Chemistry of aerosol particles and fog droplets during fall-winter season in the Po Valley

Air quality represents a key issue in the so-called pollution “hot spots”: environments in which anthropogenic sources are concentrated and dispersion of pollutants is limited. One of these environments, the Po Valley, normally experiences exceedances of PM10 and PM2.5 concentration limits, especially in winter when the ventilation of the lower layers of the atmosphere is reduced. This thesis provides a highlight of the chemical properties of particulate matter and fog droplets in the Po Valley during the cold season, when fog occurrence is very frequent. Fog-particles interactions were investigated with the aim to determine their impact on the regional air quality. Size-segregated aerosol samples were collected in Bologna, urban site, and San Pietro Capofiume (SPC), rural site, during two campaigns (November 2011; February 2013) in the frame of Supersito project. The comparison between particles size-distribution and chemical composition in both sites showed the relevant contribution of the regional background and secondary processes in determining the Po Valley aerosol concentration. Occurrence of fog in November 2011 campaign in SPC allowed to investigate the role of fog formation and fog chemistry in the formation, processing and deposition of PM10. Nucleation scavenging was investigated with relation to the size and the chemical composition of particles. We found that PM1 concentration is reduced up to 60% because of fog scavenging. Furthermore, aqueous-phase secondary aerosol formation mechanisms were investigated through time-resolved measurements. In SPC fog samples have been systematically collected and analysed since the nineties; a 20 years long database has been assembled. This thesis reports for the first time the results of this long time series of measurements, showing a decrease of sulphate and nitrate concentration and an increase of pH that reached values close to neutrality. A detailed discussion about the occurred changes in fog water composition over two decades is presented.

Chemical characterization of atmospheric secondary organic aerosol of biogenic and anthropogenic origin

The main objective of this thesis was the chemical characterization of synthetic secondary organic aerosol (SOA) produced from atmospherically relevant anthropogenic and biogenic VOCs during reaction chamber experiments. In parallel, the resulting chemical features of these laboratory-SOA were used to interpret the composition of ambient samples of atmospheric fine particulate matter collected at several sites in Europe, in order to determine the fraction of ambient aerosol organic mass accounted for by biogenic and anthropogenic SOA.

Modelling the effects of nitrogen deposition and carbon dioxide enrichment on forest carbon balance

Atmospheric CO2 concentration ([CO2]) has increased over the last 250 years, mainly due to human activities. Of total anthropogenic emissions, almost 31% has been sequestered by the terrestrial biosphere. A considerable contribution to this sink comes from temperate and boreal forest ecosystems of the northern hemisphere, which contain a large amount of carbon (C) stored as biomass and soil organic matter. Several potential drivers for this forest C sequestration have been proposed, including increasing atmospheric [CO2], temperature, nitrogen (N) deposition and changes in management practices. However, it is not known which of these drivers are most important. The overall aim of this thesis project was to develop a simple ecosystem model which explicitly incorporates our best understanding of the mechanisms by which these drivers affect forest C storage, and to use this model to investigate the sensitivity of the forest ecosystem to these drivers. I firstly developed a version of the Generic Decomposition and Yield (G’DAY) model to explicitly investigate the mechanisms leading to forest C sequestration following N deposition. Specifically, I modified the G’DAY model to include advances in understanding of C allocation, canopy N uptake, and leaf trait relationships. I also incorporated a simple forest management practice subroutine. Secondly, I investigated the effect of CO2 fertilization on forest productivity with relation to the soil N availability feedback. I modified the model to allow it to simulate short-term responses of deciduous forests to environmental drivers, and applied it to data from a large-scale forest Free-Air CO2 Enrichment (FACE) experiment. Finally, I used the model to investigate the combined effects of recent observed changes in atmospheric [CO2], N deposition, and climate on a European forest stand. The model developed in my thesis project was an effective tool for analysis of effects of environmental drivers on forest ecosystem C storage. Key results from model simulations include: (i) N availability has a major role in forest ecosystem C sequestration; (ii) atmospheric N deposition is an important driver of N availability on short and long time-scales; (iii) rising temperature increases C storage by enhancing soil N availability and (iv) increasing [CO2] significantly affects forest growth and C storage only when N availability is not limiting.

Candidate genes affecting fat deposition, carcass composition and meat quality traits in pigs

Pig meat quality is determined by several parameters, such as lipid content, tenderness, water-holding capacity, pH, color and flavor, that affect consumers’ acceptance and technological properties of meat. Carcass quality parameters are important for the production of fresh and dry-cure high-quality products, in particular the fat deposition and the lean cut yield. The identification of genes and markers associated with meat and carcass quality traits is of prime interest, for the possibility of improving the traits by marker-assisted selection (MAS) schemes. Therefore, the aim of this thesis was to investigate seven candidate genes for meat and carcass quality traits in pigs. In particular, we focused on genes belonging to the family of the lipid droplet coat proteins perilipins (PLIN1 and PLIN2) and to the calpain/calpastatin system (CAST, CAPN1, CAPN3, CAPNS1) and on the gene encoding for PPARg-coactivator 1A (PPARGC1A). In general, the candidate genes investigation included the protein localization, the detection of polymorphisms, the association analysis with meat and carcass traits and the analysis of the expression level, in order to assess the involvement of the gene in pork quality. Some of the analyzed genes showed effects on various pork traits that are subject to selection in genetic improvement programs, suggesting a possible involvement of the genes in controlling the traits variability. In particular, significant association results have been obtained for PLIN2, CAST and PPARGC1A genes, that are worthwhile of further validation. The obtained results contribute to a better understanding of biological mechanisms important for pig production as well as for a possible use of pig as animal model for studies regarding obesity in humans.

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.

Application of innovative methods of source apportionment in air contamination assessment

In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.