Search Results (259)

In protracted humanitarian crises, solid waste management (SWM) becomes a major challenge due to limited resources, inadequate infrastructure, and competing response priorities. Waste generated in humanitarian settings typically consist of heterogeneous streams, where plastics, biodegradable fractions, and packaging materials represent the dominant components. Proper management of this waste is essential to reduce health risks and environmental impacts on local communities. Within this framework, sustainable bio-based alternatives and compostable solutions represent promising alternatives. The EU-funded Bio4HUMAN project promotes the integration of innovative bio-based solutions aligned with humanitarian and sustainability goals. An exploratory assessment focused on analyzing waste production, material composition, and handling practices in two case study locations in Sub-Saharan Africa (Democratic Republic of Congo (DRC) and South Sudan (SS)). The results indicate that humanitarian waste cannot be clearly distinguished from household or commercial waste, as streams are typically mixed. Waste composition is dominated by organic matter (43–65%), followed by plastics (15–33%), while other fractions such as paper, glass, metals, and textiles are less significant. Further insights into challenges and opportunities were obtained through a combination of quantitative surveys (n = 29), qualitative interviews with key informants (KIIs) (44) and group discussions sessions (FDG) (9), direct observations, and literature review. Subsequently, a scoping approach was applied to map and classify suitable sustainable solutions into two main categories: bio-based products (BBPs) and organic waste valorization technologies. These were assessed through life cycle assessment (LCA) in accordance with ISO 14040 and 14044, applying SimaPro v.10.2.0.3 software and the Ecoinvent 3.10 database, and compared against fossil-based alternatives. This study compares two case scenarios: a HDPE oil bottle versus PLA alternative (functional unit 6 L), and PE water container versus PLA alternative (functional unit 10 L). For the oil bottle, PLA shows a lower carbon footprint (1.33 kg CO₂-eq) than HDPE (2.37 kg CO₂-eq). In contrast, for the water container, PLA performs worse (2.22 kg CO₂-eq) compared to PE (1.59 kg CO₂-eq), due to higher material demand. The results suggest that benefits are context-dependent and most evident for lightweight products with high leakage risks, particularly when composting infrastructure is accessible. This study advances previous work on humanitarian SWM by integrating field-based waste flow characterization with context-specific screening and life cycle assessment of bio-based alternatives, providing quantitative evidence on the conditions under which these solutions can effectively reduce environmental burdens in protracted crisis settings. Full article

The ongoing Palestinian conflict, particularly the escalation in Gaza since October 2023, has raised pressing concerns regarding human rights and international justice. This study explores how university students in northern Spain perceive the situation in Palestine, analyzing their levels of knowledge, emotional responses, and critical positioning. Using a mixed-method approach based on an online questionnaire and the Grid Elaboration Method, data were gathered from 147 students enrolled in education-related programs. The findings reveal three core themes in students’ representations of the conflict: resistance as a form of national identity, humanitarian suffering of civilians, and structural injustice perpetuated by global power dynamics. Gender and academic background influenced discursive emphasis, with Social Education students showing more politicized perspectives and women focusing more on Palestinian dignity and resistance. These insights underscore the potential of higher education to foster critical thinking, empathy, and engagement with international conflicts, and highlight the role of universities in cultivating a culture of peace and human rights. Full article

Access to clean and safe drinking water for all remains a global challenge, mainly for rural populations and areas affected by natural disasters or humanitarian crises. The traditional water quality treatment technologies can work well in laboratory or controlled settings, but they are usually applied under conditions unavailable in these types of conditions. Traditional water quality treatment methods are limited by established infrastructure, expensive operating costs, energy requirements, and the ability to perform in-field water treatment. To improve the barriers of traditional water quality treatment technologies, recently developed scientific discoveries of nanozymes, a new class of nanomaterials with enzyme-like catalytic activity, have shown the ability to decentralise water purification. Nanozymes provide a mechanism for water treatment that does not require the infrastructure or the cost of traditional water quality treatment methods. Also, nanozymes possess extremely high catalytic activity, chemical stability, are inexpensive, and are suitable for a variety of contaminants. This review gives a systematic overview of the development of suitable nanozyme-based portable water purification systems. It shows their catalytic mechanisms, the class of nanozymes used, and the design characteristics related to their working use, also highlighting the developments that consider the specific needs of rural contexts, provide rapid responses to disaster areas, and offer drinking water with reliable, simple, and sustainable apparatus. Full article

Drought remains a persistent challenge affecting agricultural and pastoral livelihoods, particularly in dryland mixed crop–livestock systems. Water Monitoring and Early Warning Systems (WM-EWS) have increasingly been promoted as tools for delivering climate information services and supporting drought-related decision-making. However, empirical understanding of how users perceive and engage with such systems in pastoral contexts remains limited. This study explores stakeholder perceptions regarding the usefulness and operational relevance of a WM-EWS implemented in the Borana zone of Ethiopia. A mixed-methods approach was employed, combining survey data from 71 purposively selected mixed stakeholders with qualitative insights obtained through focus group discussions and key informant interviews. Findings indicate that respondents widely reported using WM-EWS information for water-related decision-making and perceived the system as useful in supporting drought preparedness and adaptive responses. Participants associated WM-EWS use with perceived changes in areas such as livestock management, access to water-related information, and coordination among stakeholders. Respondents also reported adopting multiple coping strategies, including early livestock sales, strategic herd mobility, and engagement with external support mechanisms. Respondents perceived fewer conflicts over water resources and greater engagement from humanitarian actors following WM-EWS implementation. Overall, the study provides exploratory insights into stakeholder experiences, perceived usefulness, and operational relevance of user-centered WM-EWS in drought-prone pastoral systems. The findings contribute to understanding how pastoral communities engage with climate information services while highlighting the need for future research using objective and longitudinal approaches to assess system effectiveness more rigorously. Full article

This paper investigates the settlement experiences of Hong Kong British National (Overseas) [BN(O)] migrants in the UK, with a particular focus on housing as a central mechanism shaping their wellbeing, security, and integration. Following the introduction of the BN(O) visa route in 2021, this study draws on qualitative interviews with migrants in the North of England to explore how housing mediates conditional settlement under a marketised migration regime. Findings reveal that housing functions as the primary infrastructure of settlement, influencing employment, education, and family life, while access is conditioned by migrants’ capacity to absorb market risks such as advance rent payments and landlord discretion. The study highlights significant intra-group stratification shaped by financial resources, family composition, and transnational support, with family responsibilities intensifying housing precarity and constraining choices. Moreover, a moralised ethos of self-reliance among migrants normalises hidden insecurity and limits formal support-seeking. This research contributes to migration and housing scholarship by demonstrating how ostensibly humanitarian migration pathways reproduce uneven security through housing systems, underscoring the need for policy interventions that address the cumulative effects of housing insecurity on settlement and wellbeing. Full article

The rise in large language models (LLMs) has sparked renewed interest in how firms, particularly multinational aid organizations, can enhance learning related to meta-dynamic capabilities (DCs), such as agility, sensing, and adaptation, in response to disasters and humanitarian crises. A key strategic priority is developing meta-rules that combine general engagement frameworks with locally tailored action plans, grounded in cultural and institutional contexts. LLMs offer potential in supporting this need, but premature deployment risks harmful or misleading outcomes. This underscores the critical importance of collaboration between artificial and human intelligence (AI-HI). While AI brings computational power, it lacks the tacit knowledge—encompassing cultural, contextual, and intuitive understanding—that is essential in high-stakes, unpredictable environments. Our experimental study provides two core insights: (1) AI alone cannot effectively handle tasks requiring tacit knowledge, and (2) AI-HI collaboration thrives when human input guides AI using deep awareness of local social and political dynamics. We contribute to the discourse on dynamic capabilities in multinational contexts during catastrophic situations by offering practical strategies to support successful AI-HI partnerships and a framework for organizations aiming to enhance meta-DCs through responsible, human-centered use of disruptive technologies. Our findings clarify how the international dimensions of these capabilities influence their effectiveness across diverse cultural and institutional environments. Full article

City Information Modelling (CIM) and Urban Digital Twins (UDT) are pivotal for advancing smart urban planning and city management, yet empirical evidence on their real-world implementation is scarce. Following a sequential mixed-methods design, this study addresses this gap through a global investigation analyzing 33 projects across diverse geographic contexts. Findings reveal that these technologies are predominantly applied in 3D visualization (60.6%) and urban planning (48.5%), with significant underutilization in climate adaptation (9.1%) and AI-driven robotics (3.0%). A pronounced physical–social data divide exists, with infrastructure data prioritized over human-centric inputs. Technology stacks converge on GIS, IoT, and BIM. However, an interoperability paradox persists, as internal integration outpaces cross-organizational connectivity. Governance is predominantly public-sector-led, but multi-actor ecosystems are also involved. The study concludes with actionable recommendations to rebalance implementation portfolios, integrate socio-economic data, and advance both technical and institutional interoperability, thereby harnessing CIM and UDT for transformative urban planning and city management. Full article

Social media posts by individuals affected by disasters and their relatives provide a significant source of data for identifying emergencies and needs, assessing the situation, and determining affected areas. These posts often contain not only text but also text embedded within images. Therefore, focusing solely on text data may compromise the integrity of the information and lead to incomplete or limited analyses. In this study, a topic modelling-based clustering approach is proposed that accounts for the complementary nature of text and image text in social media posts, as well as the limitations of manual annotation during disasters. In this context, data pre-processing was performed on text and text extracted from images. Text extracted from images via Optical Character Recognition (OCR) was corrected using the GPT-4.0-mini model. Then, both data types were clustered separately using BERTopic with k-means, and the resulting clusters were integrated. A dictionary-based analysis was conducted to identify humanitarian relief categories and locations within the clusters. The proposed framework was applied to the social media dataset related to the Kahramanmaraş earthquakes, one of the largest disasters in recent times. The findings show that text and image text data complement each other. The resulting clusters are meaningful, with average coherence scores of 0.710 for text and 0.687 for image text. LLM-based post-OCR correction also yielded a 62.81% reduction in average character error rate and a 56.91% decrease in average word error rate compared to the normalized ground truth image text. Furthermore, the proposed approach outperformed both keyword-based filtering with k-means and BERTopic with HDBSCAN. In summary, the results demonstrate that the proposed unsupervised learning approach is effective for extracting humanitarian needs and locations from social media in disaster response. Full article

The growing scale and duration of global displacement driven by complex humanitarian crises pose significant challenges for humanitarian shelter and settlement planning. Refugees and displaced persons often live long-term in settlements and collective accommodation initially intended as temporary, which are frequently characterised by overcrowding, limited privacy, inadequate infrastructure, and uncertain living conditions, heightening psychological distress. Despite the recognition of mental health and psychosocial support (MHPSS) in humanitarian response, the role of the built environment and its impact on MHPSS remains underexplored. This study utilises a systematic-informed review of academic and grey literature to examine how healing architecture can support humanitarian settlement planning, with a focus on the wellbeing of displaced communities. Literature was identified through searches in Web of Science and Google Scholar, alongside selected publications from United Nations agencies and non-governmental organisations, resulting in a total of 34 documents included in the analysis. The paper addresses three research questions: What mental health challenges are most common among displaced populations? What healing architecture strategies are most relevant, and how do they influence mental health? How and under what conditions can healing architecture strategies contribute to humanitarian settlement planning to support wellbeing? Studies were identified through database and repository searches, appraised for quality, and synthesised using thematic analysis. Findings highlight key design strategies, including access to private and communal spaces, connection to nature, and culturally responsive layouts. Although the analysis identified contextual and methodological limitations in humanitarian settlement planning, integrating healing architecture offers practical pathways to enhance wellbeing through participatory and inclusive design. Full article

This paper presents a dynamic multi-period mixed-integer programming model for the Disaster Volunteer Task Assignment Problem (DVTAP) that advances the humanitarian logistics literature through an integrated treatment of features that have previously appeared only in isolation. Unlike prior formulations that assume volunteer surplus or steady-state conditions, our model reflects the acute-phase reality where tasks far exceed available volunteers and new task arrivals diminish over time as the disaster stabilizes. We incorporate makespan as an optimization objective alongside deprivation-weighted response time, skill matching, workload balance, and volunteer reliability. Ideal-nadir normalization ensures that all objective components contribute meaningfully regardless of their native units. The approach proceeds in two stages. First, we formulate and solve a single-period baseline MIP under volunteer surplus using the CBC solver at four scales (10 to 500 tasks). All four instances are solved to proven optimality, achieving 80 to 100% task coverage with skill-matching rates of 76.9 to 99.6%. Second, we develop a rolling-horizon algorithm that decomposes the multi-period problem into sequential epoch-level MIPs with state transitions, non-homogeneous Poisson task arrivals, fatigue accumulation, and task surplus conditions where the initial task-to-volunteer ratio exceeds 3:1. Computational experiments on three dynamic scenarios (up to 559 mean cumulative tasks) demonstrate that the algorithm achieves mean task completion rates of 84.21 ± 1.92% (Large-Dynamic), 93.74 ± 2.07% (Small-Dynamic), and 94.59 ± 2.03% (Medium-Dynamic) (mean ± standard deviation across 30 Monte Carlo replications) within a 15 h planning horizon, with per-epoch skill-matching rates of 11 to 20% (substantially lower than the static baseline due to triage-mode epochs that force all-volunteer assignment regardless of skill fit). The results reveal a clear regime transition: early epochs operate under severe task surplus where triage dominates, while later epochs transition to volunteer surplus where optimization of secondary objectives becomes feasible. Comparison against a skill-aware greedy heuristic confirms that the MIP’s advantage lies in global multi-objective coordination. This research contributes both a validated mathematical framework and a practical algorithmic approach for multi-period volunteer assignment under demand decay, extending prior work by Sperling and Schryenthrough explicit Poisson dynamics, fatigue state modeling, and makespan optimization. Full article

Automated building damage assessment from satellite imagery has become increasingly critical for rapid disaster response and humanitarian relief operations. However, current state-of-the-art deep learning models exhibit significant generalization challenges when deployed to geographically and environmentally diverse regions. This study investigates the nature and extent of geographic bias in building damage detection systems, revealing that model performance degradation occurs primarily from geographic and structural characteristics rather than insufficient training data representation. Through a systematic evaluation of top-performing xView2 competition solutions across 17 disaster locations across multiple climate zones, we found that even state-of-the-art models struggle with generalization under geographic shift, particularly for the minor and major damage classes, and exhibit strong geographic biases toward certain regions. In this work, we explore a six-channel Fusion Augmentation strategy that enriches RGB imagery with auxiliary structural enhancement channels, together with supervised fine-tuning and unsupervised CORAL-based domain adaptation for three unseen regions. The experimental results demonstrate a substantial improvement of 7.1% overall F1 score, with notable gains for intermediate damage categories such as minor and major damage. Domain adaptation experiments on three unseen locations show that combining Fusion Augmentation with supervised fine-tuning yields 40.8% and 60.0% improvements over the minor and major classes, while unsupervised CORAL achieves 24.2% and 39.5% improvements over the minor and major damage classes compared to benchmarks. These findings highlight persistent geographic bias and demonstrate that structural feature enhancement combined with domain adaptation is essential for globally deployable damage assessment systems. Full article

Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping the next generation of humanitarian aid management systems, focusing on algorithmic and operational aspects, matching them to a new architecture for a target-platform, called AidTech. Methods: The methodology follows a systematic literature coverage, identifying cross-disciplinary trends from operations research, computer science and sustainable logistics. We examine the convergence of optimization, artificial intelligence, and blockchain-enabled traceability toward efficient and transparent humanitarian logistics. The employed methods include adaptive scheduling, resource allocation algorithms and privacy–preserving collaboration for meeting special constraints imposed by the humanitarian scope. Results: The findings focus on the architectural perspective of humanitarian supply chains and highlight that modern humanitarian infrastructures will increasingly rely on hybrid optimization methods integrating graph theory, dynamic routing under stochastic demand, multi-criteria decision analysis and distributed ledger technologies. Conclusions: We conclude that these paradigms, when combined under a unified cyber–physical architecture, e.g., AidTech, can substantially improve responsiveness, equity and sustainability in crisis management, further shaping future humanitarian logistics. Full article

Natural disasters are devastating occurrences that have a major influence on the well-being of numerous individuals on a global scale. The primary goal of this study is to facilitate the rapid, transparent, and safe delivery of various aid such as food and clothing to people in disaster areas. For this purpose, a system has been established using blockchain technology in cooperation with institutions and humanitarian organizations. This system is designed to be accountable and reliable; it will supervise all processes from the source of aid materials to their distribution while protecting the personal information of disaster victims. The assistance process is improved using Smart Contracts in order to provide fast, effective, and coordinated assistance. Unlike existing humanitarian frameworks that rely on permissionless networks such as Bitcoin or Ethereum, this study proposes Hyperledger Fabric to ensure beneficiary privacy and eliminate per-transaction fees for end-users, thereby offering a more sustainable economic model for high-frequency aid distribution compared to public blockchains. The proposed system (Chainguard) addresses the ’efficiency gap’ in the current literature JSON Web Token (JWT)-based authentication layer. The results showed that Chainguard achieves a stable throughput of ~180 TPS with an end-to-end latency of less than 1.5 s, outperforming traditional heavy-cryptography models in terms of scalability and resource efficiency during real-time disaster response. Full article

The World Health Organization recommends the use of balanced energy protein (BEP) supplements during pregnancy in settings with a ≥ 20% prevalence of underweight women of reproductive age to reduce the risk of adverse health outcomes. Several countries are implementing BEP supplementation in varied formats. However, the implementation and monitoring of outcomes remain poor across countries. This qualitative study explores the experiences, opportunities, and challenges related to implementing national and sub-national BEP supplementation programs in nine countries (12 countries originally invited) to inform best practices. Methods: Semi-structured interviews were conducted with 15 personnel involved in its implementation in Haiti, India, Malawi, Mexico, Nigeria, Pakistan, Rwanda, Senegal, and Sri Lanka between October 2024 and March 2025. The interviewees in each country were predominantly implementation experts but also government officials involved in the provision of BEP supplementation. The transcripts were analyzed thematically, focusing on acceptability, adoption, appropriateness, cost, feasibility, and sustainability of outcomes. Results: In non-humanitarian settings (five countries), BEP supplementation was commonly integrated into the governmental health system or social protection programs. However, humanitarian contexts (four countries) often relied on partner-led (e.g., UN organizations) implementation. Clear operational protocols, including behavioral change communication strategies, facilitated the implementation. Community-based organization partnerships strengthened adherence; however, implementation costs, stock shortages, and geographic inequities in coverage varied and were limiting factors in scale-up, primarily in humanitarian contexts. Conclusion: In sum, two distinct implementation pathways emerged: government-led models characterized by policy integration, national ownership, and more stable systems, and humanitarian or donor-led models shaped by crisis response, external dependency, and non-committal challenges. Successful implementation of BEP supplements depends on the presence of effective policies, context-adapted design, integration into health systems, consistent funding, and effective monitoring. There is a need for implementation research to generate evidence on best practices when implementing BEP supplementation programs. Full article

Fallujah, by Jonathan Holmes (2007), is one of the archetypal examples of verbatim theatre, which addresses the truths of the Iraq War through dramatised eyewitness accounts and documentation reconstructions. Sketched in the Second Battle of Fallujah, the play reveals moral, political, and epistemological aspects of how modern warfare is presented. This article hinges on the postmodern theory of Jean-François Lyotard—especially the concepts of language games, paralogy, and the differend—to discuss the play Fallujah as a subversion of official grand narratives of the Iraq War. Through the use of testimonial intertextuality, irony and fragmentation, Holmes builds a multidimensional tableau of discourse contradictions in which truth is relative, and legitimacy is constantly deferred. The play turns into a meta-discursive critique of Western power dynamics, challenging the manner in which the knowledge is created, distributed, and twisted in the name of liberation and humanitarianism. Further, the article examines both dramaturgical and aesthetic techniques that lend truthfulness to Holmes’ concept of the verbatim approach as it dislocates the truth in relation to war and victimhood. The results help us comprehend the role of modern theatre in the reconstruction of the cultural memory and morality in the post-war era. The article concludes that Fallujah is a vivid example of postmodern theatrical resistance, an ethical and artistic response to commodity violence and the obliteration of lived suffering. Full article