (ddPCR) limiting dilution end-point measurements of the concentration of DNA copies per volume of sample can be traceably linked to the International System of Units (SI). Unlike values assigned using conventional relationships between ultraviolet absorbance and DNA mass concentration, entity-based ddPCR measurements are expected to be stable over time. However, the forensic community expects DNA quantity to be stated in terms of mass concentration rather than entity concentration. The transformation can be accomplished given SI-traceable values and uncertainties for the number of nucleotide bases per human haploid genome equivalent (HHGE) and the average molar mass of a nucleotide monomer in the DNA polymer. This report presents the considerations required to establish the metrological traceability of ddPCR-based mass concentration estimates of human nuclear DNA. Graphical abstract The roots of metrological traceability for human nuclear DNA mass concentration results. Values for the factors in blue must be established experimentally. Values for the factors in red have been established from authoritative source materials. HHGE stands for "haploid human genome equivalent"; there are two HHGE per diploid human genome.

Optical Characterization Studies of a Low-Cost Particle Sensor

ABSTRACT Compact low-cost sensors for measuring particulate matter (PM) concentrations are receiving significant attention as they can be used in larger numbers and in a distributed manner. Most low-cost particle sensors work on optical scattering measurements from the aerosol. To ensure accurate and reliable determination of PM mass concentrations, a relationship of the scattering signal to mass concentration should be established. The scattering signal depends on the aerosol size distributions and particle refractive index. A systematic calibration of a low-cost particle sensor (Sharp GP2Y1010AU0F) was carried out by both experimental and computational studies. Sodium chloride, silica, and sucrose aerosols were used as test cases with size distributions measured using a scanning mobility particle sizer (SMPS). The mass concentration was estimated using the measured size distribution and density of the particles. Calculations of the scattered light intensity were done using these measured size distributions and known refractive index of the particles. The calculated scattered light intensity showed better linearity with the sensor signal compared to the mass concentration. To obtain a more accurate mass concentration estimation, a model was developed to determine a calibration factor (K). K is not universal for all aerosols, but depends on the size distribution and refractive index. To improve accuracy in estimation of mass concentration, an expression for K as a function of geometric mean diameter, geometric standard deviation, and refractive index is proposed. This approach not only provides a more accurate estimation of PM concentration, but also provides an estimate of the aerosol number concentration.

Image-based Material Decomposition with a General Volume Constraint for Photon-Counting CT.

Photon-counting CT (PCCT) potentially offers both improved dose efficiency and material decomposition capabilities relative to CT systems using energy integrating detectors. With respect to material decomposition, both projection-based and image-based methods have been proposed, most of which require accurate a priori information regarding the shape of the x-ray spectra and the response of the detectors. Additionally, projection-based methods require access to projection data. These data can be difficult to obtain, since spectra, detector response, and projection data formats are proprietary information. Further, some published image-based, 3-material decomposition methods require a volume conservation assumption, which is often violated in solutions. We have developed an image-based material decomposition method that can overcome those limitations. We introduced a general condition on volume constraint that does not require the volume to be conserved in a mixture. An empirical calibration can be performed with various concentrations of basis materials. The material decomposition method was applied to images acquired from a prototype whole-body PCCT scanner. The results showed good agreement between the estimation and known mass concentration values. Factors affecting the performance of material decomposition, such as energy threshold configuration and volume conservation constraint, were also investigated. Changes in accuracy of the mass concentration estimates were demonstrated for four different energy configurations and when volume conservation was assumed.

Sensitization and chronic beryllium disease at a primary manufacturing facility, part 3: exposure–response among short-term workers

Exposure-response relations for beryllium sensitization (BeS) and chronic beryllium disease (CBD) using aerosol mass concentration have been inconsistent, although process-related risks found in most studies suggest that exposure-dependent risks exist. We examined exposure-response relations using personal exposure estimates in a beryllium worker cohort with limited work tenure to minimize exposure misclassification. The population comprised workers employed in 1999 with six years or less tenure. Each completed a work history questionnaire and was evaluated for immunological sensitization and CBD. A job-exposure matrix was combined with work histories to create individual estimates of average, cumulative, and highest-job-worked exposure for total, respirable, and submicron beryllium mass concentrations. We obtained odds ratios from logistic regression models for exposure-response relations, and evaluated process-related risks. Participation was 90.7% (264/291 eligible). Sensitization prevalence was 9.8% (26/264), with 6 sensitized also diagnosed with CBD (2.3%, 6/264). A general pattern of increasing sensitization prevalence was observed as exposure quartile increased. Both total and respirable beryllium mass concentration estimates were positively associated with sensitization (average and highest job), and CBD (cumulative). Increased sensitization prevalence was identified in metal/oxide production, alloy melting and casting, and maintenance, and for CBD in melting and casting. Lower sensitization prevalence was observed in plant-area administrative work. Sensitization was associated with average and highest job exposures, and CBD was associated with cumulative exposure. Both total and respirable mass concentrations were relevant predictors of risk. New process-related risks were identified in melting and casting and maintenance.

Field evaluation of portable and central site PM samplers emphasizing additive and differential mass concentration estimates

The US Environmental Protection Agency (EPA) published a National Ambient Air Quality Standard (NAAQS) and the accompanying Federal Reference Method (FRM) for PM10 in 1987. The EPA revised the particle standards and FRM in 1997 to include PM2.5. In 2005, EPA proposed revisions to this NAAQS to include PM10–2.5 but only finalized revisions with a PM2.5 FRM and the development of a national monitoring network in 2006. Presently, no EPA designated reference or equivalent method sampler has the ability to directly measure the mass concentrations of PM10, PM10–2.5, and PM2.5 simultaneously. An additive approach has been used for samplers like the dichotomous monitors to calculate PM10 mass concentrations from independent measures of PM10–2.5 and PM2.5 (i.e. PM10 = PM10–2.5 + PM2.5). A differential approach has been used to calculate PM10–2.5 from identical collocated PM10 and PM2.5 samplers (i.e. PM10–2.5 = PM10–PM2.5). Since these two approaches have been used widely for PM measurements, it is informative to evaluate their precision and comparability. EPA performed collocated tests of five different particle samplers in the Research Triangle Park area of North Carolina to evaluate the comparability and to characterize the additive and differential approaches used to determine particle mass concentrations. The intra-sampler precision of MiniVol, Omni, and dichotomous samplers was less than 8.4%. The precision of PM10 measurements using the additive approach with dichotomous samplers was less than 3.5%. The poorest precision of the various PM10–2.5 differential approaches was less than 15.1%. No zero or negative PM10–2.5 concentrations were calculated using the differential approach. A coefficient of determination of 0.81 or higher was obtained for all paired comparison of PM10–2.5. The reported test results show that concentrations calculated from both the additive and differential approaches generally agree among the portable samplers, the more established dichotomous sampler and the Federal Reference Methods

Vertical distribution of aerosols in the vicinity of Mexico City during MILAGRO-2006 Campaign

Abstract. On 7 March 2006, a mobile, ground-based, vertical pointing, elastic lidar system made a North-South transect through the Mexico City basin. Column averaged, aerosol size distribution (ASD) measurements were made on the ground concurrently with the lidar measurements. The ASD ground measurements allowed calculation of the column averaged mass extinction efficiency (MEE) for the lidar system (1064 nm). The value of column averaged MEE was combined with spatially resolved lidar extinction coefficients to produce total aerosol mass concentration estimates with the resolution of the lidar (1.5 m vertical spatial and 1 s temporal). Airborne ASD measurements from DOE G-1 aircraft made later in the day on 7 March 2006, allowed the evaluation of the assumptions of constant ASD with height and time used for estimating the column averaged MEE. The results showed that the aerosol loading within the basin is about twice what is observed outside of the basin. The total aerosol base concentrations observed in the basin are of the order of 200 μg/m3 and the base levels outside are of the order of 100 μg/m3. The local heavy traffic events can introduce aerosol levels near the ground as high as 900 μg/m3. The article presents the methodology for estimating aerosol mass concentration from mobile, ground-based lidar measurements in combination with aerosol size distribution measurements. An uncertainty analysis of the methodology is also presented.

Parameterization of aerosol indirect effect to complement McRAS cloud scheme and its evaluation with the 3-year ARM-SGP analyzed data for single column models

Microphysics of clouds with the Relaxed Arakawa–Schubert Scheme (McRAS) was upgraded for simulating the Aerosol Indirect Effects (AIE) for water clouds. The AIE comprises of i) Fountoukis and Nenes aerosol activation module for obtaining cloud condensation nuclei; ii) Seifert and Beheng algorithms for precipitation microphysics but with modified accretion constant for the coarse vertical-resolution typical of a global general circulation model (GCM); and iii) Khvorostyanov and Curry parameterization for computing the effective radius ( r e ) of cloud drops. The upgraded package, named McRAS-AC, was evaluated using the 3-year ARM-SGP Single Column Model (SCM) data. Invoking only the most dominant sulfate aerosols over the region, McRAS-AC simulated realistic annual mean and annual cycles of cloud water, cloud optical thicknesses, cloud drop number concentration, and r e . The follow-on SCM-sensitivity simulations showed that accretion of cloud water is sensitive to i) the terminal velocity of hydrometeors produced by autoconversion and ii) cloud height increases due to in-cloud condensation heating. The impact of aerosol mass concentration on the resultant column cloud water, and bulk optical properties of clouds were assessed by using 1/8 to 8 times the average monthly aerosol mass concentration estimates of GOCART aerosol climatology. A log-linear relation between cloud-radiative forcing and aerosol-mass concentration emerged in the simulated data.

Measuring suspended sand concentration using acoustic backscatter: a critical look at the errors and uncertainties

AbstractSuspended sand concentrations in the near-bed layer of the sea can be estimated using acoustic backscatter systems (ABS) and hence, when combined with velocity, sand transport. ABS measurements are now relatively routine and widely regarded as one of the best tools to help to measure sand transport in coastal seas and estuaries. Potentially the ABS can be used to give estimates of both concentration and sediment size with a vertical resolution of 5–10 mm and a temporal resolution of fractions of a second, but in practice there are many practical limitations to what can be achieved in the field. Often these uncertainties are overlooked or ignored because of the difficulty in estimating their magnitude or of making measurements that are any better. The major limitations and sources of errors in the ABS are discussed, including the influence of sediment size and shape. In moderately to well-sorted sandy environments with appropriate calibration, acoustic estimates of mass concentration should be within ± 30% of the true value.

Coarse particulate matter concentrations from residential outdoor sites associated with the North Carolina Asthma and Children's Environment Studies (NC-ACES)

Coarse particulate matter (PM 10 - 2.5 ) concentration data from residential outdoor sites were collected using portable samplers as part of an exposure assessment for the North Carolina Asthma and Children's Environment Studies (NC-ACES). PM 10 - 2.5 values were estimated using the differential between independent PM 10 and PM 2.5 collocated MiniVol measurements. Repeated daily 24-h integrated PM 10 and PM 2.5 residential outdoor monitoring was performed at a total of 26 homes during September 2003–June 2004 in the Research Triangle Park, NC area. This effort resulted in the collection of 73 total daily measurements. This assessment was conducted to provide data needed to investigate the association of exposures to coarse particle PM mass concentrations with observed human health effects. Potential instrument bias between the differential MiniVol methodology and a dichotomous sampler were investigated. Results indicated that minimal bias of PM 10 - 2.5 mass concentration estimates (slope = 0.8, intercept = 0.36 μ g m - 3 ) existed between the dichotomous and differential MiniVol procedures. Residential outdoor PM 10 - 2.5 mass concentrations were observed to be highly variable across measurement days and ranged from 1.1 to 12.6 μ g m - 3 (mean of 5.4 μ g m - 3 ) . An average correlation coefficient of r = 0.75 existed between residential outdoor PM 10 - 2.5 mass concentrations and those obtained from the central ambient monitoring site. Temporal and spatial variability of PM 10 - 2.5 mass concentrations during the study were observed and are described in this report.

Estimating suspended solids concentrations from backscatter intensity measured by acoustic Doppler current profiler in San Francisco Bay, California

The estimation of mass concentration of suspended solids is one of the properties needed to understand the characteristics of sediment transport in bays and estuaries. However, useful measurements or estimates of this property are often problematic when employing the usual methods of determination from collected water samples or optical sensors. Analysis of water samples tends to undersample the highly variable character of suspended solids, and optical sensors often become useless from biological fouling in highly productive regions. Acoustic sensors, such as acoustic Doppler current profilers that are now routinely used to measure water velocity, have been shown to hold promise as a means of quantitatively estimating suspended solids from acoustic backscatter intensity, a parameter used in velocity measurement. To further evaluate application of this technique using commercially available instruments, profiles of suspended solids concentrations are estimated from acoustic backscatter intensity recorded by 1200- and 2400-kHz broadband acoustic Doppler current profilers located at two sites in San Francisco Bay, California. ADCP backscatter intensity is calibrated using optical backscatterance data from an instrument located at a depth close to the ADCP transducers. In addition to losses from spherical spreading and water absorption, calculations of acoustic transmission losses account for attenuation from suspended sediment and correction for nonspherical spreading in the near field of the acoustic transducer. Acoustic estimates of suspended solids consisting of cohesive and noncohesive sediments are found to agree within about 8–10% (of the total range of concentration) to those values estimated by a second optical backscatterance sensor located at a depth further from the ADCP transducers. The success of this approach using commercially available Doppler profilers provides promise that this technique might be appropriate and useful under certain conditions in spite of some theoretical limitations of the method.

Vertical distribution of nighttime smoke following a wildland biomass fire in boreal Alaska

A comprehensive evaluation of the vertical structure of a smoldering smoke plume was afforded by a unique combination of tethersonde measurements (from ground level to about 400 m above ground level (AGL) or 274–674 m above sea level (ASL)), lidar sounding (from about 1.5 to 5 km ASL), and a video recording during the FROSTFIRE experimental burn in July 1999. Tethersonde and lidar measurements were made at local midnight. The video camera operated continuously for 1 week. Estimates of mass concentration were derived from the light‐scattering measurements. Every night, upper level smoke concentrations were estimated to be about 1000 times lower than near‐surface concentrations. The tethersonde instrument indicated maximum mass concentrations on the night following the most active burning (10–11 July), with the smoke trapped below an inversion at 115 m AGL. The lidar measurements indicated that maximum mass concentrations aloft (∼2000 m AGL) occurred on the next night (11–12 July), when the inversion was weaker, and estimated mass concentrations in the first few hundred meters ASL were smaller. The opportunistic combination of instruments offers the first available quantitative information on vertical plume structure in smoldering biomass smoke and holds promise for more a rigorous understanding of smoldering smoke as it significantly impacts visibility and human health.

Impact of correcting peak flow for nonlinear errors on air pollutant effect estimates from a panel study

Air pollutant effects are commonly investigated using panel studies employing daily measurement of changes in peak expiratory flow (PEF). Variable orifice PEF meters are inaccurate with a nonlinear relationship to actual PEF. The impact on a panel study of correcting these errors was examined. Twice-daily PEF readings were taken by 147 9-yr old children for 8 weeks and corrected using an equation derived from the response of 32 Vitalograph meters to a servomechanism-controlled pump. Pollutant effect estimates for corrected and uncorrected readings were derived using a regression approach incorporating appropriate confounders. Correction impacted little on mean PEF values (333.1-334.2 L x min(-1)), but did alter effect sizes. Nonsignificant nitrogen dioxide estimates for the entire panel decreased by up to 73%, but, for symptomatic/atopic children, a significant 5-day mean result was lost (decrease in effect size from -2.53 to -0.90% per 10 parts per billion (ppb)) and lag 0 became significant (decrease from -0.51 to -1.22% per 10 ppb). Mass concentration estimates of particles with a 50% cut-off aerodynamic diameter of 2.5 microm moved in both directions (-0.22 changed to 0.11% per 10 microg x m(-1) lag 3 and -0.29 to -0.73% per 10 microg x m(-3) for the 5-day mean). Correction of nonlinearity of peak expiratory flow meters influenced the overall outcome of this panel study, and the changes in effect estimates would be sufficient to alter the interpretation of some studies. For adults, a greater change in effect estimates may follow the larger correction required for their usual peak expiratory flow range.

Impact of correcting peak flow for nonlinear errors on air pollutant effect estimates from a panel study.

Air pollutant effects are commonly investigated using panel studies employing daily measurement of changes in peak expiratory flow (PEF). Variable orifice PEF meters are inaccurate with a nonlinear relationship to actual PEF. The impact on a panel study of correcting these errors was examined. Twice-daily PEF readings were taken by 147 9-yr old children for 8 weeks and corrected using an equation derived from the response of 32 Vitalograph meters to a servomechanism-controlled pump. Pollutant effect estimates for corrected and uncorrected readings were derived using a regression approach incorporating appropriate confounders. Correction impacted little on mean PEF values (333.1-334.2 L x min(-1)), but did alter effect sizes. Nonsignificant nitrogen dioxide estimates for the entire panel decreased by up to 73%, but, for symptomatic/atopic children, a significant 5-day mean result was lost (decrease in effect size from -2.53 to -0.90% per 10 parts per billion (ppb)) and lag 0 became significant (decrease from -0.51 to -1.22% per 10 ppb). Mass concentration estimates of particles with a 50% cut-off aerodynamic diameter of 2.5 microm moved in both directions (-0.22 changed to 0.11% per 10 microg x m(-1) lag 3 and -0.29 to -0.73% per 10 microg x m(-3) for the 5-day mean). Correction of nonlinearity of peak expiratory flow meters influenced the overall outcome of this panel study, and the changes in effect estimates would be sufficient to alter the interpretation of some studies. For adults, a greater change in effect estimates may follow the larger correction required for their usual peak expiratory flow range.

Development of a method for the determination of low contents of asbestos fibres in bulk material.

Asbestos is a category 1 carcinogen under the EU classification, but in the absence of a method to quantify asbestos in a matrix at the 0.1% level, there has been a delay in implementing relevant directives to asbestos. An analytical scheme for identification and quantification of asbestos using polarised light microscopy (PLM) and phase contrast optical microscopy (PCM) has now been developed. When used on artificial mixtures by an experienced laboratory, it achieved the required target performance, at 0.1% asbestos concentration by mass in a bulk sample, to obtain a result, which with 90% probability, is correct within a factor of two. The method of identification by PLM and quantification by PCM has been assessed by interlaboratory comparisons. The method begins with an initial identification using PLM, and depending on asbestos type and matrix a combination of preparation procedures are used to produce the analytical filter. A gentle comminution method was used which reduces the risk of overmilling. The asbestos mass percentage on the filter is quantified using PCM in combination with a PLM attachment for identification of possible non-asbestos fibres. The final method is supported by efficient methods for fibre identification for size determination and calculation of total fibre volume. A statistical analysis of mass concentration estimates was made and the effect of preferred orientation of fibres on the analytical filter was quantified.

Application of isoperimetric inequalities to the problem of acoustic scattering from irregularly shaped objects

It is of general interest to determine the extent that acoustic remote sensing can estimate physical properties of particulates suspended in the ocean. One question that can be asked is how well the concentration of particulates can be determined from measurements of the backscattered acoustic intensity. When it applies, Rayleigh scattering theory provides the relationship between the concentration and the intensity. The assumption is always made in application of the theory that the individual scatterers can be regarded as spheres. While this assumption is intuitively reasonable, it is desirable to have error estimates. In this work, bounds are derived for the error that can occur in mass-concentration estimates due to the spherical-scatterer assumption. These bounds are obtained by using the theory of isoperimetric inequalities and are rigorous; depending only on the validity of Rayleigh scattering theory. The formalism is applied to the problem of estimating the concentration of particulates in black smoker hydrothermal plumes. These particulates consist of several different metallic sulfides having different size distributions. It is found that the spherical-scatterer assumption results in over-estimating the total mass concentration by at most a factor of 5 and under-estimating it by at most a factor of 0.7.