Characterisation of atmospheric single particles in industrial and regional background environments using aerosol time of flight mass spectrometry

The composition of atmospheric particles is an important factor in determining their impact on climate and health. In this study, an aerosol time-of-flight mass spectrometer (ATOFMS) was used to measure the chemical composition of ambient single particles at two contrasting locations – an industrial site in Dunkirk, France and a regional background site in Corsica. The ATOFMS data were combined with meteorological information and other particle measurements to determine the various sources of the particles observed at the sites. The particle classes detected in Dunkirk included carbonaceous species from fossil fuel combustion and biomass burning, metal-containing types from local industries and seasalt. Highest particle number concentrations and mass concentrations of PM2.5, black carbon, organics, nitrate, ammonium and several metallic species (Fe, Mn, Pb, Zn) were found during periods heavily influenced by local industry. Particles from a ferromanganese alloy manufacturing facility were identified by comparing ambient ATOFMS data with single particle mass spectra from industrial chimney filters and ores. Particles from a steelworks were identified based on comparison of the ambient data with previous studies. Based on these comparisons, the steelworks was identified as the dominant emitter of Fe-rich particles, while the ferromanganese alloy facility emitted Mn-rich particles. In Corsica, regional transport of carbonaceous particles from biomass burning and fossil fuel combustion was identified as the major source of particles in the Mediterranean background aerosol. Throughout the campaign the site was influenced by air masses altering the composition of particles detected. During North Atlantic air masses the site was heavily influenced by fresh sea salt. Regional stagnation was the most common type of air mass regime throughout the campaign and resulted in the accumulation of carbonaceous particles during certain periods. Mass concentrations were estimated for ATOFMS particle classes, and good agreement was found between the major carbonaceous classes and other quantitative measurements. Overall the results of this work serve to highlight the excellent ability of the ATOFMS technique in providing source-specific composition and mixing state information on atmospheric particles at high time resolution.

Transport energy demand: techno-economic modelling and scenarios for Irish climate policy

The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy

Real time analysis of atmospheric single particles in urban environments using aerosol time of flight mass spectrometry

In order to determine the size-resolved chemical composition of single particles in real-time an ATOFMS was deployed at urban background sites in Paris and Barcelona during the MEGAPOLI and SAPUSS monitoring campaigns respectively. The particle types detected during MEGAPOLI included several carbonaceous species, metal-containing types and sea-salt. Elemental carbon particle types were highly abundant, with 86% due to fossil fuel combustion and 14% attributed to biomass burning. Furthermore, 79% of the EC was apportioned to local emissions and 21% to continental transport. The carbonaceous particle types were compared with quantitative measurements from other instruments, and while direct correlations using particle counts were poor, scaling of the ATOFMS counts greatly improved the relationship. During SAPUSS carbonaceous species, sea-salt, dust, vegetative debris and various metal-containing particle types were identified. Throughout the campaign the site was influenced by air masses altering the composition of particles detected. During North African air masses the city was heavily influenced by Saharan dust. A regional stagnation was also observed leading to a large increase in carbonaceous particle counts. While the ATOFMS provides a list of particle types present during the measurement campaigns, the data presented is not directly quantitative. The quantitative response of the ATOFMS to metals was examined by comparing the ion signals within particle mass spectra and to hourly mass concentrations of; Na, K, Ca, Ti, V, Cr, Mn, Fe, Zn and Pb. The ATOFMS was found to have varying correlations with these metals depending on sampling issues such as matrix effects. The strongest correlations were observed for Al, Fe, Zn, Mn and Pb. Overall the results of this work highlight the excellent ability of the ATOFMS in providing composition and mixing state information on atmospheric particles at high time resolution. However they also show its limitations in delivering quantitative information directly.