Satellite remote sensing of aerosols using geostationary observations from MSG-SEVIRI

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed metho

Impacts of the new fixed link between Sweden and Denmark on the transport logistics system in Sweden

The dissertation is a study of the impacts of the new fixed link over the Oresund on the Swedish transport logistics system. Sweden is separated from the continent by its peninsula situation. The advent of the Oresund link in the year 2000 is going to be a historic event that represents a major step in the integration of Scandinavia into the EU. For the first time, Sweden will be linked directly by land to the continental Europe. The new fixed link will have various effects in the region, including impacts on the transport logistics related to the carriage of goods from and to Sweden. It would appear that one of the main beneficiaries of the fixed link would be the railway if efforts are made to develop the European railway network. In particular, this will comprise transport over medium and long-distance. Besides rail transport, road transport on short distances is also expected to be the main user of the Oresund link, taking advantage of the 24-hour opening of the bridge. v On long distances to the continent, ferry lines via Trelleborg remain the most advantageous routes for road transport as the crossing time is taken as a rest period for the driver. The main airports in the Oresund region, Kastrup and Sturup airports will benefit from the new fixed link which will connect these airports to the road and rail network on both sides of the Sound

Energy Performances of a Passive Building in Marrakech: Parametric Study

AbstractThis paper deals with the modeling of a villa type house located in the Marrakech (Morocco) suburb. The house is constituted of two floors and was designed to be energy efficient by integrating some passive techniques: overhangs, an Earth-to-Air Heat Exchanger (EAHX), thermal insulation of the roof and external walls. Most of these systems are unusual in Marrakech buildings; thus the objective of this work is to study their effects on the house cooling and heating loads. The modeling of the house is a multi-zone one and it was carried out during one year. The effects of the passive systems on air temperature in the building, as well as on its cooling/heating load, are analyzed through the modeling of 5 cases. The first case is the real house and the others correspond to the lack of one of the system (i.e. the overhang along the south facade in the second floor, thermal insulation of the roof and thermal insulation of external walls), the fifth case correspond to the lack of all the systems (“standard house”). The results show that some of these systems reduce the maximum temperature, while some others act only on the minimum temperature by increasing it. The first systems reduce the cooling load and are very efficient in summer (this is the case, especially, of the thermal insulation of the roof). The other systems reduce the heating load and have a small effect on the cooling load. It should be mentioned that the heating load of the real house is negligible compared to the cooling one. One of the interesting results is that, corresponding to the effect of thermal insulation of external walls. This insulation has a small beneficial effect on the heating load while it increases the cooling load

Holistic Robust Data-Driven Decisions

The design of data-driven formulations for machine learning and decision-making with good out-of-sample performance is a key challenge. The observation that good in-sample performance does not guarantee good out-of-sample performance is generally known as overfitting. Practical overfitting can typically not be attributed to a single cause but instead is caused by several factors all at once. We consider here three overfitting sources: (i) statistical error as a result of working with finite sample data, (ii) data noise which occurs when the data points are measured only with finite precision, and finally (iii) data misspecification in which a small fraction of all data may be wholly corrupted. We argue that although existing data-driven formulations may be robust against one of these three sources in isolation they do not provide holistic protection against all overfitting sources simultaneously. We design a novel data-driven formulation which does guarantee such holistic protection and is furthermore computationally viable. Our distributionally robust optimization formulation can be interpreted as a novel combination of a Kullback-Leibler and Levy-Prokhorov robust optimization formulation which is novel in its own right. However, we show how in the context of classification and regression problems that several popular regularized and robust formulations reduce to a particular case of our proposed novel formulation. Finally, we apply the proposed HR formulation on a portfolio selection problem with real stock data, and analyze its risk/return tradeoff against several benchmarks formulations. Our experiments show that our novel ambiguity set provides a significantly better risk/return trade-off

Existence of Renormalized Solution of Some Elliptic Problems in Orlicz Spaces

In this paper, we study the problem:—div a(x, u, ∆u) — div Φ(u) + g(x; u) = f in the framework of Orlicz spaces. The main contribution of our work is to prove the existence of a renormalized solution without any restriction on the N-function of the Orlicz space.In this paper, we study the problem:—div a(x, u, ∆u) — div Φ(u) + g(x; u) = f in the framework of Orlicz spaces. The main contribution of our work is to prove the existence of a renormalized solution without any restriction on the N-function of the Orlicz space

Evaluation of spot size using volumetric repainting technique on a ProteusPLUS PBS Proton Therapy System

Volumetric repainting is considered as one of the techniques for motion mitigation in proton therapy. Faster layer switching time to deliver a volumetric repainting proton plan is very critical to reduce the overall treatment time. Recently, IBA (proton therapy vendor at the Miami Cancer Institute) has implemented a field regulation – a new feature to reduce the switching time between layers by applying a magnetic field setpoint to specific groups of magnets. In order to investigate the impact of field regulation and volumetric repainting technique on the spot size, several spot maps were generated. The spot sizes were measured at the isocenter and four off-axis points using the Lynx 2D scintillation detector. The average difference in spot size between two delivery sequences ( down vs. up directions) for given energy at all five locations was 0.6±0.5%. The measurement results from the current study demonstrated that the impact of field regulation on the spot size was very minimal, and this was true for both the volumetric and non-volumetric techniques on a ProteusPLUS proton system with a PBS dedicated nozzle