Ocean-Atmosphere Interactions: Linking Oceanic Biological Activity to Marine Aerosol Physico-Chemical and Cloud Properties

In this work, in-situ measurements of aerosol chemical composition, particle number size distribution, cloud-relevant properties and ground-based cloud observations were combined with high-resolution satellite sea surface chlorophyll-a concentration and air mass back-trajectory data to investigate the impact of the marine biota on aerosol physico-chemical and cloud properties. Studies were performed over the North-Eastern Atlantic Ocean, the central Mediterranean Sea, and the Arctic Ocean, by deploying both multi-year datasets and short-time scale observations. All the data were chosen to be representative of the marine atmosphere, reducing to a minimum any anthropogenic input. A relationship between the patterns of marine biological activity and the time evolution of marine aerosol properties was observed, under a variety of aspects, from chemical composition to number concentration and size distribution, up to the most cloud‐relevant properties. At short-time scales (1-2 months), the aerosol properties tend to respond to biological activity variations with a delay of about one to three weeks. This delay should be considered in model applications that make use of Chlorophyll-a to predict marine aerosol properties at high temporal resolution. The impact of oceanic biological activity on the microphysical properties of marine stratiform clouds is also evidenced by our analysis, over the Eastern North Atlantic Ocean. Such clouds tend to have a higher number of smaller cloud droplets in periods of high biological activity with respect to quiescent periods. This confirms the possibility of feedback interactions within the biota-aerosol-cloud climate system. Achieving a better characterization of the time and space relationships linking oceanic biological activity to marine aerosol composition and properties may significantly impact our future capability of predicting the chemical composition of the marine atmosphere, potentially contributing to reducing the uncertainty of future climate predictions, through a better understanding of the natural climate system.

Advanced spectroscopic techniques and chemometric analysis for atmospheric organic aerosol characterization and source apportionment

Atmospheric aerosol particles directly impact air quality and participate in controlling the climate system. Organic Aerosol (OA) in general accounts for a large fraction (10–90%) of the global submicron (PM1) particulate mass. Chemometric methods for source identification are used in many disciplines, but methods relying on the analysis of NMR datasets are rarely used in atmospheric sciences. This thesis provides an original application of NMR-based chemometric methods to atmospheric OA source apportionment. The method was tested on chemical composition databases obtained from samples collected at different environments in Europe, hence exploring the impact of a great diversity of natural and anthropogenic sources. We focused on sources of water-soluble OA (WSOA), for which NMR analysis provides substantial advantages compared to alternative methods. Different factor analysis techniques are applied independently to NMR datasets from nine field campaigns of the project EUCAARI and allowed the identification of recurrent source contributions to WSOA in European background troposphere: 1) Marine SOA; 2) Aliphatic amines from ground sources (agricultural activities, etc.); 3) Biomass burning POA; 4) Biogenic SOA from terpene oxidation; 5) “Aged” SOAs, including humic-like substances (HULIS); 6) Other factors possibly including contributions from Primary Biological Aerosol Particles, and products of cooking activities. Biomass burning POA accounted for more than 50% of WSOC in winter months. Aged SOA associated with HULIS was predominant (> 75%) during the spring-summer, suggesting that secondary sources and transboundary transport become more important in spring and summer. Complex aerosol measurements carried out, involving several foreign research groups, provided the opportunity to compare source apportionment results obtained by NMR analysis with those provided by more widespread Aerodyne aerosol mass spectrometers (AMS) techniques that now provided categorization schemes of OA which are becoming a standard for atmospheric chemists. Results emerging from this thesis partly confirm AMS classification and partly challenge it.