Evaluation of airborne asbestos exposure from routine handling of asbestos-containing wire gauze pads in the research laboratory.

Three independently conducted asbestos exposure evaluations were conducted using wire gauze pads similar to standard practice in the laboratory setting. All testing occurred in a controlled atmosphere inside an enclosed chamber simulating a laboratory setting. Separate teams consisting of a laboratory technician, or technician and assistant simulated common tasks involving wire gauze pads, including heating and direct wire gauze manipulation. Area and personal air samples were collected and evaluated for asbestos consistent with the National Institute of Occupational Safety Health method 7400 and 7402, and the Asbestos Hazard Emergency Response Act (AHERA) method. Bulk gauze pad samples were analyzed by Polarized Light Microscopy and Transmission Electron Microscopy to determine asbestos content. Among air samples, chrysotile asbestos was the only fiber found in the first and third experiments, and tremolite asbestos for the second experiment. None of the air samples contained asbestos in concentrations above the current permissible regulatory levels promulgated by OSHA. These findings indicate that the level of asbestos exposure when working with wire gauze pads in the laboratory setting is much lower than levels associated with asbestosis or asbestos-related lung cancer and mesothelioma.

Evaluation of recommended REACH exposure modeling tools and near-field, far-field model in assessing occupational exposure to toluene from spray paint.

Predictive modeling is an available tool to assess worker exposures to a variety of chemicals in different industries and product-use scenarios. The European Chemical Agency (ECHA)'s guidelines for manufacturers to fulfill the European Union's legal requirements pursuant to the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) initiative include recommendations for the use of modeling to predict worker exposures. ECHA recommends different models for different target populations (i.e. workers, consumers, environment) and routes of exposure (i.e. skin absorption, ingestion, inhalation), and presents them hierarchically, with Tier 1 models presented as the most simplistic, conservative models and Tier 2 models recommended for further intensive evaluation of substances or preparations. In order to assess these models for one exposure (product-use) scenario, a simulation of the scenario was completed in a controlled environment and the measured results were compared with the modeling outputs. The authors predicted, based on the design of the modeling tools, that all models would overestimate worker exposures under the simulated product-use scenario, with the lower-tiered model producing the most conservative estimate of exposure. In this study, a Tier 1 model and a Tier 2 model were evaluated for comparison with the near-field, far-field (NF-FF) deterministic model and measured experimental results in a real-time worker inhalation exposure assessment. Modeling was conducted prior to actual air monitoring. The exposure scenario that was evaluated involved the application of a toluene-containing spray paint to a work surface. Air samples were collected to evaluate short-term (15-min) and long-term (240-min) exposures. Eight-hour time-weighted averages (8-h TWAs) were calculated and compared with the modeling outputs from the recommended REACH modeling tools and the NF-FF model. A comparison of each of the modeling tools with measured experimental results was generated. The Tier 1 Targeted Risk Assessment tool overestimated the 8-h TWA airborne concentration of toluene in the spray scenario by a factor of 3.61. The higher tiered Advanced REACH Tool and NF-FF models showed greater concordance with experimental results, overestimating the TWA exposure by a factor of 2.92 and 1.96, respectively. In conclusion, the Tier 1 and 2 exposure modeling tools performed as expected for the simulated exposure scenario, providing relatively accurate, though conservative, estimates according to the level of detail and precision accounted for in each model.

Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage.

Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.

Extended X-Ray Absorption Fine Structure of ZrW2O8: Theory vs. Experiment.

Extended x-ray absorption fine structure (EXAFS) is well-suited for investigations of structure and disorder of complex materials. Recently, experimental measurements and analysis of EXAFS have been carried out to elucidate the mechanisms responsible for the negative thermal expansion (NTE) in zirconium tungstate (ZrW2O8). In contrast to previous work suggesting that transverse O-displacements are largely responsible, the EXAFS analysis suggested that correlated rotations and translations of octahedra and tetrahedra within the structure are a major source. In an effort to resolve this controversy, we have carried out ab initio calculations of the structure, lattice vibrations, and EXAFS of ZrW2O8 based on real-space multiple-scattering calculations using the FEFF9 code and auxiliary calculations of structure and Debye-Waller factors. We find that the theoretical simulations are consistent with observed EXAFS, and show that both of the above mechanisms contribute to the dynamical structure of ZrW2O8.

A comparison study using a mathematical model and actual exposure monitoring for estimating solvent exposures during the disassembly of metal parts.

The objective of this research was to compare the airborne solvent concentrations measured during the disassembly of solvent-coated metal parts with concentrations predicted by a mathematical model. The study involved three test simulations where cyclohexane, used as a penetrating solvent, was squirted onto a gate valve while the valve was subsequently disassembled. Three test simulations were performed to evaluate the effect of varying the speed of random air movement in the work area. For statistical considerations, six replicate solvent application trials were conducted for each simulation. Area and personal air samples were collected during the trials performed under each test simulation. Cyclohexane was applied to the valve at a consistent rate to obtain, to the greatest extent possible, a constant generation rate of solvent vapors. The Near Field-Far Field (NF-FF) model, applied using a constant solvent generation rate, was selected to predict the solvent vapor concentrations, and Monte Carlo analysis was used to quantify uncertainty in the input parameters of the model. Solvent concentration predictions obtained from the modeling process were within a multiplicative factor of 0.1 to 1.5 of the arithmetic mean of the actual air sample results for all three NF and FF conditions in each simulation. Application of the NF-FF model under the conditions described suggests there is a reasonable degree of reliability in forecasting airborne contaminant levels in the workplace environment. Given the limited resources faced today by many industrial hygienists, exposure modeling can serve as a valuable tool for generating the information needed to make informed decisions about employee exposure.

Heavy equipment maintenance exposure assessment: using a time-activity model to estimate surrogate values for replacement of missing data.

This study on four pieces of heavy construction equipment was conducted to determine the concentration of airborne asbestos fibers during in-frame maintenance and repair activities, which included aggressive techniques that resulted in visible dust from work involving friction products and gaskets. Despite execution of a carefully planned sampling strategy, approximately 10% (47) of the samples collected could not be analyzed due to overloading or filter damage. To include the overloaded samples in the data analysis, surrogate values were estimated following a time-activity model. Twelve long-term personal samples, 2 short-term, 30-min personal samples, and 31 long-term area samples were modeled. Personal and area time-weighted average (TWA) data were analyzed both with and without the estimated surrogate values and compared. A total of 444 samples were collected over 9 days. Four experienced heavy equipment mechanics removed and replaced friction products and gaskets. Samples were analyzed using NIOSH Method 7400 Phase Contrast Microscopy followed by NIOSH Method 7402 Transmission Electron Microscopy. Sample data information including the surrogate values for the full-shift, TWA personal sample results ranged from 0.002 to 0.064 asbestos f/cc. Personal, short-term, 30-min sample results, including the two surrogate values, ranged from 0.038 to 0.561 asbestos f/cc. Full-shift TWA area samples, including the 31 surrogate values, ranged from 0.005 to 0.039 asbestos f/cc. Area air sample results at the end of the project were similar to levels measured before the start of the project. No fiber concentration buildup within the work area was indicated over the 9-day study. All full-shift personal and area TWA sample results were below 0.1 f/cc, and short-term 30-min personal samples were below 1.0 f/cc. Statistical results of the sample data with and without the surrogate values were consistent. Use of the time-activity model reduced the uncertainty associated with this data analysis and provided a consistent logical process for estimating surrogate values to replace missing data.

Estimating benzene exposure at a solvent parts washer.

A mathematical model is described for estimating benzene exposure at a parts washer using petroleum distillates solvent containing benzene. The basic assumptions are that the benzene mass emission rate exponentially decreases over time, and that the air above the parts washer basin to which a worker is exposed is part of a well-mixed air zone termed the near field (relative to the source location). Two previously conducted simulations of the parts washer process are described. A single 1-hour time-weighted average (TWA) benzene concentration was measured during Simulation #1, and two 4-hour TWA benzene concentrations were measured during Simulation #2. The initial benzene concentrations in the solvents were known, and the exponential loss rate constants were estimated from subsequent determinations of the benzene concentrations. Values for the interzonal airflow rate were estimated based on the conceptual geometry of the near field zone and sparse information on air speed near the parts washers. Minimum values for the room supply/exhaust air rate were estimated based on the room volumes and ventilation conditions. The modeled benzene concentrations were within a multiplicative range of one-half to twofold the measured concentrations. Uncertainty in a model estimate was quantified by Monte Carlo analysis; the distributions of model estimates exhibited coefficients of variation of approximately 40%. Issues related to uncertainty in exposure estimates made by mathematical modeling are discussed.