LAC - Laboratory of Atmospheric Chemistry
The Laboratory of Atmospheric Chemistry (LAC), established 1 January 2000, is a laboratory of the Energy and Environment Research Division (ENE) at the Paul Scherrer Institute (PSI).
Understanding the processes determining the gas and aerosol chemistry and aerosol physics in the atmosphere in order to determine (1) the impact of energy use on the atmosphere and (2) the impact of pollution on air quality, human health, local weather and climate change.
Our laboratory consists of four interacting groups that operates cutting-edge facilities and instrumentations in the lab and in the field. We run three National facilities, two ambient observatories and an atmospheric chamber facility, that are foreseen to be included in the ACTRIS European research infrastructure. We study the impact of anthropogenic air pollution across environments ranging from cities in Europe and developing countries (e.g. India and China) to pristine areas (e.g. in polar regions and in the free troposphere). We are continuously measuring key climate variables relevant for aerosol properties at the landmark high-alpine Jungfraujoch research site in Switzerland. We simulate the processes occurring in the atmosphere in our smog chamber facility and during experiments at the CLOUD chamber at CERN. Field and laboratory data are interpreted and air pollution sources are quantified with numerical and statistical models. We collaborate with toxicologists, epidemiologists and medical doctors to understand the impact of air pollution on health.
News & Highlights
Forschende haben an 22 Standorten in Europa die Quellen der Aerosolverschmutzung bestimmt.
Launch of the analytical chemistry community gateway.
Find criteria and more information below or on: https://open-research-europe.ec.europa.eu/gateways/analytical-chemistry/about
The CLOUD experiment reveals a new mechanism by which atmospheric particles form. The particles rapidly travel the world, globally impacting cloud formation and climate.
Saharan dust storms played havoc with weather predictions. Invertible neural networks to retrieve aerosol properties from light scattering data may help.