A solution to difficult atmospheric pollution measurements

Air monitoring

A solution to difficult atmospheric pollution measurements

30 Jun, 2020

Published over 6 years ago. See the latest and most current information on Air monitoring.

Atmospheric Particulate Matter (PM) or aerosol plays a key role in atmospheric pollution as particles cause visibility reduction, act as clouds condensation nuclei, affect global climate change and are responsible for adverse health effects.  Carbonaceous Aerosol (CA), typically emitted by incomplete combustion of fossil fuels related to traffic, industrial processes and domestic heating, is one of the main fractions of PM especially in urban environments and it is very important from the climate change point of view too, since Elemental Carbon (EC), which, depending on the technique adopted to reveal it, can also be called Black Carbon (BC), is the primary responsible of light absorption and of the direct radiative effect of aerosol on climate. Nevertheless, the measurement of CA composition, though prescribed by national and European regulations, is at the moment a “work in progress” and no methodology that is both of simple use and sufficiently robust seems to be available. Creating state of the art the measurement of light absorbing aerosols is still a challenging field of expertise, even though filter-based on-line techniques (e.g. the aethalometer; the particle soot absorption photometer; the multi angle absorption photometer, among others) are widespread, it is widely recognised that they are affected by measurement and sampling techniques which must be accurately managed by skilled personnel. 

With this in mind, Dado Lab have created a methodology, using their Giano PMx sequential sampler, for measuring the concentration of black carbon that adopts many of the advantages of commercially available instruments, in particular the possibility of obtaining a "real time" measurement by means of non-destructive techniques, and that can at the same time overcome some of their limits by exploiting different physical principles and allowing its integration into a sequential sampler.

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