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AbstractOver the last decade the progress in amorphous and nanocrystalline silicon (nc‐Si) for photovoltaic applications received significant interest in science and technology. Advances in the understanding of these novel materials and their properties are growing rapidly. In order to realise nc‐Si in the solar cell, a thicker intrinsic layer is required. Due to the indirect band gap in the crystallites, the absorption coefficients of nc‐Si are much lower. In this work we have used electrochemical etching techniques to produce silicon nanocrystals of the sizes 3–5 nm. Viable drop cast deposition of Si nanocrystals to increase the thickness without compromising the material properties was investigated by atomic force microscopy, optical microscopy, photoemission spectroscopy and optical absorption methods.

This paper shows how to exploit the degree of freedom represented by the common-mode voltage, which is inherent in three-phase Cascaded H-Bridge (CHB) converters, to minimize the total Root Mean Square (RMS) current value of the distributed dc sources. An optimal common-mode voltage injection law is derived, constituting a Maximum Power Per Ampere (MPPA) modulation strategy with respect to the currents of the dc sources. The potential benefits introduced by the proposed algorithm are analyzed in the context of battery-fed CHB converters and validated experimentally with a three-time-constant Randles model of a battery cell. The MPPA strategy is compared with traditional common-mode voltage injection methods, and battery loss reduction is demonstrated. The obtained battery energy saving is dependent on the converter modulation index and power factor. Experimental tests on a 36-cell full-bridge CHB converter validates the simulation and numerical derivation. To demonstrate the efficacy of the proposed method in practical applications, a 3 MW Energy Storage System (ESS) and a 110 kW Battery Electric Vehicle (BEV) undergoing standard drive cycles are presented as case studies. Compared to traditional modulation strategies, the MPPA strategy reduces the battery losses by up to 10.9% in the ESS and 27.5% in the BEV application.

There are substantial differences in carbon footprints across households. This study applied an environmentally extended multiregional input–output approach to estimate household carbon footprints for 12 different income groups of China’s 30 regions. Subsequently, carbon footprint Gini coefficients were calculated to measure carbon inequality for households across provinces. We found that the top 5% of income earners were responsible for 17% of the national household carbon footprint in 2012, while the bottom half of income earners caused only 25%. Carbon inequality declined with economic growth in China across space and time in two ways: first, carbon footprints showed greater convergence in the wealthier coastal regions than in the poorer inland regions; second, China’s national carbon footprint Gini coefficients declined from 0.44 in 2007 to 0.37 in 2012. We argue that economic growth not only increases income levels but also contributes to an overall reduction in carbon inequality in China.

The societal and economic losses due to compound extremes, i.e., extreme events often result from one extreme state or amplification due to many other contributing mild or extreme states, are manifold higher in magnitude compared to the impacts of those from individual extremes alone. To understand the future impact of compound flood events at different spatio-temporal aggregation levels and climate zones, i.e., mountains, flood plains, and coasts, it is inevitable to examine the mechanisms of compound floods. To this end, this thesis highlights the importance of an integrated process-based physical modelling approach (atmospheric, hydrological and hydrodynamic) for the proper investigation of future flood risk. The research described in this thesis cover several relevant topics related to a complete flood risk chain (from mountains to coasts) and their impact on water resources in regions around the world (i.e., Europe and Asia). First part of this thesis focuses on empirical, univariate and bivariate approaches to understand historical climate trends and associated hazards in data scarce High Mountain Asia (HMA). This study provides a concise overiew of climate related changes across different regions which were difficult to align and compare either due to use of different data or spatio-temporal scales. Analysis reveals while the temperature is consistently increasing at a higher rate than the global warming rate, precipitation changes are not uniform, with substantial temporal and spatial variation in particular for the higher altitudes of HMA. Changes in climatic variables give rise to nonlinear, non-stationary, and non-uniform responses of cryospheric and hydrological variables such as snow, glaciers, soil moisture, and groundwater. Therefore, second part of this thesis investigates the systemic effect of the compound occurrence of extreme precipitation and temperature, at a wide range of spatio-temporal scales, and their impacts on the seasonality and trends in total water availability for HMA using a high-resolution cryospheric-hydrological model. This study shows a shift in the magnitude and peak of water availability, at seasonal time scale, to earlier in the year due to earlier onset of melting. Analysis reveals that the contrasting responses of HMA's rivers are primarily dictated by their hydrological regimes. To understand the risk due to compound floods in coastal regions, the third study of this thesis investigates the possibility of finding near-simultaneous storm surge and extreme river discharge along the Dutch coast using an extended dataset derived from a storm surge model and two hydrological river-discharge models forced with conditions from a high-resolution regional climate model in ensemble mode. This study conceptually shows that a strong storm whose winds set up a storm surge will need time to reach the Rhine headwaters where heavy rainfall will find its way to the river mouth after multiple days of travel time. The fourth and final study of this thesis investigates and quantifies the role of memory components in hydrological and meteorological systems which are responsible to generate extreme discharge, i.e. soil moisture, snow accumulation and the antecedent hydro-climatic conditions. Results show that the meteorological autocorrelation (manifesting itself by the occurrence of clustered precipitation events) has a strong impact on the magnitude of peak discharge. Finally, the study illustrates how hydrological memory from snow accumulation and soil moisture complements the generation of extreme discharges. A new valuable insight on the mechanisms of compound floods and its potential impact on water resources (both for historical and future climate) has been gained with novel modelling approaches. The outcomes generated from this thesis might contribute to support climate change adaptation policy planning and outreach programs in these climate change hotspots, i.e., the mountains and deltas.

The Ganges-Brahmaputra-Meghna (GBM) delta is one of the world's largest deltas. It is currently experiencing high rates of relative sea-level rise of about 5 mm/year, reflecting anthropogenic climate change and land subsidence. This is expected to accelerate further through the 21st Century, so there are concerns that the GBM delta will be progressively submerged. In this context, a core question is: can sedimentation on the delta surface maintain its elevation relative to sea level? This research seeks to answer this question by applying a two-dimensional flow and morphological model which is capable of handling dynamic interactions between the river and floodplain systems and simulating floodplain sedimentation under different flow-sediment regimes and anthropogenic interventions. We find that across a range of flood frequencies and adaptation scenarios (including the natural polder-free state), the retained volume of sediment varies between 22% and 50% of the corresponding sediment input. This translates to average rates of sedimentation on the delta surface of 5.5 mm/yr to 7.5 mm/yr. Hence, under present conditions, sedimentation associated with quasi-natural conditions can exceed current rates of relative sea-level rise and potentially create new land mass. These findings highlight that encouraging quasi-natural conditions through the widespread application of active sediment management measures has the potential to promote more sustainable outcomes for the GBM delta. Practical measures to promote include tidal river management, and appropriate combinations of cross-dams, bandal-like structures, and dredging.

Liberalisation of the British household electricity market, in which previously monopolised regional markets were exposed to large-scale entry, is used as a natural experiment on oligopolistic nonlinear pricing. Each oligopolist offered a single two-part electricity tariff, but inconsistent with current theory, the two-part tariffs were heterogeneous in ways that cannot be attributed to explanations such as asymmetric costs or variations in brand loyalty. Instead, the evidence suggests that firms deliberately differentiated their tariff structures, resulting in market segmentation according to consumers’ usage.