Measuring, modelling and mitigating particulate matter in indoor environments

Lowther, Scott (2022) Measuring, modelling and mitigating particulate matter in indoor environments. PhD thesis, UNSPECIFIED.

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Abstract

With modern populations spending on average greater than 90% of their time indoors, a large proportion of total exposure to air pollution occurs within indoor environments. Exposure to air pollution is linked to numerous health effects and mortality, with indoor air quality estimated to be the ninth-largest risk to public health. One of the main components of indoor air quality is particulate matter (PM), the sum of all solids and liquids suspended within the air. PM includes dust, pollen and combustion products. PM is linked to mortality from respiratory and cardiovascular diseases, with the smallest sized particles believed to be the most significant to health. This thesis sits at the nexus between measurement, modelling, and mitigation of indoor PM. It (a) outlines the utility of different PM metrics and sensors, and the challenges facing PM measurement; (b) characterises the efficacy of HEPA filtering technology in both the laboratory and the real world and (c) outlines the development and deployment of an effective integrated air quality monitor. Together this provides a holistic contribution to managing PM in indoor environments. PM measurement uses three key metrics, Pmass, Pnum and Psize. Pmass is a robust, low-cost measurement, and is easy to compare and benchmark against other Pmass measurements. Pnum, the number of suspended particles in air, is suggested to be more important in a health context, as it is disproportionately weighted by fine and ultrafine particles, which are thought to have a greater impact on health. In the future, metrics that better link PM to health effects, such as surface area, particle length concentrations or compositional measurements, are likely to become more important, as better measurement technologies are developed. Particulate mass is measured using gravimetric methods, photometers and beta attenuation methods and is suited to compliance monitoring and trend analysis, as measurements are easily compared. Particle number is measured using condensation particle counters, optical particle counters and diffusion chargers, and is suited to source characterisation, trend analysis and ultrafine particle investigations. Particle size distribution measurements can be made by a scanning mobility particle sizer or fast mobility particle sizer, and are typically limited to research applications. High-efficiency particulate air (HEPA) type purifiers are effective at removing “real-world” PM from air. Although ultrafine particles are removed effectively, particles between 200-300nm are removed least effectively, and this is noteworthy as particles of this size can penetrate buildings effectively, remain airborne for extended periods and are especially important in a health context. HEPA purifiers are effective in the real world, but a single air purifier is insufficient to purify an entire residence, so it should be placed where residents spend the most time. Air change will also reduce air purifier efficiency when ambient levels of PM exceed those indoors. With low-cost sensors becoming increasingly accurate and available, measurements of air quality are likely to be increasingly available, with individuals being better able to understand their exposure. With this, it seems likely that future “smart homes” will contain “internet of things” indoor air quality sensors, which can give recommendations and make interventions (activating ventilation and purification), all in real-time. As measurements of the properties of PM become more diverse and well established, epidemiologists will be better equipped to understand the relationship between PM properties (mass, size, composition, surface area) and health. This will allow for better regulation of PM, to improve health as the correct properties of PM can be regulated.