Plenary Speakers

Markku Kulmala

University of Helsinki, Institute of Atmospheric and Earth System Research / Physics, Helsinki, Finland

Academician, Academy Prof. Markku Kulmala directs the Institute for Atmospheric and Earth System Research (INAR) /Physics, and has served as a professor at the University of Helsinki since 1996. Kulmala also acts as coordinator for the Centre of Excellence, appointed by the Academy of Finland first time in 2002 and Digital Belt and Road Program International Center of Excellence at University of Helsinki. Previously he has directed two Nordic Center of Excellence, appointed by Nordforsk (BACCI and CRAICC)). CRAICC is the largest joint Nordic research and innovation initiative to date, aiming to strengthen research and innovation regarding climate change issues in the Nordic and high-latitude Regions.

Prof. Kulmala together with Prof. Hari is the primary inventor of the SMEAR concept. According to the ISI Web of Knowledge, M. Kulmala has been in the top 10 in the Citation Rankings in Geosciences (since 2009). His H-factor is 104. Prof. Kulmala has received several international awards such as the Smoluchovski Award (1997), the International Aerosol Fellow Award (2004), the Wilhelm Bjerkenes medals (2007), Fuchs Memorial Award (2010), Litke Gold Medal of Russian Geographical Society (2015). the honorary title of Academician of Science (Finland and China), Wihuri International Prize 2017, Distinguished Visiting Fellow (IIASA), and World Academy of Sciences fellow.

Atmospheric New Particle Formation: from Molecular Clustering to Global Climate and Air Quality

Atmospheric new particle formation: from molecular clustering to global climate and air quality

The production of molecular clusters and their growth to larger sizes, is a world-wide phenomenon, with a significant contribution to aerosol particle number load and indirect radiative effects as well as urban air pollution. Understanding the very initial steps of atmospheric aerosol formation requires detailed knowledge of interlinked physics and chemistry in sub 3 nm size range.

There is always more or less intensive clustering in the atmosphere but only some fraction of those clusters are able to growth to 3-4 nm and further to cloud condensation nuclei and haze particle sizes. However, NPF is a major aerosol source affecting significantly to global aerosol and CCN load as well as global climate and regional/local air quality.

In the presentation I will focus on:

Environmental grand challenges
- Climate change
- Air quality
Continuous, comprehensive observations, SMEAR stations
COBACC (COntinental Biosphere-Aerosol-Cloud-Climate) feedback loop
Gas-to-Particle conversion / New particle formation (NPF)
The contribution of NPF on haze formation
Global and regional aerosol load – climate and air quality effects

E-mail: markku.kulmala@helsinki.fi

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Maria E Messing

Leading the aerosol nanoparticle group at the division of Solid State Physics at Lund University, Sweden

Maria E Messing is currently leading the aerosol nanoparticle group at the division of Solid State Physics at Lund University, Sweden, where she specializes on generation and characterization of nanomaterials. The main focus of her research group is development and advanced characterization of designed nanoparticles by aerosol methods, primarily spark ablation. The emphasis is on production of metal, semiconductor and alloy particles for different applications and Marias favorite characterization tool is the electron microscope.

Maria obtained her Master in Engineering Nanoscience in 2007 and her PhD in Physics in 2011, both from Lund University where she now holds a position as associate professor in Materials Physics. She is, since 2015, one of two coordinators of the material science research within NanoLund, which is one of the research excellence areas of Lund University with more than 250 affiliated researchers. Additionally, Maria is responsible for the popular scientific outreach activities towards the general public organized by NanoLund, and a member of the Swedish standards institute (SiS) working group on nanotechnology.

Designing Engineered Nanoparticles: From Sparks to Magnetic, Catalytic and Optoelectronic Materials

Smart nanomaterials with designed properties based on nanoparticles have the potential to revolutionize applications in magnetics, catalysis and optoelectronics. But implementing nanoparticles’ potential for such applications requires realizing and understanding nanoparticles with controllable size, morphology, crystal structure and chemical composition on a large scale, at low costs and in a safe and environmentally friendly way.

Spark ablation is a method with high potential to fulfill the above declared requirements, especially for the production of pure metal and metal alloy particles. In this talk I aim to demonstrate some of the possibilities with aerosol-based nanotechnology, focusing mainly on spark ablation. I will show how spark ablation can be used to produce nanoparticles with fully controlled and tailored size, morphology and chemical composition. I will then show examples of the possible use of these particles in magnetic, catalytic and optoelectronic applications.

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Ulla Vogel

National Research Centre for the Working Environment, Copenhagen, Denmark

Ulla Vogel is professor in Chemical Working Environment at the National Research Centre for the Working Environment (NFA) and adjunct professor in Nanosafety at the Technical University of Denmark. She is head of Danish Centre for Nanosafety and has worked with the toxicology of inhaled (nano)particles for 20 years with focus on cancer, cardiovascular disease and reprotoxicity.

The Nanosafety research group at NFA is past and present partner in more than 20 EU projects related to nanosafety. Ulla Vogel is a European Registered Toxicologist and acts as advisor to the Working Environment Authority, the Environment Protection Agency and the Ministry of Health.

Health effects of Inhaled Nanomaterials

Most nanoparticles are more hazardous (by mass) by inhalation compared to larger particles with the same chemical composition. This is especially true for nanoparticles with low solubility and low toxicity. Carbon nanotubes constitute a group of highly toxic nanomaterials when inhaled and other high-aspect-ratio nanomaterials may potentially have similar toxicity. Inhalation of nanomaterials has been shown to cause inflammation, acute phase response, fibrosis and tumors, thus linking inhalation of nanomaterials to risk of cardiovascular disease and cancer. Based on animal studies, NIOSH (National Institute of Occupational Safety and Health in the USA) suggested occupational exposure limits of 0.001 mg/ for carbon nanotubes and 0.3 mg/m3 for nanosized titanium dioxide.

In conclusion, inhalation of nanomaterials can be linked to risk of cancer and cardiovascular disease. Accordingly, occupational exposure to nanomaterials should be carefully assessed.

Email: ubv@nrcwe.dk

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Thorsten Hoffmann

Professor of Analytical Chemistry at the Johannes Gutenberg-University of Mainz, Germany

Thorsten Hoffmann is Professor of Analytical Chemistry at the Johannes Gutenberg-University of Mainz, Germany, since 2003. Before he had a stand-in Professorship at the University of Leipzig and was coordinator of the research areas ‘Analytical Methods in the Life Sciences’ and ‘Atmospheric Trace Constituents’ at the Leibniz-Institut für Analytische Wissenschaften – ISAS in Dortmund. 1994/95 he hold a postdoc position at the California Institute of Technology (Caltech, Pasadena, USA) in the group of John H. Seinfeld.

His main research activities are the design and development of tailored methods to chemically characterize environmental matrixes. The motivation is a better understanding of biosphere-atmosphere interactions, e.g. by the investigation of the sources, formation pathways and chemical transformation of secondary organic aerosol particles, or the development of trace analytical techniques to investigate climate archives (ice cores, speleothems). Most of the analytical research is focussed on organic trace analysis in combination with mass spectrometry (LC/MS, high resolution mass spectrometry), however, with emphasis on the development of real-time methods for atmospheric aerosol characterization (aerosol mass spectrometry).

Chemistry of Secondary Organic Aerosols

The knowledge of the chemical composition of secondary organic aerosol (SOA) is one essential key to understand the origin and fate of SOA in the atmosphere. In contrast to many inorganic aerosol constituents, the organic aerosol fraction undergoes a chemical evolution, starting from the very early steps of new particle formation and continuing by chemical aging during transport. However, the chemical pathways and mechanisms from the very first condensing/nucleating molecules to the final SOA composition are still insufficiently understood and object of current research. For several reasons especially chemical reactions leading to higher molecular weight compounds (MW) are of interest (i.e. highly oxidized, highly functionalized or increased MW organics due to oligomerization or accretion reactions). The motivation for these studies is their very low vapor pressure and therefore their influence on the formation and the properties of atmospheric aerosols, e.g. gas/particle partitioning of SOA, the phase state of organic aerosols and especially the still intensively debated question about the role of organic compounds in atmospheric new particle formation. However, also brown carbon (BrC), i.e. the fraction of organic material in atmospheric particulates with a strong wavelength dependent absorption in the VIS/UV region, can be formed by chemical reactions of SOA components, e.g. by the formation of nitrogen heterocycles. Beside the discussion of the current state of understanding of the chemistry of atmospheric SOA, the contribution will also introduce recently developed analytical methodologies for SOA characterization, especially techniques based on online (e.g. CIMS) and offline mass spectrometry (high resolution MS) and their application in field and laboratory studies.

David Topping

Senior lecturer at the University of Manchester, United Kingdom

I completed my PhD in 2005 on ’Modelling the hygroscopic properties of atmospheric aerosol particles’ at the University of Manchester Institute of Science and Technology (UMIST) after finishing a degree in Physics at the same institute. Following this I became a fellow of the UK National Centre for Atmospheric Science (NCAS) before taking on the role of a senior research fellow part funded by the School of Earth and Environmental Science (SEES)/Centre for Atmospheric Science (CAS) at the University of Manchester where I am now a senior lecturer.

My research focuses primarily on monitoring and predicting the evolving characteristics of aerosol particles, and their impact, through computational models. My initial research interests focused on building computational models at the single particle scale. These included multicomponent/multiphase models designed to predict hygroscopic properties and act as a benchmark for experimental studies. Following this I have developed and applied a range of model frameworks from automated box-models through to parameterizations of aerosol processes used in regional and global models. From an experimental perspective, this has included managing and collaborating on a range of laboratory studies designed to increase model fidelity through provision of fundamental property data.

Driven by both the complexity of aerosol and the need for supporting reproducibility, I now develop and coordinate open source informatics and model frameworks, including the UManSysProp suite designed to automated predictions of molecular properties deemed important for prediction aerosol evolution. Most recently my research focuses on evaluating the efficacy of emerging data science driven methodologies in tackling topical questions in aerosol research. This includes evaluating, for example, methods for predicting and unraveling complex spectral signatures of sampled aerosol particles. Most recently I became a fellow of the Alan Turing Data Science Institute, the UK’s national institute for data science and artificial intelligence in the UK. Throughout this fellowship I am continuing research into evaluating the use of machine learning in tackling ongoing challenges in aerosol research, including determining the role of process complexity and assess impacts on health.

Machine Learning in Aerosol Science: Something Old, Something New

Machine learning is pervading most areas of research, promising the potential to deliver new insights and solutions to topical questions relevant to science and society. Aerosol science is no different and, as a highly multidisciplinary area of research, delivers a wide range of problems to which machine learning might be applied. Indeed a recent report by the UK aerosol society notes that ‘Aerosol science is core to a broad range of disciplines extending from drug delivery to the lungs to disease transmission, combustion and energy generation, materials processing, environmental science, and the delivery of agricultural and consumer products’. This naturally provides a range of challenges when it comes to technology adaption, not least from a training and development perspective. One might argue each element of aerosol research has distinctly different drivers when it comes to such adaption and this should be managed in a siloed way. However, in some ways, the excitement and widespread use of machine learning brings its own momentum in whatever discipline it is applied. Some consider wide-scale adoption of machine learning to reflect a form of ‘solutionism’, whilst others are demonstrating a quantifiable benefit. In this talk, I will attempt to generate a debate on such issues by providing examples of adoption across aerosol science. These include, but are not limited to: new approaches for extracting information from aerosol instrumentation; methods for evaluating impacts on human health; methods for predicting fundamental properties; and techniques for reducing computational cost in process models. As already noted, aerosol science is naturally multidisciplinary and machine learning might offer a vehicle for efficient knowledge exchange if we appreciate the key factors that will dictate sustainability and wide-scale use.

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