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The establishment of PM_TEN (Physical Methods and Technologies for Environmental Needs) has been developed as part of the spin-off project of the University of Genoa. 

PM_TEN offers a connection between the world of academic research and the business market, from one side  proposing applications of results of research, in particular the activity developed in the Environmental Physics Laboratory; and from the other side, being itself a driving force for new progresses  of the methods developed in the academic context.


PM_TEN could supply advisory services and environmental analysis focusing on meteorological, weather, sea and air quality assessments, environmental impacts studies, designing and implementation of atmospheric monitoring campaigns and compositional analysis of atmospheric particulate. 

Thanks to its marked innovation attitude, it could develop specific methodologies for atmospheric pollution assessment, mathematical models describing complex processes and software implementing them. Moreover, PM_TEN designs and develops innovative instruments and components for air quality analysis.

In this context, recently a sequential PMx sampler has been developed (according to EN12341:2014), filing a patent application (Giano BC1 project). 

Among its competences, the technical assistance to companies concerning the whole process to prepare and manage European financed project proposals (Horizon Europe, Interreg, LIFE, etc...) can be counted, offering support in problem solving and project building also through Lego Serious Play workshops design. 

Recently, thanks to two regional funds (POR ERDF 2014-2020) devoted to complex R&D projects, PM_TEN has developed a Sea Situational Awareness system, called SINDBAD, in partnership with On Air S.r.l. and Xedum S.r.l, able to supply integrated sea and weather services such as navigation support, risk and comfort assessment in the Ligurian Sea and soon for Mediterranean Sea, for pleasure navigation. In 2020, PM_TEN, On Air and Xedum have founded the Sindbad Consortium with commercial distribution aims to develop new field applications (fishery, aquaculture, etc...)  In addition, PM_TEN has strong scientific relationships with universities and research centres, university spin-off, public authorities and many companies.

It is a member of the consortium TICASS, managing body of the Research and Innovation Hub for Energy, Environment and Sustainable Development, and of the consortium TECNOMAR LIGURIA, managing the ?Distretto Ligure Tecnologie Marine? (DLTM).

Descrizione Brevetti

GIANO-BC1 is a new instrument for sampling the airborne particulate matter (PM) while monitoring the black carbon (BC) atmospheric concentration.

The concentration of PM and BC are usually measured by separate instruments with possible systematics differences even in the collecting inlets.

The new equipment is based on a low-volume sequential PM sampler, fully compliant with the EU-CEN and US-EPA regulatory standards, with a built-in optical BC monitor. The BC concentration is continuously measured during the sampling in the PM accumulated on the filter while the PM concentration can be obtained off-line by a standard gravimetric analysis.

The optical set-up, upstream the collecting filter, is composed by a single wavelength light source (lambda = 635 nm) and a photodiode, placed in way to receive the light backscattered by the filter surface at a fixed angle.

The mechanical arrangement does not introduce any perturbation to the PM sampling. Thanks to anoriginal calibration curve, the sample absorbance is deduced from the output signal of the photodiode. Finally, the BC concentration is obtained through the Mass Absorption Coefficient (MAC).

After the sampling and the PM gravimetric determination, the same filter can be sent to other compositional analyses.

Thermo-optical quantification of the Elemental and Organic Carbon (EC and OC) in the filter sample can thus be exploited to tune the MAC value to the PM composition of a particular site.

GIANO BC1 is a patented technology (PM_TEN S.R.L. - Dadolab S.R.L. Patent nr 102019000006685).