C-reactive protein from dried blood spots: Application to household air pollution field studies.

Household air pollution (HAP) is estimated to be an important risk factor for cardiovascular disease, but little clinical evidence exists and collecting biomarkers of disease risk is difficult in low-resource settings. Among 54 Nicaraguan women with woodburning cookstoves, we evaluated cross-sectional associations between 48-hour measures of HAP (eg, fine particulate matter, PM2.5 ) and C-reactive protein (CRP) via dried blood spots; secondary analyses included seven additional biomarkers of systemic injury and inflammation. We conducted sub-studies to calculate the intraclass correlation coefficient (ICC) in biomarkers collected over four consecutive days in Nicaragua and to assess the validity of measuring biomarkers in dried blood by calculating the correlation with paired venous-drawn samples in Colorado. Measures of HAP were associated with CRP (eg, a 25% increase in indoor PM2.5 was associated with a 7.4% increase in CRP [95% confidence interval: 0.7, 14.5]). Most of the variability in CRP concentrations over the 4-day period was between-person (ICC: 0.88), and CRP concentrations were highly correlated between paired dried blood and venous-drawn serum (Spearman ρ = .96). Results for secondary biomarkers were primarily consistent with null associations, and the sub-study ICCs and correlations were lower. Assessing CRP via dried blood spots provides a feasible approach to elucidate the association between HAP and cardiovascular disease risk.

Low-Cost, Distributed Environmental Monitors for Factory Worker Health.

An integrated network of environmental monitors was developed to continuously measure several airborne hazards in a manufacturing facility. The monitors integrated low-cost sensors to measure particulate matter, carbon monoxide, ozone and nitrogen dioxide, noise, temperature and humidity. The monitors were developed and tested in situ for three months in several overlapping deployments, before a full cohort of 40 was deployed in a heavy vehicle manufacturing facility for a year of data collection. The monitors collect data from each sensor and report them to a central database every 5 min. The work includes an experimental validation of the particle, gas and noise monitors. The R² for the particle sensor ranges between 0.98 and 0.99 for particle mass densities up to 300 μg/m³. The R² for the carbon monoxide sensor is 0.99 for concentrations up to 15 ppm. The R² for the oxidizing gas sensor is 0.98 over the sensitive range from 20 to 180 ppb. The noise monitor is precise within 1% between 65 and 95 dBA. This work demonstrates the capability of distributed monitoring as a means to examine exposure variability in both space and time, building an important preliminary step towards a new approach for workplace hazard monitoring.

Optimizing a Sensor Network with Data from Hazard Mapping Demonstrated in a Heavy-Vehicle Manufacturing Facility.

Objectives: To design a method that uses preliminary hazard mapping data to optimize the number and location of sensors within a network for a long-term assessment of occupational concentrations, while preserving temporal variability, accuracy, and precision of predicted hazards. Methods: Particle number concentrations (PNCs) and respirable mass concentrations (RMCs) were measured with direct-reading instruments in a large heavy-vehicle manufacturing facility at 80-82 locations during 7 mapping events, stratified by day and season. Using kriged hazard mapping, a statistical approach identified optimal orders for removing locations to capture temporal variability and high prediction precision of PNC and RMC concentrations. We compared optimal-removal, random-removal, and least-optimal-removal orders to bound prediction performance. Results: The temporal variability of PNC was found to be higher than RMC with low correlation between the two particulate metrics (ρ = 0.30). Optimal-removal orders resulted in more accurate PNC kriged estimates (root mean square error [RMSE] = 49.2) at sample locations compared with random-removal order (RMSE = 55.7). For estimates at locations having concentrations in the upper 10th percentile, the optimal-removal order preserved average estimated concentrations better than random- or least-optimal-removal orders (P < 0.01). However, estimated average concentrations using an optimal-removal were not statistically different than random-removal when averaged over the entire facility. No statistical difference was observed for optimal- and random-removal methods for RMCs that were less variable in time and space than PNCs. Conclusions: Optimized removal performed better than random-removal in preserving high temporal variability and accuracy of hazard map for PNC, but not for the more spatially homogeneous RMC. These results can be used to reduce the number of locations used in a network of static sensors for long-term monitoring of hazards in the workplace, without sacrificing prediction performance.

Sampling Strategies for Accurate Hazard Mapping of Noise and Other Hazards Using Short-Duration Measurements.

Hazard mapping is an effective way to depict spatial variability in hazard intensity obtained with direct-reading instruments on a facility floor plan. However, the extent to which temporal variability affects map accuracy is unknown, and guidance on sampling strategies to minimize map bias is lacking. In this study, we evaluated the accuracy of hazard maps produced for simulated sources and sampling strategies in a hypothetical facility. Hazard maps were produced from sampled data at high, mid, and low spatial resolution and with and without replicates and compared to a reference time-weighted average hazard map using several map comparison metrics. In agreement with 'real-world' mapping datasets, the simulation showed that increasing the number of replicates improved the overall comparability of the hazard map produced from the sampled data with the time-weighted average hazard map more efficiently than increasing the sampling spatial resolution. However, if accurately capturing peak exposures near sources is of interest, increasing the spatial resolution of the measurements, particularly near sources, is needed. From these results, we formulated guidelines to use the preliminary assessment of the temporal variability of large and intermittent sources to inform the spatial resolution and need for replicate measures to minimize the bias in hazard maps.

New Methods for Personal Exposure Monitoring for Airborne Particles.

Airborne particles have been associated with a range of adverse cardiopulmonary outcomes, which has driven its monitoring at stationary central sites throughout the world. Individual exposures, however, can differ substantially from concentrations measured at central sites due to spatial variability across a region and sources unique to the individual, such as cooking or cleaning in homes, traffic emissions during commutes, and widely varying sources encountered at work. Personal monitoring with small, battery-powered instruments enables the measurement of an individual's exposure as they go about their daily activities. Personal monitoring can substantially reduce exposure misclassification and improve the power to detect relationships between particulate pollution and adverse health outcomes. By partitioning exposures to known locations and sources, it may be possible to account for variable toxicity of different sources. This review outlines recent advances in the field of personal exposure assessment for particulate pollution. Advances in battery technology have improved the feasibility of 24-h monitoring, providing the ability to more completely attribute exposures to microenvironment (e.g., work, home, commute). New metrics to evaluate the relationship between particulate matter and health are also being considered, including particle number concentration, particle composition measures, and particle oxidative load. Such metrics provide opportunities to develop more precise associations between airborne particles and health and may provide opportunities for more effective regulations.

Effects of data sparsity and spatiotemporal variability on hazard maps of workplace noise.

Personal sampling, considered a state-of-the-art technique to assess worker exposures to occupational hazards, is often conducted for the duration of a work shift so that time-weighted average (TWA) exposures may be evaluated relative to published occupational exposure limits (OELs). Such cross-shift measurements, however, provide little information on the spatial variability of exposures, except after a very large number of samples. Hazard maps, contour plots (or similar depiction) of hazard intensity throughout the workplace, have gained popularity as a way to locate sources and to visualize spatial variability of physical and chemical hazards within a facility. However, these maps are often generated from short duration measures and have little ability to assess temporal variability. To assess the potential bias that results from the use of short-duration measurements to represent the TWA in a hazard map, noise intensity measurements were collected at high spatial and temporal resolution in two facilities. Static monitors were distributed throughout the facility and used to capture the temporal variability at these locations. Roving monitors (typical of the hazard mapping process) captured spatial variability over multiple traverses through the facility. The differences in hazards maps generated with different sampling techniques were evaluated. Hazard maps produced from sparse, roving monitor data were in good agreement with the TWA hazard maps at the facility with low temporal variability. Estimated values were within 5 dB of the TWA over approximately 90% of the facility. However, at the facility with higher temporal variability, large differences between hazard maps were observed for different traverses through the facility. On the second day of sampling, estimates were at least 5 dB different than the TWA for more than half of the locations within the facility. The temporal variability of noise was found to have a greater influence on map accuracy than the spatial sampling resolution.

Development of a sampler to estimate regional deposition of aerosol in the human respiratory tract.

A multistage sampler was developed and tested to estimate regional deposition of aerosol in the human respiratory system. The motivation for this research is to improve our ability to estimate inhaled aerosol dose. Current methods for aerosol measurement and exposure/risk assessment are based on particle aspiration (e.g. inhalable PM) or on penetration to various regions of the respiratory system (e.g. PM10). The sampler developed here operates at 1 m(3) h(-1) (16.7 l min(-1)) of flow and utilizes several substrates, connected in series, to mimic regional particle deposition. Two sets of polyurethane foam substrates are used to mimic particle deposition in the head airways and tracheobronchial regions, respectively. Particle deposition in the alveolar region is mimicked using diffusion screens. These substrates are amenable to trace chemical analyses but not gravimetric analyses, due to water vapor uptake with small changes in relative humidity.

Influence of analysis methods on interpretation of hazard maps.

Exposure or hazard mapping is becoming increasingly popular among industrial hygienists. Direct-reading instruments used for hazard mapping of data collection are steadily increasing in reliability and portability while decreasing in cost. Exposure measurements made with these instruments generally require no laboratory analysis although hazard mapping can be a time-consuming process. To inform decision making by industrial hygienists and management, it is crucial that the maps generated from mapping data are as accurate and representative as possible. Currently, it is unclear how many sampling locations are necessary to produce a representative hazard map. As such, researchers typically collect as many points as can be sampled in several hours and interpolation methods are used to produce higher resolution maps. We have reanalyzed hazard-mapping data sets from three industrial settings to determine which interpolation methods yield the most accurate results. The goal is to provide practicing industrial hygienists with some practical guidelines to generate accurate hazard maps with 'off-the-shelf' mapping software. Visually verifying the fit of the variogram model is crucial for accurate interpolation. Exponential and spherical variogram models performed better than Gaussian models. It was also necessary to diverge from some of the default interpolation parameters such as the number of bins used for the experimental variogram and whether or not to allow for a nugget effect to achieve reasonable accuracy of the interpolation for some data sets.

Solid versus liquid particle sampling efficiency of three personal aerosol samplers when facing the wind.

The objective of this study was to examine the facing-the-wind sampling efficiency of three personal aerosol samplers as a function of particle phase (solid versus liquid). Samplers examined were the IOM, Button, and a prototype personal high-flow inhalable sampler head (PHISH). The prototype PHISH was designed to interface with the 37-mm closed-face cassette and provide an inhalable sample at 10 l min(-1) of flow. Increased flow rate increases the amount of mass collected during a typical work shift and helps to ensure that limits of detection are met, particularly for well-controlled but highly toxic species. Two PHISH prototypes were tested: one with a screened inlet and one with a single-pore open-face inlet. Personal aerosol samplers were tested on a bluff-body disc that was rotated along the facing-the-wind axis to reduce spatiotemporal variability associated with sampling supermicron aerosol in low-velocity wind tunnels. When compared to published data for facing-wind aspiration efficiency for a mouth-breathing mannequin, the IOM oversampled relative to mannequin facing-the-wind aspiration efficiency for all sizes and particle types (solid and liquid). The sampling efficiency of the Button sampler was closer to the mannequin facing-the-wind aspiration efficiency than the IOM for solid particles, but the screened inlet removed most liquid particles, resulting in a large underestimation compared to the mannequin facing-the-wind aspiration efficiency. The open-face PHISH results showed overestimation for solid particles and underestimation for liquid particles when compared to the mannequin facing-the-wind aspiration efficiency. Substantial (and statistically significant) differences in sampling efficiency were observed between liquid and solid particles, particularly for the Button and screened-PHISH, with a majority of aerosol mass depositing on the screened inlets of these samplers. Our results suggest that large droplets have low penetration efficiencies through screened inlets and that particle bounce, for solid particles, is an important determinant of aspiration and sampling efficiencies for samplers with screened inlets.

Prospects and pitfalls of occupational hazard mapping: 'between these lines there be dragons'.

Hazard data mapping is a promising new technique that can enhance the process of occupational exposure assessment and risk communication. Hazard maps have the potential to improve worker health by providing key input for the design of hazard intervention and control strategies. Hazard maps are developed with aid from direct-reading instruments, which can collect highly spatially and temporally resolved data in a relatively short period of time. However, quantifying spatial-temporal variability in the occupational environment is not a straightforward process, and our lack of understanding of how to ascertain and model spatial and temporal variability is a limiting factor in the use and interpretation of workplace hazard maps. We provide an example of how sources of and exposures to workplace hazards may be mischaracterized in a hazard map due to a lack of completeness and representativeness of collected measurement data. Based on this example, we believe that a major priority for research in this emerging area should focus on the development of a statistical framework to quantify uncertainty in spatially and temporally varying data. In conjunction with this need is one for the development of guidelines and procedures for the proper sampling, generation, and evaluation of workplace hazard maps.

A rotating bluff-body disc for reduced variability in wind tunnel aerosol studies.

A rotating bluff-body disc (RBD) was developed to reduce spatiotemporal variability associated with sampling supermicron aerosol in low-velocity wind tunnels. The RBD is designed to rotate eight personal aerosol samplers around a circular path in a forward-facing plane aligned with the wind tunnel cross section. Rotation of the RBD allows each sampler to traverse an identical path about the wind tunnel cross section, which reduces the effects of spatial heterogeneity associated with dispersing supermicron aerosol in low-velocity wind tunnels. Samplers are positioned on the face of the RBD via sampling ports, which connect to an air manifold on the back of the disc. Flow through each sampler was controlled with a critical orifice or needle valve, allowing air to be drawn through the manifold with a single pump. A metal tube, attached to this manifold, serves as both the axis of rotation and the flow conduction path (between the samplers and the vacuum source). Validation of the RBD was performed with isokinetic samplers and 37-mm cassettes. For facing-the-wind tests, the rotation of the RBD significantly decreased intra-sampler variability when challenged with particle diameters from 1 to 100 µm. The RBD was then employed to determine the aspiration efficiency of Institute of Occupational Medicine (IOM) personal samplers under a facing-the-wind condition. Operation of IOM samplers on the RBD reduced the between-sampler variability for all particle sizes tested.

Cloud condensation nuclei and ice nucleation activity of hydrophobic and hydrophilic soot particles.

Cloud condensation nuclei (CCN) activity and ice nucleation behavior (for temperatures

Development of a sampler for total aerosol deposition in the human respiratory tract.

Studies that seek to associate reduced human health with exposure to occupational and environmental aerosols are often hampered by limitations in the exposure assessment process. One limitation involves the measured exposure metric itself. Current methods for personal exposure assessment are designed to estimate the aspiration of aerosol into the human body. Since a large proportion of inhaled aerosol is subsequently exhaled, a portion of the aspirated aerosol will not contribute to the dose. This leads to variable exposure misclassification (for heterogenous exposures) and increased uncertainty in health effect associations. Alternatively, a metric for respiratory deposition would provide a more physiologically relevant estimate of risk. To address this challenge, we have developed a method to estimate the deposition of aerosol in the human respiratory tract using a sampler engineered from polyurethane foam. Using a semi-empirical model based on inertial, gravitational, and diffusional particle deposition, a foam was engineered to mimic aerosol total deposition in the human respiratory tract. The sampler is comprised of commercially available foam with fiber diameter = 49.5 microm (equivalent to industry standard 100 PPI foam) of 8 cm thickness operating at a face velocity of 1.3 m s(-1). Additionally, the foam sampler yields a relatively low-pressure drop, independent of aerosol loading, providing uniform particle collection efficiency over time.