Autocorrelation and variability of indoor air quality measurements

Mapping Occupational Hazards with a Multi-sensor Network in a Heavy-Vehicle Manufacturing Facility

Due to their small size, low-power demands, and customizability, low-cost sensors can be deployed in collections that are spatially distributed in the environment, known as sensor networks. The literature contains examples of such networks in the ambient environment; this article describes the development and deployment of a 40-node multi-hazard network, constructed with low-cost sensors for particulate matter (SHARP GP2Y1010AU0F), carbon monoxide (Alphasense CO-B4), oxidizing gases (Alphasense OX-B421), and noise (developed in-house) in a heavy-vehicle manufacturing facility. Network nodes communicated wirelessly with a central database in order to record hazard measurements at 5-min intervals. Here, we report on the temporal and spatial measurements from the network, precision of network measurements, and accuracy of network measurements with respect to field reference instruments through 8 months of continuous deployment. During typical production periods, 1-h mean hazard levels ± standard deviation across all monitors for particulate matter (PM), carbon monoxide (CO), oxidizing gases (OX), and noise were 0.62 ± 0.2 mg m-3, 7 ± 2 ppm, 155 ± 58 ppb, and 82 ± 1 dBA, respectively. We observed clear diurnal and weekly temporal patterns for all hazards and daily, hazard-specific spatial patterns attributable to general manufacturing processes in the facility. Processes associated with the highest hazard levels were machining and welding (PM and noise), staging (CO), and manual and robotic welding (OX). Network sensors exhibited varying degrees of precision with 95% of measurements among three collocated nodes within 0.21 mg m-3 for PM, 0.4 ppm for CO, 9 ppb for OX, and 1 dBA for noise of each other. The median percent bias with reference to direct-reading instruments was 27%, 11%, 45%, and 1%, for PM, CO, OX, and noise, respectively. This study demonstrates the successful long-term deployment of a multi-hazard sensor network in an industrial manufacturing setting and illustrates the high temporal and spatial resolution of hazard data that sensor and monitor networks are capable of. We show that network-derived hazard measurements offer rich datasets to comprehensively assess occupational hazards. Our network sets the stage for the characterization of occupational exposures on the individual level with wireless sensor networks.

Bioaerosol sampling: sampling mechanisms, bioefficiency and field studies

Investigations into the suspected airborne transmission of pathogens in healthcare environments have posed a challenge to researchers for more than a century. With each pathogen demonstrating a unique response to environmental conditions and the mechanical stresses it experiences, the choice of sampling device is not obvious. Our aim was to review bioaerosol sampling, sampling equipment, and methodology. A comprehensive literature search was performed, using electronic databases to retrieve English language papers on bioaerosol sampling. The review describes the mechanisms of popular bioaerosol sampling devices such as impingers, cyclones, impactors, and filters, explaining both their strengths and weaknesses, and the consequences for microbial bioefficiency. Numerous successful studies are described that point to best practice in bioaerosol sampling, from the use of small personal samplers to monitor workers' pathogen exposure through to large static samplers collecting airborne microbes in various healthcare settings. Of primary importance is the requirement that studies should commence by determining the bioefficiency of the chosen sampler and the pathogen under investigation within laboratory conditions. From such foundations, sampling for bioaerosol material in the complexity of the field holds greater certainty of successful capture of low-concentration airborne pathogens. From the laboratory to use in the field, this review enables the investigator to make informed decisions about the choice of bioaerosol sampler and its application.

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.