https://repos.hcu-hamburg.de:443/handle/hcu/13 2026-10-08T00:39:05Z 2026-10-08T00:39:05Z vom Baur, Jeanette https://repos.hcu-hamburg.de:443/handle/hcu/1302 2026-10-03T00:08:56Z 2026-10-02T12:26:01Z

Title: Processed dataset on demolition cases in Germany: building use, lifespan and stated circumstances surrounding demolition Authors: vom Baur, Jeanette Abstract: This dataset contains processed and systematically categorised data on documented building demolition cases in Germany derived from the crowd-sourced platform Abriss-Atlas Deutschland. It consists of a structured research dataset compiled from publicly documented demolition cases and further processed for analytical purposes by the author as part of a doctoral research project investigating decision-making between the (re)use and demolition of existing buildings in Germany. The dataset includes information on building uses, lifespan and stated circumstances surrounding the documented demolition events. Categories were developed by the author and assigned to the cases for the analysis of site-related objectives, building-related considerations and external contextual conditions. The dataset combines information reproduced from the entries on the platform Abriss-Atlas Deutschland with variables further specified, calculated or categorised by the author.; Der Datensatz enthält aufbereitete und systematisch kategorisierte Informationen zu dokumentierten Gebäudeabrissen in Deutschland auf Grundlage der Crowd-Sourcing-Plattform Abriss-Atlas Deutschland. Er wurde im Rahmen eines Promotionsprojekts erstellt, das Entscheidungsprozesse zwischen (Weiter-)Nutzung und Abriss von Bestandsgebäuden untersucht. Enthalten sind Angaben zu Gebäudenutzungen, Lebensdauern und dokumentierten Umständen rund um die Abrissfällen. Für die Analyse wurden Kategorien zu grundstücksbezogenen Zielsetzungen, gebäudespezifische Begründungen und angegebene externe Rahmenbedingungen entwickelt und den einzelnen Fällen zugeordnet. Der Datensatz verbindet aus dem Abriss-Atlas übernommene Informationen mit Variablen, die von der Autorin weiter spezifiziert, berechnet oder kategorisiert wurden.

2026-10-02T12:26:01Z Alexander, Nick Tannenbaum, Milva Noennig, Jörg Rainer https://repos.hcu-hamburg.de:443/handle/hcu/1309 2026-10-02T00:06:04Z 2026-10-01T14:08:02Z

Title: Operational Decision Support for Evacuating Nursing Home Residents: A Hamburg Benchmark and Metaheuristic Comparison Under a 5-Minute Time Budget Authors: Alexander, Nick; Tannenbaum, Milva; Noennig, Jörg Rainer Abstract: Evacuating mobility-impaired nursing home residents during urban emergencies requires routing and scheduling heterogeneous vehicles under minute-level deadlines. We introduce the Nursing Home Evacuation Vehicle Routing Problem (NH-Evac-VRP) with open-ended multi-trip shuttling, split pickups, load-dependent service times, and shelter capacities; solutions must be produced within a hard 300 s single-thread budget. We release the Hamburg-NH-Evac benchmark with two expert-specified scenarios: (i) an unexploded-ordnance exclusion-zone evacuation in Altona-Altstadt (479 evacuees, one shelter), (ii) a storm-surge evacuation in Wilhelmsburg (510 evacuees, three shelters), plus (iii) a synthetic stress test (1,348 evacuees, five shelters). Instances use real facility data and asymmetric road-network travel times. Across five scenario-fleet configurations, we compare a constructive dispatcher with a Genetic Algorithm, Memetic Algorithm, and Adaptive Large Neighborhood Search, minimizing demand-weighted average waiting time and makespan with a shelter-overfill penalty. No method dominates: ALNS attains the best makespan in two configurations; in the heterogeneous Flood-Augmented case this advantage is driven by capacity-maximizing "sweeper" tours. MA is best in three configurations by favoring rapid shuttle cycles, outperforming ALNS by 27 min in the synthetic mass-transit case. We also provide a web-based decision support system for scenario configuration, optimization, and schedule visualization.

2026-10-01T14:08:02Z Salaymeh, Abdulraheem Holler, Stefan Peters, Irene https://repos.hcu-hamburg.de:443/handle/hcu/1308 2026-10-02T00:04:26Z 2026-10-01T13:30:49Z

Title: Advanced spatio-temporal source–demand matching for practical waste heat utilization in district heating Authors: Salaymeh, Abdulraheem; Holler, Stefan; Peters, Irene Abstract: Waste heat is widely recognized as a key lever for advancing climate neutrality in urban heating systems. While recent policy regulations have significantly improved the transparency of waste heat potentials, the gap between reported theoretical potentials and their practical usability remains insufficiently explored. This study develops a novel residual-aware, guided source–demand allocation approach, leveraging officially reported, technically detailed waste heat source information and high-resolution building typology data to reveal key insights into spatial and technical utilization potentials and limitations. The results also derive key distributional and operational source characteristics, combined with spatial and typological building patterns, considering three refurbishment scenarios. The proposed methodology provides a transparent and policy-relevant tool for translating reported waste heat potentials into actionable planning insights. The results indicate that the utilizable share of the reported waste heat potential is reduced to approximately 35 % due to techno-spatial constraints, decreasing further to approximately 24 % when temporal source–demand coincidence is additionally considered. Depending on building refurbishment progress, the number of potentially supplied buildings ranges from 1.8 to 5.7 million. Overall, these findings demonstrate that coordinated spatio-temporal planning, combined with efficiency measures, is essential to unlock the significant, yet primarily spatially constrained, waste heat potential.

2026-10-01T13:30:49Z Shirmohammadi, Mahdieh Mafi-Gholami, Davood Pirasteh, Saied Youssefi, Fahimeh Shen, Jie Li, Weilian Li, Jonathan https://repos.hcu-hamburg.de:443/handle/hcu/1307 2026-10-02T00:02:29Z 2026-10-01T13:21:17Z

Title: Assessing climatic change impacts on mangrove structural dynamics on the northern coasts of the Persian Gulf Authors: Shirmohammadi, Mahdieh; Mafi-Gholami, Davood; Pirasteh, Saied; Youssefi, Fahimeh; Shen, Jie; Li, Weilian; Li, Jonathan Abstract: Monitoring long-term trends in structural changes within mangrove ecosystems is essential for understanding their response to climate change and devising effective adaptation strategies in coastal regions. This study examines changes in mangrove patchiness within the Hara Biosphere Reserve (HBR) along the northern coasts of the Persian Gulf (PG) over a 31-year period (1986-2017), focusing on variations in rainfall patterns and drought occurrences. Employing a 35-year time series of monthly Standardized Precipitation Index (SPI) values alongside satellite imagery analysis, trends in both the number of patches (NP) and the Largest Patch Index (LPI) were assessed at the mangrove stand level. The analysis reveals a significant correlation between structural changes in mangroves and drought events. Pre-1998, characterized by wetter conditions, witnessed a decrease in both NP and LPI, indicating patch expansion and habitat extension. Conversely, post-1998, during drought periods, both indices increased, indicating habitat degradation due to heightened drought intensity. Pre-1998 structural changes in the HBR signify habitat expansion, with increased patch extent and core areas reflecting enhanced structural integrity. However, post-1998, a concerning trend of habitat degradation emerged, with increased NP and LPI attributed to intensified droughts. These findings highlight a transitional period marked by favourable conditions for mangrove growth followed by habitat degradation linked to increased drought intensity. This underscores the vulnerability of mangrove ecosystems to climate change impacts, particularly exacerbated droughts, necessitating urgent efforts for conservation and management to preserve biodiversity and ecosystem services in coastal regions.

2026-10-01T13:21:17Z