Diese Dissertation präsentiert Modelle zur Lösung von Verhandlungsproblemen mit diskreten Strukturen. Hauptgrundlage der Betrachtung ist dabei die Erweiterung und Anwendung von Theorien der kooperativen Spieltheorie. Insbesondere der Shapley-Wert spielt eine wichtige Rolle. Als erste Problemklasse werden kooperative Spiele präsentiert, bei denen einige Spiele feste Auszahlungen erhalten. Als zweite Problemklasse werden kooperative Spiele untersucht, deren Lösungen ausschließlich ganzzahlig sein dürfen.

I investigate the links between mercury use, release, deposition, and population exposure in Tampa Bay, with the focus of identifying levers for reducing population mercury exposures. To achieve this, I investigated the trends in mercury use and release by products and processes in the Tampa Bay area using a Material Flow Analysis. Analysis of USEPA National Emissions Inventory data over time (1999 - 2008) identified relevant air source emission categories, and explored and compared state and regional trends in mercury emissions. To understand source contributions to wet deposited mercury in the Tampa Bay area, I analyzed trends in mercury deposition data from the National Atmospheric Deposition Program, Mercury Deposition Network, and the 2001 Bay Regional Atmospheric Chemistry Experiment. I also collected wet deposition samples for mercury and trace metals in the Tampa Bay area during a 6-month campaign at a site at the University of South Florida (USF) campus. Samples were analyzed using Cold Vapor Atomic Fluorescence Spectrometry (CVAFS) for mercury, and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for trace metals analysis. Concentration data were analyzed for source contributions using HYSPLIT back-trajectory meteorology-based modeling to assess source locations, and the Positive Matrix Factorization (PMF) statistical receptor model to apportion the deposition data by source type. To explore the factors influencing fish consumption behaviors of the local angler population, I analyzed population surveys collected previously from fisher-folks along the Hillsborough River, in Hillsborough County, Florida. Results from the mercury inventory indicate that mercury releases from industrial sources and dental facilities were the most important sources of mercury to the Tampa Bay area. Furthermore, the solid-waste pool was the most important direct sink in the domain, with air emissions an important indirect sink. Emissions inventory data indicated that coal-fired power plants were the largest contributors of mercury emissions in the Tampa Bay area. Medical and municipal waste incineration also accounted for significant fractions of total mercury releases to the domain. Emissions from sources in Hillsborough County accounted for a significant portion of mercury emissions in the region and state. Measurement data indicated that event mercury concentration was only very weakly correlated with event precipitation depth, with both studies showing agreement with this phenomenon. Back-trajectory simulations reveal that high mercury concentration events were often from air masses with recent trajectories over Florida land (6 and 24 hr), and with previous high precipitation depth events over the trajectory in the long term (72 hr). The statistical PMF results indicate the importance of coal burning power plant emissions, medical and municipal waste incineration, and agrochemicals on mercury in wet deposition in the Tampa Bay area. Changes were observed between the 2001 and 2012 data, including greater mercury concentrations in 2012, and the removal of medical waste incineration as a mercury source in the 2012 model results. Together with local emissions inventory data, these results suggest that sources local to the Tampa Bay area and in Florida likely contribute substantially to mercury deposition in the region. Finally, population survey data suggests that mercury exposure risks are poorly understood by the fishing population in Hillsborough County. Taken together, these results suggest that policies targeting mercury emissions control, particurlarly for coal-fired power plants and municipal waste processing, and fish consumption education may be instrumental to the protection of susceptible populations.

The Particulate Matter Source Apportionment Technology (PSAT) is used together with PMCAMx, a regional chemical transport model, to estimate how local emissions and pollutant transport affect primary and secondary particulate matter concentration levels in European megacities such as Paris, London and Po Valley. The case of Paris megacity was investigated in detail. During the summer and the winter period examined, only 13% of the PM2.5 is due to local Paris emissions, with 36% due to mid range (within 500 km from the center of the Paris) sources and 51% resulting from long range transport (more than 500 km from the center of the Paris). The local emissions contribution to elemental carbon (EC) is significant, with almost 60% of the EC originating from local sources during both summer and winter. Approximately 50% of the fresh primary organic aerosol (POA) originated from local sources and another 45% from areas 100-500 km from the receptor region during summer. Regional sources dominated the secondary PM components. More than 70% of the sulfate originated from SO2 emitted more than 500 km away from the center of the Paris. Also more than 45% of secondary organic aerosol (SOA) was due to the oxidation of VOC precursors that were emitted 100-500 km from the center of the Paris. Long range sources are more important during winter because the photochemical activity is lower. PSAT results for contributions of local and regional sources were also compared with observation-based estimates from field campaigns that took place during the MEGAPOLI project. PSAT predictions are in general consistent with these estimates OA and sulfate but PSAT predicts lower transported EC for both seasons. / Ο καταμεριστικός αλγόριθμος ατμοσφαιρικών σωματιδίων (PSAT, Particulate Matter Source Apportionment Technology) χρησιμοποιείται σε συνδυασμό με το τρισδιάστατο μοντέλο χημικής μεταφοράς PMCAMx με σκοπό να εκτιμήσει κατά πόσο οι τοπικές εκπομπές και η μεταφορά της ρύπανσης επηρεάζουν τα πρωτογενή και τα δευτερογενή επίπεδα σωματιδιακών συγκεντρώσεων σε Ευρωπαϊκές μεγαλουπόλεις όπως το Παρίσι, το Λονδίνο και η κοιλάδα του ποταμού Πάδου στη βόρεια Ιταλία (Po Valley). Η περίπτωση του Παρισιού μελετήθηκε λεπτομερώς. Κατά τη διάρκεια του καλοκαιριού και του χειμώνα που εξετάστηκε, μόνο το 13% των PΜ2.5 σωματιδίων προέρχονται από τοπικές πηγές, 36% προέρχεται από ενδιάμεσες πηγές (μεταξύ 500 km από το κέντρο του Παρισιού) και 51% από απομακρυσμένες περιοχές (σε αποστάσεις μεγαλύτερες των 500 km από το κέντρο του Παρισιού). Η συνεισφορά των τοπικών πηγών στο στοιχειακό άνθρακα είναι σημαντική, 60% περίπου του στοιχειακού άνθρακα προέρχεται από τοπικές πηγές κατά τη διάρκεια τόσο του καλοκαιριού όσο και του χειμώνα. Σχεδόν 50% των φρέσκων πρωτογενών οργανικών σωματιδίων (POA) προέρχονται από τοπικές πηγές και 45% από περιοχές 100-500 km από των αποδέκτη κατά τη διάρκεια του καλοκαιριού. Οι συνεισφορά από απομακρυσμένες περιοχές κυριαρχεί στα δευτερογενή σωματίδια. Περισσότερο από 70% των θεϊκών σωματιδίων προέρχεται από διοξείδιο του θείου το οποίο εκπέμπεται από αποστάσεις μεγαλύτερες των 500 km από το κέντρο του Παρισιού. Επίσης περισσότερο από το 45% των δευτερογενών οργανικών σωματιδίων οφείλεται στην οξείδωση των πτητικών οργανικών ενώσεων (VOCs) που εκπέμπονται από 100 έως 500 km μακριά από το κέντρο του Παρισιού. Οι απομακρυσμένες περιοχές είναι πιο σημαντικές κατά τη διάρκεια του χειμώνα λόγω της ελάχιστης φωτοχημείας. Τα αποτελέσματα που προέκυψαν από τον αλγόριθμο PSAT για τις συνεισφορές των τοπικών όσο και των απομακρυσμένων περιοχών επίσης συγκρίνονται με μετρήσεις πεδίου από πειραματικές διατάξεις στο πλαίσιο του διεθνούς προγράμματος MEGAPOLI. Ο αλγόριθμος PSAT προβλέπει γενικά ικανοποιητικά τις συνεισφορές σε σχέση με αυτές που υπολογίστηκαν από τις μετρήσεις πεδίου.

Formulary apportionment is an intensively debated mechanism for allocating tax base within multinational groups. Systems under which the formula is identical in all jurisdictions and systems under which jurisdictions can determine the weights on the formula factors individually can be observed. The latter systems produce uncertainty about the overall tax-liable share of the future group tax base. Counter-intuitively, I identify scenarios under which increased uncertainty leads to higher expected future group income. My results provide helpful insights for firms and policy makers debating the specific design of a formulary apportionment system. (author's abstract) / Series: WU International Taxation Research Paper Series

The subject matter of the thesis is a comparative analysis of the possibilities of tax competition in the USA and in the European Union. It aims to compare the extent and form of the tax competition within these systems. The thesis consists of five parts. At the beginning, the term tax competition is examined and the possibility of a distinction between fair and unfair tax practices is explored. In the next part the analysis of the US tax system with a focus on competition in the area of direct and indirect taxation is carried out. The third part provides similarly structured analysis of the tax competition in the EU. The fourth part presents the evaluation and the comparison of the tax competition in both systems. The final part concludes with certain normative recommendations for the future of the EU tax system which are made with respect to their applicability for current deliberation of the reform of the taxation in the European Union. The performed analysis yielded interesting results. Contrary to the expectations, it was determined that the tax competition in the US was more intense than in the EU and the tax practices used by some US states included at least the same level of unfairness as those used by some member states in the EU.

Based on the concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in 144 road dust samples collected from 36 sites across 4 seasons from 2016 to 2017 in Beijing, this study systematically analyzed the levels and main sources of health risks in terms of their temporal and spatial variations. A combination of receptor models (positive matrix factorization and multilinear engine-2), human health risk assessment models, and Monte Carlo simulations were used to apportion the seasonal variation of the health risks associated with these heavy metals. While non-carcinogenic risks were generally acceptable, Cr and Ni induced cautionary carcinogenic risks (CR) to children (confidence levels was approximately 80% and 95%, respectively). Additionally, fuel combustion posed cautionary CR to children in all seasons, while the level of CR from other sources varied, depending on the seasons. Heavy metal concentrations were the most influential variables for uncertainties, followed by ingestion rate and skin adherence factor. The values and spatial patterns of health risks were influenced by the spatial pattern of risks from each source.

Understanding the effect of human-induced pollution on the environment is an important precursor to promoting public health and environmental stability. One aspect of understanding pollution is understanding pollution sources. Various methods have been used and developed to understand pollution sources and the amount of pollution those sources emit. Multivariate receptor modeling seeks to estimate pollution source profiles and pollution emissions from concentrations of pollutants such as particulate matter (PM) in the air. Previous approaches to multivariate receptor modeling make the following two key assumptions: (1) PM measurements are independent and (2) source profiles are constant through time. Notwithstanding these assumptions, the existence of temporal correlation among PM measurements and time-varying source profiles is commonly accepted. In this thesis an approach to multivariate receptor modeling is developed in which the temporal structure of PM measurements is accounted for by modeling source profiles as a time-dependent Dirichlet process. The Dirichlet process (DP) pollution model developed herein is evaluated using several simulated data sets. In the presence of time-varying source profiles, the DP model more accurately estimates source profiles and source contributions than other multivariate receptor model approaches. Additionally, when source profiles are constant through time, the DP model outperforms other pollution receptor models by more accurately estimating source profiles and source contributions.

During the latter part of the 20th century, a transition away from coal as a major energy source in developed countries was accompanied by a notable decrease in air pollution-related deaths in those countries. Currently the same phenomenon is being observed in developing nations like China and India. However, many areas that do still rely on coal for their energy production or industrial needs also reflect a gap in research on the effects of those specific processes on local populations. Located in Nepal at the foot of the Himalayan Plateau, Kathmandu represents one such location. The local economy of Kathmandu and the surrounding area relies heavily on the production of bricks using coal-fired kilns, which produce large amounts of particulate matter. This particulate matter contains a characteristic mix of metals. This unique fingerprint can be used to identify and track kiln emissions in ambient samples. We collected hourly samples of ambient metal concentrations over a period of three months at the start of 2019. We then used these data to perform positive matrix factorization (PMF) to identify several factors contributing to the ambient air pollution of the sampled area, each representing a source type. The PMF output included the chemical ‘fingerprint’ of each factor as well as hourly variation of each factor. We were able to isolate the fraction of PM2.5 contributed by coal and estimate the health effects attributable to this fraction using a modified risk ratio of 1.05 to reflect the higher toxicity of coal emissions. We found that the current estimates of health impacts in Nepal underestimate the true impact of coal by 416 deaths per year.

Ambient and indoor air pollution is a major cause of premature mortality, and has been associated with more than three million preventative deaths per year worldwide. Most of these health impacts are from the effects from fine particulate matter. It is suspected that PM2.5 health effects vary by composition, which depends on the mixture of pollutants emitted by sources. This has led to efforts to estimate relationships between sources of PM2.5 and health effects. The health effects of PM2.5 may be preferentially dependent on specific species; however, recent work has suggested that health impacts may actually be caused by the net effect of the mixture of pollutants which make up PM2.5. Recently, there have been efforts to use source impacts from source apportionment (SA) studies as a proxy for these multipollutant effects. Source impacts can be quantified using both receptor and chemical transport models (RMs and CTMs), and have both advantages and limitations for their use in health studies. In this work, a technique is developed that reconciles differences between source apportionment (SA) models by ensemble-averaging source impacts results from several SA models. This method uses a two-step process to calculate the ensemble average. An initial ensemble average is used calculate new estimates of uncertainties for the individual SA methods that are used in the ensemble. Next, an updated ensemble average is calculated using the SA method uncertainties as weights. Finally, uncertainties of the ensemble average are calculated using propagation of errors that includes covariance terms. The ensemble technique is extended to include a Bayesian formulation of weights used in ensemble-averaging source impacts. In a Bayesian approach, probabilistic distributions of the parameters of interest are estimated using prior distributions, along with information from observed data. Ensemble averaging results in updated estimates of source impacts with lower uncertainties than individual SA methods. Overall uncertainties for ensemble-averaged source impacts were ~45 - 74%. The Bayesian approach also captures the expected seasonal variation of biomass burning and secondary impacts. Sensitivity analysis found that using non-informative prior weighting performed better than using weighting based on method-derived uncertainties. The Bayesian-based source impacts for biomass burning correlate better with observed levoglucosan (R2=0.66) and water soluble potassium (R2=0.63) than source impacts estimated using more traditional methods, and more closely agreed with observed total mass. Power spectra of the time series of biomass burning source impacts suggest that profiles/factors associated with this source have the greatest variability across methods and locations. A secondary focus of this work is to examine the impacts of biomass burning. First a field campaign was undertaken to measure emissions from prescribed fires. An emissions factor of 14±17 g PM2.5/kg fuel burned was determined. Water soluble organic carbon (WSOC) was highly correlated with potassium (K) (R2=.93) and levoglucosan (R2=0.98). Results using a biomass burning source profile derived from this work further indicate that source apportionment is sensitive to levels of potassium in biomass burning source profiles, underscoring the importance of quantifying local biomass burning source profiles. Second, the sensitivity of ambient PM2.5 to various fire and meteorological parameters in was examined using the method of principle components regression (PCR) to estimate sensitivity of PM2.5 to fire data and, observed and forecast meteorological parameters. PM2.5 showed significant sensitivity to PB, with a unit-based sensitivity of 3.2±1 µg m-3 PM2.5 per 1000 acres burned. PM2.5 had a negative sensitivity to dispersive parameters such as wind speed.

Im Zuge der Diskussion einer Harmonisierung der Ertragsbesteuerung innerhalb der Europäischen Union wird bereits seit geraumer Zeit die Einführung einer gemeinsamen konsolidierten Körperschaftsteuerbemessungsgrundlage (GKKB/CCCTB) von den Mitgliedsstaaten der Europäischen Union in Erwägung gezogen. Bereits im Jahr 2001 wurde die Möglichkeit einer grenzüberschreitenden Besteue-rung europaweit tätiger Konzerne von der Europäischen Kommission erwähnt. In den darauf folgenden Jahren wurde die Ausgestaltung einer G(K)KB sowohl auf politischer Ebene als auch in der Literatur fortwährend weiterentwickelt. Eine Reform der Unternehmensbesteuerung ruft regelmäßig Änderungen des Steueraufkommens in den betroffenen Nationalstaaten hervor und führt häufig zu einer Veränderung der Kosten zur Befolgung steuerlicher Gewinndeklarationspflichten. Ferner können Steuerreformen zu Verhaltensreaktionen der Steuerpflichtigen an die geänderten steuerlichen Rahmenbedingungen führen. Beispielsweise kann das Investitionsverhalten oder die Finanzierungsstrategie beeinflusst werden. Vor diesem Hintergrund wird im Rahmen des ersten Beitrags untersucht, welche Verhaltensreaktionen auf Seiten der Steuerpflichtigen in Bezug auf die Wahl des Besteuerungsregimes, das Investitionsverhalten und Steuerplanungsaktivitäten bei Einführung einer optionalen GKKB zu erwarten wären. Ziel des zweiten Beitrags ist eine Ermittlung möglicher Aufkommenskonsequenzen, die sich bei der Einführung einer gemeinsamen Körperschaftsteuerbemessungsgrundlage (GKB/CCTB) oder gemeinsamen Unternehmenssteuerbemessungsgrundlage (GUB) für den deutschen Staatshaushalt ergeben würden. Neben der Ermittlung des Gesamteffekts wird zusätzlich die Bedeutung der Änderung einzelner steuerlicher Gewinnermittlungsvorschriften (zum Beispiel Abschreibungsvorschriften) auf die Gesamtänderung des Steueraufkommens untersucht. Darüber hinaus wird analy-siert, in welchem Umfang die Gewinnermittlungsvorschriften der GKKB im Vergleich zum gegenwärtigen deutschen Steuerrecht Veränderungen der steuerlichen Befolgungskosten hervorrufen. Gegenstand des dritten Beitrags ist eine Auseinandersetzung mit der weniger in der Literatur, sondern vielmehr der allgemeinen Diskussion anzutreffenden Kritik an der Nutzung ökonomischer Experimente zur Untersuchung von Fragestellungen mit Bezug zur Unternehmensbesteuerung. Die Kritik beruht darauf, dass die Ergebnisse ökonomischer Experimente aufgrund fehlender externer Validität nicht auf reales Verhalten übertragen werden könnten. Der Mangel an externer Validität wird damit begründet, dass ökonomische Experimente häufig mit Studierenden durchgeführt werden und diese nicht mit den relevanten steuerlichen Vorschriften vertraut sind. Vor diesem Hintergrund ist das Ziel des dritten Beitrags darin zu sehen, einen me-thodischen Beitrag zu leisten, geeignete Probandengruppen sowie effiziente experi-mentelle Design zur Untersuchung von Fragestellungen mit einem ertragsteuerlichen Fokus zu identifizieren.