Optical sensing of VOCs and viral biomolecules via IR spectroscopy for air pollution monitoring

In the current era the climate changes, environmental risks, human impact and the intensive depletion of natural resources are highly debated and urgent topics, requiring an immediate intervention. Atmospheric pollution has a large and dangerous role, as one of the major, hard problems that our world has to face. Emissions from intensive anthropogenic, industrial and productive activities cause the release of artificial and dangerous pollutants in the atmosphere, constituting a concrete danger for nature and human health safety and leading to severe consequences in global warming and climate changes. In order to efficiently fight air pollution, strategically, strong and direct actions should be implemented. Strict regulations should be introduced concerning the drastic reduction of pollutants emission in the shortest time as possible and a more efficient monitoring has to be performed in order to ensure human health safety and environment prevention. The instantaneous, highly sensitive and specific tracking of air status is necessary for immediately understanding which is the problem, how to intervene for contrasting it and to verify whether preventive measures are efficiently working and are enough to guarantee human and nature safety. Mainly focusing on the context of health prevention in indoor and outdoor urbanized places, from working places, to means of transport, schools, hospitals, offices, factories and so on, the status of atmosphere worths a major attention. Toxic emissions should constantly be under control and human exposure to dangerous chemical compounds should be regimented and monitored. Not only, the scientific community studies are recently converging to the possibility of a strong connection between the climate change, the air pollution and the pandemic risk [1]. SARS-CoV-2 pandemic could have been a clear example, heavily burdening the world from 2020 to 2023 and founding somehow our society unprepared. The resulting worldwide crisis has been a clear demonstration of the dangerous power of a pandemic and of the weak organizational and technological capacity of humans to face it. Closed and crowded places are also the main ones where biological pollution due to pathogens achieves a very high and worrying level, and where a pandemic can find a fertile ground to easily spread. The possibility of a large-scale monitoring of pathogens constitutes a fundamental step for prevention and control, in order to guarantee global health security. It would be an urgent and necessary issue especially for hospitals, but also for every kind of indoor and/or generally crowded place. For example, still taking experience of recent SARS-CoV-2 pandemic, air and water vapor is an optimal medium for viruses to move from a host to another one, constituting what it is generally called bioaerosol. Prevention measures implemented during the 2020-2023 pandemic, such as the imposition of social distancing and the use of personal protective equipment, have not been enough to face the fast spreading of COVID19 virus and crowded, indoor spaces were the main risk for human infection. It has been clear that a technological development in the field of airborne pathogen sensing was necessary to track and face the pandemic rising. Both if we are aiming to chemical emissions tracking and subsequent reduction and if we are focusing on bioaerosol sensing, the capacity to monitor atmosphere status is essential to guarantee safety, health and prevention and to move a preliminary step to solve environmental pollution issue. Moved by these motivations, considering both pollutions due to chemical compounds produced by production chains and industrial and humans activities and the biological risk due to airborne pathogens pollution, this PhD thesis work is the result of a project aiming to introduce a technological advancement in the field of (bio)sensing, in order to face environmental and health emergencies. It falls in the context of sustainability for contributing to the building of a green society, bringing innovations in the field of health, occupational and environmental safety. Specifically, the goal of this project is to develop a (bio)sensing strategy both for VOCs and pathogens, with a particular focus on viruses and on SARS-CoV-2, based on vibrational Infrared (IR) spectroscopy. The combination of this technique with a biofuncionalized sensor platform employing Metal-Organic Frameworks (MOFs) biocomposites and with Machine Learning (ML) algorithms is explored and deepened with the final goal to provide an efficient, specific and rapid tool for monitoring air-quality status. The following thesis reports the main results obtained in the three-years long PhD project. In the first section, the employed approach for VOCs detection based on IR spectroscopy is presented, aiming to overcome current sensors limitations and provide an innovative system for gas detection. The development and optimization of the IR experimental setup for gaseous VOCs measurements is described and results about nine different chemical compounds are shown, from their characterization, to the building of their individual calibration curves and the analysis of random VOCs mixtures. A Machine Learning algorithm for gases automatic recognition is reported, constituting a first step toward the automation and engineering of the whole sensor system, with the final goal to allow an effective technological transfer from laboratories to a real urbanized indoor environment. Indeed, the employment of a predictive algorithm for VOCs monitoring could provide an easy-to-use and real time tool which can be directly used by no expertise personelle to keep under control and track gaseous pollutants spreading in a closed space. In the second part of this thesis, the airborne pathogen issue is faced and the IR spectroscopy approach is presented. Starting from the pathogen analysis, research focuses on SARS-CoV-2 virus and its variants. In particular, Spike protein is considered as biomarker. Besides the biosensing goal of the project, taking advantage of spectroscopy, a structural analysis of these viral proteins is performed in order to investigate and shed light on their conformation and physico-chemical properties. First research focuses on the characterization and structural inspection of individual protein domains, from the simpler RBD to S1 and S2 units, up to the overall Spike protein. The second research provided a comparative study of S1 proteins from three different SARS-CoV-2 variants, namely α, γ and o, through spectroscopic and computational tools. The aim is to verify the possibility to detect and discriminate even very similar viral proteins, differing only for few number of mutations, and to search for structural variations induced by mutations. Once the advantages and the possibility to exploit vibrational spectroscopy for airborne viruses detection is established, in the third and final part of the thesis, first results are shown about the design and development of a sustainable biosensor platform. Exploiting the technology of Metal-organic frameworks biocomposites synthesis, a promising biofunctionalization strategy is designed. Preliminary tests are reported, paving the way to the future implementation of a green and sustainable sensor for chemical and biological atmospheric pollution monitoring.