Estimating particulate black carbon concentrations using two offline light absorption methods applied to four types of filter media

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Abstract

Atmospheric particulate black carbon has been linked to adverse health outcomes. Additional black carbon measurements would aid a better understanding of population exposure in epidemiological studies as well as the success, or otherwise, of relevant abatement technologies and policies. Two light absorption measurement methods of particles collected on filters have been applied to four different types of filters to provide estimations of particulate black carbon concentrations. The ratio of transmittance (lnI0/I) to reflectance (lnR0/R) varied by filter type and ranged from close to 0.5 (as expected from simple theory) to 1.35 between the four filter types tested. The relationship between light absorption and black carbon, measured by the thermal EC(TOT) method, was nonlinear and differed between filter type and measurement method. This is particularly relevant to epidemiological studies that use light absorption as an exposure metric. An extensive archive of filters was used to derive loading factors and mass extinction coefficients for each filter type. Particulate black carbon time series were then calculated at locations where such measurements were not previously available. When applied to two roads in London, black carbon concentrations were found to have increased between 2011 and 2013, by 0.3 (CI: −0.1, 0.5) and 0.4 (CI: 0.1, 0.9) μg m−3 year−1, in contrast to the expectation from exhaust abatement policies. New opportunities using archived or bespoke filter collections for studies on the health effects of black carbon and the efficacy of abatement strategies are created.

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Davy, P. M., Tremper, A. H., Nicolosi, E. M. G., Quincey, P., & Fuller, G. W. (2017). Estimating particulate black carbon concentrations using two offline light absorption methods applied to four types of filter media. Atmospheric Environment, 152, 24–33. https://doi.org/10.1016/j.atmosenv.2016.12.010

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