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The urban heat island effect is often associated with large metropolises. However, in the Netherlands even small cities will be affected by the phenomenon in the future (Hove et al., 2011), due to the dispersed or mosaic urbanisation patterns in particularly the southern part of the country: the province of North Brabant. This study analyses the average night time land surface temperature (LST) of 21 North-Brabant urban areas through 22 satellite images retrieved by Modis 11A1 during the 2006 heat wave and uses Landsat 5 Thematic Mapper to map albedo and normalized difference temperature index (NDVI) values. Albedo, NDVI and imperviousness are found to play the most relevant role in the increase of night-time LST. The surface cover cluster analysis of these three parameters reveals that the 12 “urban living environment” categories used in the region of North Brabant can actually be reduced to 7 categories, which simplifies the design guidelines to improve the surface thermal behaviour of the different neighbourhoods thus reducing the Urban Heat Island (UHI) effect in existing medium size cities and future developments adjacent to those cities. Tema. Journal of Land Use, Mobility and Environment, Vol 9, N° 1 (2016): Planning for livable and safe cities: Extreme weather events caused by climate change

The river Rhine is one of Europe’s busiest waterways and is part of the Rhine-Alpine corridor. In 2018 the river experienced a severe low discharge extreme. This impacted the river’s transport capacity for a period of several months, causing shortages of source materials and fuels in regions far in-land. Historically, prolonged droughts of this magnitude are not uncommon. Concerns have been raised, however, that climate change may further increase their frequency and severity. Additionally the increased proportion of larger vessels in the overall fleet composition has made the supply of cargo via the river Rhine more vulnerable to reduced water depths. A better understanding of the risks and effects of sustained low water levels for Inland Waterway Transport network performance is therefore essential to enable sensible mitigation. An integral model that explicitly links the state of the river to supply chain performance at the scale of corridors, however, appears to be not yet available. This paper suggests a novel method to explicitly include the cascading effects of low discharge events (and mitigating measures) in climate risk assessments of waterborne supply chain performance, at system level. It is shown that its implementation can describe cascading effects and climate risks for fleet management and terminal operation.

This study quantifies the uncertainties in the projected changes in potential longshore sediment transport (LST) rates along a non-straight coastline. Four main sources of uncertainty, including the choice of emission scenarios, Global Circulation Model-driven offshore wave datasets (GCM-Ws), LST models, and their non-linear interactions were addressed through two ensemble modelling frameworks. The first ensemble consisted of the offshore wave forcing conditions without any bias correction (i.e., wave parameters extracted from eight datasets of GCM-Ws for baseline period 1979–2005, and future period 2081–2100 under two emission scenarios), a hybrid wave transformation method, and eight LST models (i.e., four bulk formulae, four process-based models). The differentiating factor of the second ensemble was the application of bias correction to the GCM-Ws, using a hindcast dataset as the reference. All ensemble members were weighted according to their performance to reproduce the reference LST patterns for the baseline period. Additionally, the total uncertainty of the LST projections was decomposed into the main sources and their interactions using the ANOVA method. Finally, the robustness of the LST projections was checked. Comparison of the projected changes in LST rates obtained from two ensembles indicated that the bias correction could relatively reduce the ranges of the uncertainty in the LST projections. On the annual scale, the contribution of emission scenarios, GCM-Ws, LST models and non-linear interactions to the total uncertainty was about 10–20, 35–50, 5–15, and 30–35%, respectively. Overall, the weighted means of the ensembles reported a decrease in net annual mean LST rates (less than 10% under RCP 4.5, a 10–20% under RCP 8.5). However, no robust projected changes in LST rates on annual and seasonal scales were found, questioning any ultimate decision being made using the means of the projected changes.

This paper proposes a method for optimally dimensioning the components of a prosumer energy management system that integrates photovoltaic (PV) panels, multiple bidirectional electric vehicle chargers, an inverter, and a battery energy storage charger. Besides optimally dimensioning the components, it also optimizes power management while integrating the frequency containment reserve market and Li-ion battery degradation. The results show that the integration of the frequency containment reserve (FCR) market can increase lifetime cost savings by 36%, compared to optimal power management alone and up to 460% compared to non-optimal power management. Furthermore, the effects of PV and battery energy storage (BES) degradation on reservable capacity are analyzed including the importance of battery second-life value on lifetime net present cost is investigated.