Monitor for detecting and assessing exposure to airborne nanoparticles
Source abstract
Abstract
An important safety aspect of the workplace environment concerns the severity of its air pollution with nanoparticles (NP; <100 nm) and ultrafine particles (UFP; <300 nm). Depending on their size and chemical nature, exposure to these particles through inhalation can be hazardous because of their intrinsic ability to deposit in the deep lung regions and the possibility to subsequently pass into the blood stream. Recommended safety measures in the nanomaterials industry are pragmatic, aiming at exposure minimization in general, and advocating continuous control by monitoring both the workplace air pollution level and the personal exposure to airborne NPs. This article describes the design and operation of the Aerasense NP monitor that enables intelligence gathering in particular with respect to airborne particles in the 10–300 nm size range. The NP monitor provides real time information about their number concentration, average size, and surface areas per unit volume of inhaled air that deposit in the various compartments of the respiratory tract. The monitor’s functionality relies on electrical charging of airborne particles and subsequent measurements of the total particle charge concentration under various conditions. Information obtained with the NP monitor in a typical workplace environment has been compared with simultaneously recorded data from a Scanning Mobility Particle Sizer (SMPS) capable of measuring the particle size distribution in the 11–1086 nm size range. When the toxicological properties of the engineered and/or released particles in the workplace are known, personal exposure monitoring allows a risk assessment to be made for a worker during each workday, when the workplace-produced particles can be distinguished from other (ambient) particles.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Air Quality and Health Impacts · Noise Effects and Management · Air Quality Monitoring and Forecasting
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (19)
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