High-quality, temporally consistent training samples are the cornerstone of accurate long-term urban Land Use/Land Cover (LULC) mapping. However, traditional sample generation relies heavily on labor-intensive manual interpretation and often lacks reproducibility. To address this, we developed PRTS-AI (Primary Regulated Time-series Sampling), an open-source system that integrates OpenStreetMap (OSM) data extraction, Large Language Model (LLM)-driven semantic classification, and LandTrendr-based temporal filtering into an automated workflow. By leveraging generative AI (e.g., DeepSeek/ChatGPT/Gemini) to interpret polygon attributes and using POI-based consistency checks, the system significantly reduces manual workload while ensuring semantic accuracy.

The PRTS-AI system integrates multi-source spatial and temporal data into a streamlined workflow, including:

(1) extraction of OpenStreetMap (OSM) features for user-defined study areas;

(2) semantic classification of polygon features using large language models;

(3) detection and filtering of change pixels using the LandTrendr time-series algorithm;

(4) recommendation of city-specific sampling parameters based on a six-dimensional urban typology framework.

This system enables reproducible multi-temporal sample generation, spatial heterogeneity validation, and fine-scale classification support across diverse urban settings. Furthermore, this system can operate in parallel with the usual land cover sample selection and subsequent classification processes.

We applied PRTS-AI to map the urban evolution of diverse cities in Liaoning and Shandong provinces, China, from 2000 to 2020. The framework achieved an overall mapping accuracy of ~80%, with residential categories reaching 90%. Beyond mapping, we utilized the fine-grained Local Climate Zone (LCZ) metrics generated by the system to investigate the transferability of samples. Through Principal Component Analysis (PCA) of residential morphologies, we quantitatively identified that cities cluster into distinct typologies driven by macro-factors (e.g., coastal vs. resource-based industrial cities) rather than administrative hierarchies. These findings challenge the assumption of universal sample transferability, suggesting that sample migration is most effective within specific urban typologies. Consequently, PRTS-AI incorporates a typology-based parameter recommendation module to guide city-specific sampling. This study presents a scalable, AI-empowered solution for urban mapping and offers new insights into the spatiotemporal heterogeneity of urban forms.

However, limited sample transferability may still be achieved between cities with similar characteristics, based on a preliminary six-dimensional classification framework.

PRTS-AI provides a lightweight, reproducible, and extensible solution for urban LULC research, supporting both academic investigations and practical urban planning applications.

How to cite: Tian, T., Yu, L., Chen, B., and Gong, P.: From Generative Sampling to Urban Typology: A PRTS-AI Supported Framework for Multi-Decadal Urban LULC Mapping and Cross-City Transferability Analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13942, https://doi.org/10.5194/egusphere-egu26-13942, 2026.

Sea Surface Temperature (SST), due to its influence on air-sea interactions, is a critical input into weather models. While physics-based ocean models are continually improving to better represent SST in weather models, data-driven methods offer a promising alternative. In this work, we present an implementation of nonlinear operator inference on a satellite-based SST field (10 km spatial resolution, 1 day temporal resolution) in the northern Indian Ocean, which is known to significantly impact the Indian monsoon. For the prediction of SST, a reduced-order model with a polynomial structure is built non-intrusively from satellite data over a 30-day training period, showing the first five proper orthogonal decomposition modes to capture the SST evolution. A moving-window assimilation scheme utilises the reduced-order model adjoint to correct the prior state, enforcing the model equations over the assimilation window with state observations. Results show that this framework corrects drift, extending the prediction horizon from one week to twenty days. We demonstrate the efficacy of the discovered models using error metrics and their ability to accurately capture lateral SST gradients. Importantly, the inferred operators from the reduced-order model enable the derivation of an explicit adjoint directly from the data, overcoming the computational constraints of General Circulation Models that prohibit rapid adjoint-based assimilation. The performance of the reduced-order model over multiple seasons will also be presented, including the effects of training with data from several years.

How to cite: Madduri, S. H. Y. K., Mathur, M., and Kalur, A.: Data-Driven Modelling and Assimilation of the Sub-Seasonal Evolution of Sea Surface Temperature, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-707, https://doi.org/10.5194/egusphere-egu26-707, 2026.

We present the progress of the project Twin-ER: Pilot Digital Twin for Earthquake Risk. The goal of the project is the integration of digital models of the city and the Earth into the structure of a digital twin, focused on seismic risk.

The Earth model includes the generation of new seismic source models based on maps correlating surface deformation and seismic activity rates. Deformation maps will be determined through the analysis of GNSS time series and InSAR images for several dates. Seismic activity rates will be calculated by combining statistical analyses of the seismic catalog with mechanical analyses of earthquake-related stress changes in the crust. The derived maps will show location-, magnitude-, and time-dependent activity rates. Seismic source models will form the basis for the development of seismic hazard maps and constitute the main component of the Earth model.

The city model integrates innovative exposure models based on Cadastral data, enhanced with machine learning and deep learning algorithms to identify building typologies and their seismic vulnerability. These analyses will incorporate data of different nature, such as cadastral reference value or exposure time to high temperatures, with the aim of extending the exposure to a multi-hazard and multi-risk context. The exposure and vulnerability models constitute the main component of the city model.

By combining seismic hazard models on one hand, and exposure and vulnerability models on the other, the seismic risk model will be obtained. This model represents the expected damage and losses in a city in the event of an earthquake. Therefore, it is a crucial piece of information for proposing risk mitigation measures and planning emergency response.

Both Earth and city models are embebed into the digital twin seismic risk. This digital twin is conceived in a pilot phase. The model will be fed with the results of risk simulations, which can be visualized in a web environment, leaving aspects of data loading automation from updated sensors or external servers and subsequent simulations with that updated data for future developments.

The project is applied in two study areas of similar size but different, complementary characteristics. One is southeastern Spain, where (1) seismic activity is moderate, and major earthquakes occur rarely, (2) cities have a relatively old building stock and are more vulnerable to earthquakes, and (3) the availability and accessibility to cadastral data are optimal. The other study area is El Salvador, where (1) there is high seismic activity with frequent large earthquakes, (2) cities have a relatively modern building stock with abundant informal construction, and (3) there is no free access to cadastral data.

 The advances presented here include the UML model of the entire digital twin, the seismic activity and deformation maps in SE Spain, and the city 3D models of two scenarios of application.

How to cite: Staller, A., Gaspar-Escribano, J., Torres, Y., Martínez-Cuevas, S., Arranz, J. J., García-Aranda, C., Iturrioz, T., and Pallero, J. L. G. and the Twin-ER Team: Progress of the Twin-ER project: pilot digital twin for earthquake risk, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20253, https://doi.org/10.5194/egusphere-egu26-20253, 2026.

The net zero (NZ) agenda is one of the foremost planetary challenges facing urban policymakers - presenting both localised impacts, along with transnational co-operation and governance challenges. Data is fundamental to measuring policy success and failure and taking informed intervention decisions, and global Earth Observation data has enhanced evidence bases in terms of where local actions are needed. In the face of evolving national politics, it is common for city-regions to lead on NZ policy. However, the distribution of multi-level powers and resources fundamentally shapes what urban leaders can do and who they need to work with to respond to the climate emergency. Given this complex policy architecture, progress towards NZ is dependent on the effective use of data. Many intermediate city-regions need support to build capacity and marshal data effectively, and questions about which data sources to deploy at specific contexts can be difficult to resolve. This leads to the possibility for a gap between the sophistication of data which may be able to support policymakers – increasingly available from breakthrough techniques and modelling – and capability, governance and communication issues in subnational policymakers’ ability to act. Starting with the end users of data at city-region level, we explore the need for better understanding between the policy and data/science communities.

How to cite: Allan, G., Oda, T., and Waite, D.: How does the growing availability of novel data interact with the uses of data by policymakers in city-regions on their journey to net zero?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14570, https://doi.org/10.5194/egusphere-egu26-14570, 2026.

Climate adaptation is critical for the functionality and quality of life in urban areas under more frequent and severe extreme weather events, such as heatwaves, droughts, and floods. Smaller towns, however, may struggle to adapt because of funding issues, administrative burdens and difficulties using environmental data. This study presents EcoScapes, a decision-support framework to enhance LLM advisory with local Earth observation data. EcoScapes integrates three key components: automated acquisition and preprocessing of Sentinel-2 imagery; Vision Language Models (VLMs) for structured interpretation of satellite-derived representations; and a downstream knowledge-based advisory workflow inspired by prior work.

Given a user-provided town or city name, EcoScapes geocodes the location and retrieves Sentinel-2 imagery for a 5 km bounding box around the urban center. To minimize cloud interference, we use a 1% cloud cover filter, which enables usability but might bias towards drier conditions and miss seasonal water bodies. EcoScapes processes satellite data rendered by the Sentinel-2 API, which includes RGB, water, and moisture views. The system uses a modular analytical pipeline, with an RGB analysis module employing a VLM to describe urban structures, like built-up areas, green spaces, and roads, via focused prompts. This approach reduces hallucinations and ensures more accurate analyses. Separate water and moisture modules analyze the outputs. Water analysis removes small, likely irrelevant features before an RGB-based step connects identified water bodies to their environment and infrastructure. Moisture analysis is used to find heat islands. Finally, a local small language model combines outputs into a single “Climate Report”. This report is subsequently used as context for a ChatClimate-style [1] system that is grounded in the IPCC AR6. This enables a comparison between a baseline advisory system relying on the knowledge base alone and the same system augmented with EcoScapes’ local report.

Since EcoScapes generates varied text outputs, we qualitatively assess its performance using two contrasting case studies: Roßtal, a small rural community of 10,000 people, and Erlangen, a medium-sized city with a population exceeding 100,000. The results indicate EcoScapes can provide useful local context where pre-existing model knowledge is limited. EcoScapes’ report made Roßtal’s adaptation recommendations more relevant and usable, correcting geographically inaccurate suggestions in the baseline. However, EcoScapes’ own inconsistencies and occasional hallucinations remain a limiting factor. The downstream recommendations were affected by errors in interpreting water data in Erlangen, relative to the baseline system, which was more familiar with the city because of its training data. EcoScapes demonstrates Sentinel-2 data’s potential to improve climate advice in smaller towns. Achieving generalization will require improved multimodal reasoning and higher resolution images, while broader evaluation is necessary to determine whether such generalization holds.

More information can be found at our GitHub repository (https://github.com/Photon-GitHub/EcoScapes) and the corresponding paper on arXiv (https://arxiv.org/abs/2512.14373).

References

[1] S. Vaghefi et al., “Chatclimate: Grounding conversational ai in climate science,” Communications Earth & Environment, vol. 4, no. 1, pp. 480, 2023

How to cite: Röhn, M., Gourmelon, N., and Christlein, V.: EcoScapes: LLM-Powered Advice for Crafting Sustainable Cities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3515, https://doi.org/10.5194/egusphere-egu26-3515, 2026.

In the context of a rapidly changing climate, there is a growing need to assess the impacts of climate change on natural systems, infrastructure, and human activities. Arctic regions are particularly vulnerable, as climate-driven changes extend beyond environmental degradation to significantly affect multiple socioeconomic dimensions. Therefore, there is an increasing need for holistic frameworks capable of capturing and analysing the socioeconomic impacts of climate change on local Arctic communities. In this regard, recent advances in geoinformation technologies - particularly Earth Observation (EO), cloud computing, Geographic Information Systems (GIS), and WebGIS platforms - offer unprecedented opportunities for Arctic climate change research. Nevertheless, a notable gap remains in existing methodological approaches for the effective integration of geoinformatics with socioeconomic studies. This study aims to provide an overview of the EO-PERSIST project, an EU-funded project under the MSCA Staff Exchanges scheme, which aims at developing a cloud-based geospatial platform for understanding the socioeconomic impacts of climate change on Arctic communities. In addition, this study presents the proposed methodological frameworks integrating socioeconomic and geoinformation data developed under EO-PERSIST project, alongside key results from the socioeconomic modeling and the project’s Use Cases. Overall, this work highlights the need for an interdisciplinary and integrated approach that combines EO data, geospatial technologies, and socioeconomic analysis to support informed decision-making in Arctic regions. The EO-PERSIST geospatial platform contributes to this effort by providing key research outputs and methodological approaches that support adaptation strategies and policy development, ultimately enhancing resilience in Arctic permafrost environments.

Keywords: GIS; Earth Observation; Geoinformatics; EO-PERSIST, Cloud Platform, Arctic, Socioeconomic Impact; Acknowledgement The present research study is supported by the project “EO-PERSIST”, funded by the European Union’s Horizon Europe research and innovation program (HORIZON-MSCA-2021-SE-01-01, under grant agreement no. 101086386

How to cite: Starakis, M., Myofa, N., Volianaki, E., Tselos, G. N., Petropoulou, K., Detsikas, S. E., Litke, A., and Petropoulos, G. P.: Assessing Socio-Economic Impacts of Climate Change in the Arctic through Geoinformatics: the contribution of EO-PERSIST project , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1736, https://doi.org/10.5194/egusphere-egu26-1736, 2026.

Planetary Boundaries (PBs) define biophysical limits that safeguard Earth system stability. Exceeding these limits undermines ecosystem services, food security, economic stability, and climate resilience. Humanity is currently transgressing several of the PBs, demanding integrative and transformative research approaches that connect biophysical monitoring, sustainability targets, and societal decision-making. Despite its conceptual strength, the PB framework remains difficult to operationalize for regional agricultural systems. Global-scale assessments obscure the pronounced spatial heterogeneity of farming landscapes, where localized exceedances in nitrogen cycling, freshwater use, climate sensitivity, and biosphere integrity accumulate to drive broader Earth system risks. Consequently, there are limited guidance on where, how, and under which biophysical constraints agriculture can remain productive without breaching local environmental limits. This study proposes an integrated monitoring and modelling paradigm to assess regional agricultural production within planetary boundaries.

Our method moves beyond static, indicator-based assessments toward a dynamic, process-aware evaluation of local biophysical variables. We integrate high-resolution climate, soil, and land-use data with a spatially explicit crop model (SIMPLACE) to define regional control variables, including yield thresholds, nitrate leaching, and water-stress limits. To address structural uncertainties and capture non-linear climate-crop-soil interaction, we develop a hybrid modelling approach that couples SIMPLACE with machine learning algorithm (XGBoost).

Using SSP5-8.5 projections, we quantify specific yield and environmental constraints for Winter Wheat and Silage Maize in the Berlin–Brandenburg region in Germany. Hybrid simulations significantly outperform standalone process-based models, reducing mean absolute percentage error by ~9% for Winter Wheat and yielding consistently higher skill for Silage Maize. Our results reveal that emerging local boundaries are increasingly governed by compound climate extremes, particularly heat stress and precipitation deficits during flowering and early grain filling.

By framing PBs at the regional scale, hybrid modelling approaches enable the identification of conditions under which agricultural productivity, climate adaptation, and environmental integrity remain compatible—and where biophysical limits impose fundamental constraints. This approach offers a transferable pathway for embedding planetary stewardship into regional agricultural planning, climate adaptation strategies, and land-system governance.

How to cite: Halder, K., Srivastava, A. K., Almeida, B., Nowak, L., Awoke, M. D., Stuckas, H., Fritz, S., Helming, K., and Ewert, F.: Assessing Agricultural Production within Planetary Boundaries using an Integrated Monitoring and Hybrid Modelling Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20658, https://doi.org/10.5194/egusphere-egu26-20658, 2026.

Urban-rural interdependencies from an Earth system’s view

Global demand for resources such as food, building materials and water is rising, while land take —driven significantly by urbanization—is accelerating and has become a critical factor. This surge in demand is accompanied by the spatial decoupling of production and consumption regions, leading to unevenly distributed environmental damage. Consequently, issues like soil degradation, water pollution, and greenhouse gas emissions are externalized and cause the deterioration of natural conditions in the hinterland or in teleconnected rural areas. Accordingly, sustainability balancing ecological, social and economic aspects can hardly be achieved.

While the Earth system sciences in the Anthropocene also deal with the cumulative effects of human activity on environmental change, research on urban-rural interdependencies in the context of global sustainability remains rare. However, compliance with Earth system boundaries requires integrated approaches across resources, sectors and spatial scales. This necessitates rethinking urban-rural relationships beyond the traditional dichotomy of producers and consumers and instead views them as cooperative socio-ecological systems.

Based on the thematic examples of food, material, water and land use, we highlight regional approaches and derive three fundamental principles—‘circularity’, ‘spatial justice’, and ‘participation’—alongside with two heuristic perspectives: ‘socio-ecological systems thinking’ and ‘framing and governance'. hey are used to propose an advanced research agenda covering (i) an integrated framework for system knowledge on the complex and dynamic urban-rural interdependencies, (ii) scientific references for regional target knowledge informed by Earth boundaries, and (iii) the examination of governance structures as transformation knowledge to enable cross-regional design and implementation.

How to cite: Warner, B. and Müller-Petke, M.: Urban-rural interdependencies from an Earth system’s view, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9385, https://doi.org/10.5194/egusphere-egu26-9385, 2026.

Climate change contributes to the emergence of multiple hazards, including zoonotic diseases whose transmission dynamics are closely linked to environmental and socio-ecological transformations. Following the Covid-19 pandemic, a re-emergence of CCHF was observed in Senegal, particularly in rural areas where livestock farming plays a central role. This emerging zoonosis, transmitted mainly through ticks and infected cattle, remains poorly understood by the general population and disproportionately affects women involved in agro-pastoral activities. While epidemiological responses currently use a One Health framework, the approach often lacks community inclusion and adequate consideration of mental health. Previous global health emergencies (Ebola and Covid-19) have led to social, psychological, and emotional disruptions, causing fear and reinforcing misconceptions about health measures and denial of disease, particularly in contexts where cultural beliefs and mistrust hinder public health interventions. This study analyses the psychosocial effects associated with the emergence of CCHF in order to identify key challenges for epidemic interventions within a broader context of climate-related health risks. A mixed-methods approach was conducted across eight regions of Senegal, combining surveys, observations, and in-depth interviews (IDIs). Quantitative surveys were administered to 434 livestock keepers at the household level, alongside interviews with 6 farmers to assess knowledge of zoonotic diseases and risk perception. In 2023, field observations focused on surveillance activities, followed in 2024 by IDIs with 10 directly affected individuals, including bereaved families, and 6 health professionals involved in case management. The findings reveal limited knowledge and low risk perception of zoonotic diseases among livestock keepers, who often rely on informal practices for disease management. High levels of psychological distress, including fear, panic, insomnia, and social stigma, were reported among patients, relatives, and communities. Isolation measures and restrictions on visits intensified suffering, eroded trust in response teams, and in some cases triggered hostility toward intervention actors. Health professionals experienced ethical dilemmas between their duty of care and fear of infection, exacerbated by harsh climatic conditions. The study highlights the need for systemic and multidisciplinary risk-reduction strategies that extend beyond biomedical control. This call for Integrating structured psychosocial support, community engagement, and culturally sensitive communication. Strengthening the links between environmental change, disease emergence, mental health, and social behaviour is essential to enhancing resilience and preparedness for future epidemics in climate-vulnerable contexts.
Keywords: emerging zoonotic diseases, CCHF, climate-related health risks, risk perception, psychosocial effects, epidemic intervention, Senegal.

How to cite: Ndoye, F., Sène, M., Ndione, A. G., Sow, A., Tine, J. A., Leneman, M., Boersma, K., Ndour, A. P., and Ngowi, H. A.: Psychosocial effects and intervention challenges during the re-emergence of Crimean–Congo Hemorrhagic Fever (CCHF) in Senegal, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21166, https://doi.org/10.5194/egusphere-egu26-21166, 2026.

How, and to what extent, can societal norms legitimately enter scientific knowledge-making, or can science intervene in societal norm-making? This question has become a key matter in defining and studying the Anthropocene as a new geological epoch. This paper aims to enrich the discussion by examining how two kinds of norms – one operating primarily within the boundary of science and the other originating from broader societal concerns – came to intersect in the debate over formalizing the Anthropocene as a new geological epoch. The first part of the paper traces the historical development of the GSSP practice as the central normative backbone of modern chronostratigraphy. Drawing on archival documents from the International Subcommission on Stratigraphic Classification (ISSC), in which the concept of GSSP was first debated and negotiated, it shows how the classification of geological time became a GSSP-based institutional practice through specific procedures, standards, and conventions for recognizing particular stratigraphic signals as valid evidence for defining geological time. Against this historical backdrop, the second part points out that, from its inception, the Anthropocene has carried the reflexive mode of thinking about the consequences of human activities, such as climate change, biodiversity loss, and habitability, hence calling for planetary stewardship. Since a new geological epoch can only be ratified through the acceptance of a specific GSSP proposal, formalizing the Anthropocene became a site at which the scientific norms constructed in the late 20^th century for the development of GSSP are brought into contact with the 21^st-century societal norms embedded in the concept of a human-driven Earth-system change. In a nutshell, the very term “Anthropocene” connotes both descriptive and prescriptive practices.

In 2023, the Anthropocene Working Group (AWG) submitted a GSSP proposal identifying plutonium-239 fallout from the mid-20^th-century nuclear testing as a globally synchronous marker, supported by multiple auxiliary stratigraphic proxies. As maintained by Skelton and Noone (2025) and the members of the AWG, this proposal has met the formal GSSP requirements with evidential robustness exceeding those of many previously ratified epochs. Nevertheless, the Subcommission on Quaternary Stratigraphy (SQS) voted to reject the proposal. This paper argues that the difficulties surrounding the formalization of the Anthropocene do not stem from matters of empirical evidence, but from matters of normative science: i.e., how existing scientific norms are to be interpreted, negotiated, and sometimes reconstructed when they encounter the pressure of societal imperatives to address planetary transformations. The paper thus asks how scientists should navigate the deeply humanistic implications of their stratigraphic decision about the Anthropocene.

How to cite: Koh, K. and Park, B. S.: Formalizing the Anthropocene: an interplay between normative knowledge-making and societal norm-making, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8747, https://doi.org/10.5194/egusphere-egu26-8747, 2026.

In May 2024, Samcheok Blue Power Unit 1, a coal-fired thermal power plant in Samcheok, Gangwon Province, South Korea, began commercial operation. Together with Unit 1 (completed in October 2023) and Unit 2 (scheduled for completion by the end of 2025), the Samcheok Blue Power complex will reach an installed capacity of 2,100 MW. Considering that fossil fuels are a decisive contributor to climate change and that South Korea has officially pledged to phase out coal by 2050, the continued construction and operation of a new coal plant in 2024 appears paradoxical. This puzzle becomes even more striking given that Samcheok has been widely recognized as a region with a successful anti-nuclear movement, suggesting the presence of an active environmental politics and a history of resistance to energy megaprojects.

To explore this contradiction, this research investigates how fossil fuel infrastructure is sustained through intertwined “circuits” of capital, material, and affect. In doing so, the study engages with debates on the technosphere, understood as a global assemblage of energy systems, infrastructures, institutions, and material interdependencies that shape, and often constrain, social and ecological futures. Rather than treating infrastructure as a self-contained system with clear boundaries, the study proposes the concept of infra-circuits. This concept emphasizes that infrastructures function as nodal points within circuits that are simultaneously connected and closed: they enable specific forms of connection while restricting others, much like electronic circuits that allow flow only through certain configured pathways. Infra-circuits are also chained, meaning that if one link is disrupted, the stability of the entire configuration is threatened unless alternative routes can be mobilized.

Importantly, infra-circuits are not only spatial but also temporal. They operate through inherited material pathways, regulatory arrangements, financial instruments, and labor regimes that bind present energy decisions to past investments and future obligations. While this resonates with socio-technical systems theory and its emphasis on path dependence, the concept of infra-circuits allows for analytical dimensions that remain underdeveloped in conventional approaches to technological adoption and innovation. Specifically, it draws attention to how infrastructures endure by assembling heterogeneous circuits of matter, finance, and affect, thereby revealing the intimate relationship between fossil development and patterned forms of public sentiment, attachment, fear, and aspiration.

By highlighting the chained and temporally extended nature of these circuits, this study argues that fossil infrastructure persists not merely due to economic rationality or policy failure, but because it is embedded in technospheric arrangements that stabilize particular futures while foreclosing others. Ultimately, the concept of infra-circuits offers a framework for rethinking fossil energy infrastructure as a material and affective formation situated at the apex of ecological crises in the Anthropocene.

How to cite: Kim, J.: Infra-circuits of fossil capital and Technosphere: More-than-human politics of the Samcheok thermal power plant, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8729, https://doi.org/10.5194/egusphere-egu26-8729, 2026.

There is a pressing need for developing pedagogical frameworks that respond to the damaged, uneven, and entangled planetary conditions of the Anthropocene. I propose “patch-based learning” as a new pedagogical concept, in order to engage learners with the deep predicaments of the Anthropocene. The case study focuses on Yongsan in central Seoul, South Korea—a site marked by layered histories of militarization, displacement, and environmental degradation. Attending to ferality, terrestrial traceability, and denizenship as guiding vectors for traversing Yongsan, I explore ways of reading the site as Anthropocene patches and consider the pedagogical significance of such a reading. I argue that patch-based learning may offer a way to work with the ruptures, leaks, and feral dynamics that characterize planetary landscapes in the Anthropocene.

How to cite: Ahn, S.: How to Reimagine Education in the Anthropocene: Patch-based Learning of Feral Beings and Effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4187, https://doi.org/10.5194/egusphere-egu26-4187, 2026.

As human exploration advances into increasingly hostile and isolated environments, such as extraterrestrial habitats on Mars, the Moon, or deep-sea stations, the concept of resilience must evolve beyond its traditional technical and physiological dimensions.

This need becomes particularly critical in contexts of long-duration habitation, where survival alone is insufficient to guarantee long-term operational stability and human wellbeing.

Central to this assertion is the recognition that resilience entails examining construction in relation to permanence, which may also be understood as a sense of feeling at home, shifting resilience from a purely performance-based concept to a relational and experiential condition.

This perspective requires redirecting science, technology, and design toward the conditions that enable habitation to become sustainable, meaningful, and socially durable.

This includes environmental adaptation, understood as the strategic use of local raw materials and regenerative systems, reducing dependency on external supply chains and increasing environmental compatibility, as well as the processes accompanying construction, which involve the complex relationships between these local materials, the tools, crafts, and other elements that make construction possible.

These construction–material ecologies play a decisive role in transforming temporary shelters into places of permanence.

Finally, it encompasses cultural embeddedness, which acknowledges the importance of cultural identity, symbolic practices, and sensory experiences that converge in the creation of an atmosphere of resilience, influencing perception of safety, cohesion, and long-term habitability.

The literature on this concept is fragmented due to the complexity and interdisciplinary nature of the aspects involved in the state of feeling at home.

Architecture, design, sociology and anthropology, nutrition, indoor environmental quality (thermal, acoustic, lighting, olfactory), tactile experience, physical activity, structural safety, and risk perception all contribute to this condition, yet are rarely addressed within a unified framework.

A common view across disciplines is missing in the related literature, yet it is of fundamental importance to understand and to design the future of resilient spatial architecture, both in extraterrestrial settings and in climate-stressed environments on Earth.

This abstract proposes a theoretical framework for understanding resilience in these terms, emphasizing the integration of cultural, psychological, material, and collaborative factors in the sustainable design of long-term human settlements in hostile environments.

By reframing resilience as the capacity to sustain a sense of “being at home”, the framework offers a shared conceptual ground for interdisciplinary dialogue across environmental sciences, engineering, architecture, and the social sciences.

 It challenges the prevailing techno-centric framing of resilience in extreme environments, arguing instead for a holistic approach that embraces human complexity, cultural roots, and collaborative innovation, with direct implications for climate adaptation, remote communities, and future off-Earth settlements.

How to cite: Alcindor, M., Salese, F., Sangiorgio, V., Araújo, A. M., Rodrigues, P. F. S., and Simão, E.: Feeling at Home as a Dimension of Resilience in Architecture for Extreme Environments , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16322, https://doi.org/10.5194/egusphere-egu26-16322, 2026.

Climate change adaptation and mitigation take place in a complex world associated with deep uncertainties related to external factors, among others population growth, new technologies, socio-economic developments and their subsequent impacts (Haasnoot et al., 2013, 2024). Therefore, there is a need for flexible framework that can respond to these challenges, bridge the social and environmental sciences and support climate change mitigation. Scenario planning can assist in developing integrative mental models to deliver pathways of change while incorporating alternative policies, evolving innovative practices and management options (Sroufe and Watts, 2022). The fundamental strength of the pathways approach is their ability to deal with uncertainty by assessing possible future impacts and navigating across multiple future trajectories. Pathways are designed to achieve future vision and assess whether the desired objectives have been accomplished (Coulter, 2019). Specifically, this approach can help to explore potential future trajectories, investigate innovation for carbon sequestering and more sustainable agriculture (Sroufe and Watts, 2022). So far, limited literature concerning development of pathways approach to GHG mitigation in agriculture exists.

Our approach aims to combine SSPs (Shared-socioeconomic pathways) downscaled for the Czech Republic within AdAgriF project with Mitigation pathways developed for Czech agriculture. Such integration enables us to assess the full potential of particular SSP-pathway combinations while considering future uncertainties. These SSP-independent pathways are not tied to a single SSP storyline, but instead each pathway is assessed for robustness across SSPs. This approach avoids over-commitment to one socio-economic future and highlights no-regret and robust mitigation pathways (bundles of measures).

This presentation highlights the process of interdisciplinary cooperation in order to support the pathway co-development, which involves exploring potential trajectories of pathways and their mitigation measures as well as SSPs with modelling using various agro-ecosystem simulation models that will be applied.

References:

Haasnoot, M., Di Fant, V., Kwakkel, J., & Lawrence, J. (2024). Lessons from a decade of adaptive pathways studies for climate adaptation. Global Environmental Change, 88, 102907. https://doi.org/10.1016/j.gloenvcha.2024.102907

Haasnoot, M., Kwakkel, J. H., Walker, W. E., & Ter Maat, J. (2013). Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change, 23(2), 485–498. https://doi.org/10.1016/j.gloenvcha.2012.12.006

Sroufe, R., & Watts, A. (2022). Pathways to Agricultural Decarbonization: Climate Change Obstacles and Opportunities in the US. Resources, Conservation and Recycling, 182, 106276. https://doi.org/10.1016/j.resconrec.2022.106276

How to cite: Krkoška Lorencová, E., Suchá, L., Koudelková, M., and Harmáčková, Z.: Designing mitigation pathways in Czech agriculture, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20080, https://doi.org/10.5194/egusphere-egu26-20080, 2026.

The most critical blind spot in contemporary climate crisis response is the reliance on standardized macro-metrics, which obscure the specific reality of individual suffering. Just as economics uses consumer sentiment to capture household realities and meteorology uses apparent temperature to reflect physiological truths, occupational safety must transition toward integrating perceived risks that exist beyond mere numerical thresholds. This study argues that human perception functions as a high-fidelity biological integration of environmental stressors and conceptualizes it as a Perceptual Trigger: an embodied risk signal with diagnostic and policy relevance. The 2023 fatality of a young logistics worker in Korea illustrates the lethal failure of current systems; while sensors recorded ambient conditions within regulatory thresholds, the system failed to register the worker’s chest tightness—a critical physiological survival signal.

To bridge this gap, a Living Lab for Heatwave Adaptation was implemented in August 2025, engaging 30 port workers from Incheon and 6 technicians from a specialized manufacturer of surface treatment additives as active co-creators. In this study, workers were not treated as mere subjects for data extraction but were empowered as epistemic agents who fundamentally identified and defined hazards within their real-world micro-climates. This study employed the Living Lab methodology as a requisite mechanism to derive Worker Perception Data, which can only be captured within the complex real-world context of the field. Through the systematic qualitative analysis of this co-creation process, the researcher demonstrated that complex heat risks—such as localized radiant heat, engine emissions, and entrapped micro-climates—which are systematically overlooked by standardized sensor arrays, can be effectively rendered into data via worker perception.

The core contribution of this research lies in its translational process: converting Worker Perception Data into systematic risk signals (Information), consolidating them into collectively validated Evidence, and establishing the Policy Grounds for the right to stop work. The researcher proposes a Complementary Governance Model that precisely fills the blind spots of technical sensor monitoring with the acute sensitivity of worker perception data, arguing that this model is a vital mechanism for ensuring site-specific climate adaptation. By framing the datafication of lived experience as an act of Industrial Democracy, this approach serves as an essential interface for connecting grassroots experience with institutional decision-making.

How to cite: Kim, J.: Beyond Metric-Centric Adaptation: Redefining Occupational Heatwave Governance through Living Lab Co-creation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20084, https://doi.org/10.5194/egusphere-egu26-20084, 2026.

Climate-sensitive vector-borne diseases are increasingly influenced by environmental and climatic variability, posing growing challenges for public health preparedness under climate change. Within the Planet4Health project, an Early Warning System (EWS) is being developed to support anticipatory decision-making for climate-sensitive diseases by integrating climate, environmental, and epidemiological information into operational risk products.

This contribution presents an EWS focused on the sand fly vector (Phlebotomus spp.) and leishmaniasis over the Iberian Peninsula, using machine learning–based modelling approaches. The system integrates high-resolution climate data, climate-derived indicators (e.g. temperature, humidity, and precipitation-related indices), land and environmental variables, and vector presence information to model conditions favourable for sand fly activity and disease transmission. The modelling strategy prioritises interpretable machine learning techniques to ensure transparency and usability for public health and veterinary stakeholders.

The EWS operates across multiple temporal scales, addressing short-term and seasonal forecasts, while also incorporating climate projections to assess potential future changes in  environmental suitability for sand flies and associated disease risk. Machine learning models are trained and evaluated using historical climate and entomological data, capturing non-linear relationships between environmental drivers and vector presence while explicitly accounting for uncertainty. Model outputs are translated into spatially explicit risk maps and alert-oriented indicators designed to support operational surveillance and decision-making.

Results from the Iberian sand fly–leishmaniosis case study demonstrate that the EWS successfully reproduces known spatial patterns of vector suitability and seasonal dynamics across the Peninsula, as well as interannual variability linked to climatic anomalies. The modular and data-driven design of the system supports adaptation of the framework to other regions and climate-sensitive diseases, in line with the broader objectives of Planet4Health.

Funding: The PLANET4HEALTH consortium is funded by the European Commission grant 101136652. The five Horizon Europe projects, GO GREEN NEXT, MOSAIC, PLANET4HEALTH, SPRINGS, and TULIP, form the Planetary Health Cluster. The data for EDENext was obtained from the Palebludata website (https://www.palebludata.com). The data for Vectornet was obtained from the ECDC.

How to cite: Natal, S., San-Martín, D., Maia, C., Marme, R., Berriatua, E., Verdú-Serrano, E., Risueño, J., Pérez-Cutillas, P., JImenez, M., and Molina, R.: An Early Warning System for sand fly-borne diseases in the Iberian Peninsula, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17834, https://doi.org/10.5194/egusphere-egu26-17834, 2026.

Rising extreme temperatures driven by climate change are expected to significantly degrade outdoor thermal conditions, stretching the day of extreme heat and leaving fewer hours for comfortable and safe outdoor activity, while increasing the health risks associated with outdoor exposure. This study investigates the impact of climate change on thermal discomfort across the Kingdom of Saudi Arabia. Projections from two CMIP6 models, at 6-hour temporal resolution, were used to compute the Discomfort Index (DI) based on dry-bulb temperature and relative humidity, and to assess diurnal variations in thermal stress at 03 UTC (06:00 AST), 09 UTC (12:00 AST), 15 UTC (18:00 AST), and 21 UTC (00:00 AST) under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Changes were evaluated for the near (2021–2040), mid (2041–2060), and far future (2081–2100). Thermal discomfort across Saudi Arabia intensifies progressively from the historical period to the far future, exhibiting pronounced spatial and diurnal variability. Historically, daytime discomfort (09–15 UTC) had a mean DI value of ~25.4 °C, corresponding to uncomfortable conditions across most regions, with some areas, particularly in the southeast and coastal regions, reaching very uncomfortable conditions. Early morning and evening hours (03–21 UTC) were slightly lower, with mean DI values around 22.8–23.4 °C, corresponding to slightly uncomfortable conditions. Future projections indicate a substantial increase in discomfort magnitude, particularly in coastal and southeastern areas. In the near-future (2021–2040), mean DI values increase to ~25–26 °C during daytime and ~23 °C during early morning and evening hours. By the mid-future (2041–2060), at 09 UTC (12:00 AST), the southeast and coastal regions are very uncomfortable and can reach extremely uncomfortable conditions under SSP5-8.5, reflecting peak thermal stress during the day. In the far-future period (2081–2100), at 09 UTC (12:00 AST), mean DI values reach ~27–28.6 °C under SSP2-4.5 and SSP5-8.5 scenarios, with maximum values exceeding 32 °C in the southeast region under SSP5-8.5, corresponding to dangerous conditions, highlighting the severity of midday thermal stress and its potential impacts on outdoor activities and urban livability. Evening and early morning mean DI values also rise substantially compared to historical conditions, reaching ~25–27 °C (uncomfortable), with some regions, particularly in the southeast, reaching up to ~30.5 °C (extremely uncomfortable), indicating that nighttime relief is markedly reduced and thermal discomfort persists even outside peak daytime hours. These findings emphasize the necessity of adaptive strategies to ensure the resilience, safety, and comfort of outdoor environments under increasing heat stress.

How to cite: Abuwaer, N., Vinodhkumar, B., and Al-Ghamdi, S.: Clocking the Heat: Projected Diurnal Patterns of Thermal Discomfort Across Saudi Arabia Under Future Climate Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10525, https://doi.org/10.5194/egusphere-egu26-10525, 2026.

Mediterranean territories are increasingly exposed to growing environmental fragility, risks linked to climate change and associated environmental disasters, as well as persistent socioeconomic challenges exacerbated by long-established patterns of urbanization. In this context, nature-based solutions (NBS) have been promoted by European policy frameworks as key tools for addressing these challenges. However, despite their growing political relevance, NBS often encounter barriers to implementation related to low public acceptance, limited social legitimacy, concerns about environmental and social justice, and insufficient integration of local knowledge and everyday practices.

This study addresses this gap by examining how local communities perceive, interpret, and interact with NBS in Mediterranean contexts through public participation processes in urban environments. The analysis focuses on several case studies located in Italy (Catania and Ferla, Demo 4), France (Saint-Jérôme and Saint-Charles, Marseille, Demo 5), Spain (Zaragoza, Demo 6), and Cyprus (Nicosia, Demo 9), within the CARDIMED project. These cases include various implementations of NBS, such as rain gardens, vertical green walls, green facades with vertical gardening and hydroponic systems, photobioreactor systems, biological drainage channels, and other nature-based interventions.

The study is theoretically grounded in socio-ecological governance and sustainability transition theories, conceptualizing NBS not only as technical measures but as relational and well-being-oriented solutions capable of reshaping human-environment relationships and strengthening social cohesion The participatory methodology draws on behavioral economics principles to analyze the underlying human behaviors, attitudes, and perceptions that condition NBS acceptance. To explore these dynamics, structured focus groups were conducted with key community representatives  (5 - 14 participants per group) to investigate shared perceptions, experiences, and concerns towards NBS, as well as their role in shaping narratives on water conservation, climate resilience, and sustainable land-use practices. The qualitative data were then analyzed using content analysis and ATLAS.ti software.

The results indicate that participatory processes play a decisive role in improving the awareness, legitimacy, and long-term governance of NBS, while revealing the structural and institutional constraints that risk undermining their transformative potential. These findings provide critical insights and pave the way for further investigation into justice-based and socially rooted NBS implementation pathways, supporting greater societal acceptance and strengthening collective ownership.

How to cite: Giuffrida, E. R., Sciuto, L., Cirelli, G. L., Quina Gomez, A., Muñoz Gonzalez, D. B., Fernandez, B. G., Zamudio Correa, A. F., and Licciardello, F.: Towards a citizen-based green transition: Nature-Based Solutions in mediterranean areas: CARDIMED project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19141, https://doi.org/10.5194/egusphere-egu26-19141, 2026.

Background

Policymakers lack structured, evidence-based processes and robust value assessments to guide planetary health investments. Health technology assessment (HTA)—a well-established framework for evidence-informed priority setting—has been proposed to address human and planetary health challenges under climate change. We aimed to assess whether existing evidence on adaptation can inform the prioritisation of planetary health interventions by examining their alignment with HTA criteria and decision-support tools.

Methods

We conducted a scoping review of adaptation interventions targeting climate-sensitive diarrheal disease or its determinants. Nine databases were searched from inception to May, 2025: BIOSIS Citation Index, CINAHL Complete, Econlit, Embase Classic+Embase, Global Health, GreenFILE, Medline ALL, Scopus and Web of Science Core Collection. Data was extracted on climate hazards, adaptation characteristics, outcomes, and HTA-relevant dimensions. Narrative synthesis and evidence gap maps were used to summarise patterns and identify gaps.

Findings

In total, 2924 studies were identified of which 88 studies describing 129 distinct adaptations were analysed. The findings highlight a disparate evidence base, with minimal alignment with HTA evaluative criteria or tools that facilitate prioritization within HTA, such as standardized criteria, economic evaluation and methods for addressing uncertainty.

Interpretation

As climate change alters diarrheal disease patterns, governments must balance investments between current service delivery and future climate risks. Evidence on adaptation for diarrheal disease remains limited to inform such trade-offs from an HTA perspective. These findings highlight research needs for advancing adaptation evaluation and evolving HTA from a human to a planetary health focus.

How to cite: Madriz Montero, A., Kooiman, F., Ruiz, F., Falconer, J., Harris, V., and Bozzani, F.: Prioritization of planetary health through health technology assessment: A scoping review , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17758, https://doi.org/10.5194/egusphere-egu26-17758, 2026.

Despite great reductions in the global burden of diarrheal disease, it remains a leading cause of mortality among children under five years old. Climate change threatens these gains, as extreme weather events such as floods, droughts, and heavy rainfall following dry periods are associated with increased risk. The impacts of climate change on childhood diarrheal disease burden depend on interactions between climate hazards, vulnerabilities, and pathogen exposures, although pathogen-specific impacts are not well understood. Improved understanding of how hydrometeorological factors influence pathogen-specific diarrheal disease is needed to predict future diarrheal disease risk and inform preventive action. The SPRINGS project (Supporting Policy Regulations and Interventions to Negate aggravated Global diarrheal disease due to future climate Shocks) brings together scientists from multiple disciplines to collaborate with communities, public authorities, and policymakers to address these challenges within a Planetary Health framework. The case study in Akuse, Ghana integrates epidemiology, environmental sampling, and weather data.  

This study aims to determine how hydrometeorological variables influence the incidence of medically-attended diarrheal disease among children under five in Akuse, Ghana. More specifically, this study aims to assess whether the influence of hydrometeorological variables on diarrhea is direct or acts through intermediate impacts on water quality and other water, sanitation and hygiene (WaSH) factors. By identifying climate-sensitive transmission pathways, this study will improve projections of future diarrheal disease risk and identify potential targets for intervention to mitigate the impact of climate change on diarrheal disease in this area in Ghana. 

This two-year epidemiological study employs a case-control study design, with a nested case-crossover study. Children under the age of five presenting to four selected health facilities with and without diarrheal disease will be recruited as cases and controls, respectively. Surveys administered by local nurses will collect data about individual- and household-level risk factors, including WASH conditions and animal ownership. In addition, stool samples will be collected to estimate the attributable incidence of diarrheal disease due to four key diarrheal pathogens: rotavirus, Campylobacter, Cryptosporidium, and Giardia. Local weather conditions during the study will be monitored by weather stations positioned near each health facility. Throughout the study, water samples will be collected from various sources in the study area to be tested for multiple water quality parameters, including the presence of the four diarrheal pathogens of interest. Additionally, anthropological research will improve the understanding of human behaviours and perceptions related to diarrheal disease risk and climate change in this area.  

By linking weather variability, environmental pathogen presence, WASH factors, and child health outcomes, this study illustrates how a Planetary Health approach can improve understanding of climate-sensitive diarrheal disease risk and provide evidence to inform adaptation strategies and child health interventions in Ghana.

How to cite: Kooiman, F.: The influence of hydrometeorological variables on childhood diarrheal disease: A Planetary Health approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22160, https://doi.org/10.5194/egusphere-egu26-22160, 2026.

As coal-dependent regions increasingly transition away from fossil fuels, questions about how to responsibly close and transform coal mines have gained global attention. In India, where coal mining has created monoeconomies with considerable informal and semi-/unskilled employment opportunities, the closure and transition of coal mines has significant implications for mining communities’ livelihoods and landscapes. However, existing approaches to post-mining land management globally tend to prioritize technical remediation and environmental compliance associated with mine closure and often overlook the voices and priorities of affected communities. Where stakeholder perspectives are solicited, it is most often through structured, quantitative multicriteria decision analysis (MCDA) techniques incorporating the perspectives of mining personnel and geotechnical experts rather than community members. Even while India and other countries (e.g., Australia) champion the use of participatory methods and stakeholder involvement in mine‑closure planning, there is still no agreed-upon set of protocols for fostering consistent, in-depth engagement. A critical gap persists between grassroots, community‑led initiatives and more technical top-down approaches, and research from the social sciences on mining remains notably scarce.

This study addresses this gap in the post-mining land use (PMLU) literature by explicitly incorporating social and community priorities into suitability assessments of PMLUs in the Indian context. We propose a “people-centric” approach integrating spatial‑decision support tools with social‑ecological systems thinking, which enables the identification of PMLUs which are not only suitable to the specificities of the mine site, but in line with more pressing socio-economic needs faced by surrounding stakeholders, particularly mining communities. Our three phase approach includes I) compiling information about the mine site, key stakeholders, and the regional context, II) understanding the social-ecological system the mine site is situated in, and III) developing spatially-explicit PMLU recommendations that are both technically appropriate for the site and match stakeholder needs and priorities. 

Phase I involves (re)assessing the mine site to ensure the site meets baseline environmental standards as well as engaging with regional and local stakeholders to solicit priorities, build trust, and set expectations. Phase II uses qualitative system dynamics modelling and causal loop diagrams to understand key social-ecological linkages and feedbacks, and then match the most relevant PMLUs to stakeholder priorities. Phase III involves identifying relevant geotechnical, biophysical, and socioeconomic criteria for each selected PMLU, and conducting a geographic information system (GIS)-MCDA with conflict resolution algorithms to map the most suitable locations within the mine site for each use.

Our workflow is designed to be flexible and responsive to changes in context; each phase operates along a spectrum of Low‑Medium‑High complexity, allowing for differences in data availability and time/resource constraints for stakeholder consultations, which is particularly important in low and middle income contexts like India. By foregrounding community priorities and embracing mixed-methods, we seek to bridge the gap between geotechnical and socio-cultural approaches to coal mine repurposing, identifying PMLUs that are not only technically feasible, environmentally sound, and economically viable, but deliver tangible livelihood benefits while preserving sociocultural ties to the landscape.

How to cite: Tiwari, A., Ramachandran, A., and Chowdhary, V.: A People-Centric Approach to Repurposing Coal Mines in India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5100, https://doi.org/10.5194/egusphere-egu26-5100, 2026.

Exposure to fine particulate matter (PM_2.5) has been linked with adverse birth outcomes in Nigeria. Emerging evidence suggests that high temperatures may also be associated with these outcomes. However, this association, as well as whether temperature modifies the effects of PM_2.5 on these outcomes, has not been explored in Nigeria.
Using data from the 2018 Nigerian Demographic and Health Survey, we examined the association between maternal exposure to maximum temperature (Tmax) during pregnancy and adverse birth outcomes, including Low Birth Weight (LBW), Preterm Births (PTB), and Stillbirths (SB). A daily maximum near-surface air temperature gridded dataset (2012-2018) at 1-km² resolution was obtained from Zhang et al. (2022) and linked to birth clusters based on geographic coordinates. Temperature metrics (hot days and heatwave events) were derived from the 90th percentile threshold of the daily Tmax values, based on all pregnancy periods. Logistic regression analysis was used to estimate the association between these metrics and birth outcomes. The intensity, frequency, and duration of these temperature metrics in relation to the birth outcomes were also evaluated. We then estimated the Relative Excess Risk due to Interaction (RERI) using interaction terms for each temperature metric during the corresponding PM_2.5 exposure period.
We observed a strong correlation (r=0.93) between the model temperature data and observational data (2012-2018). An increasing positive association was observed between the duration of hot days and PTB, while an increase in heatwave events was positively associated with LBW. Intensity in hot days was positively associated (1.59; 95% CI: 1.28-1.96) with LBW. At the same time, frequency in hot days showed no significant relationship with any of the birth outcomes. Positive additive interaction between high temperature and PM_2.5 was observed across exposure categories for LBW and SB. The magnitude of interaction was greater at moderate PM_2.5 levels (Q2) for LBW, while the highest levels (Q3) had a greater effect for SB. As global temperatures rise, these findings provide evidence that maximum temperature can intensify the health burden of ambient PM_2.5 during pregnancy, underscoring the need for climate-adaptive maternal health interventions.

How to cite: Seyinde, D. and Dey, S.: Adverse Birth Outcomes Attributable to High Heat in Nigeria , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-694, https://doi.org/10.5194/egusphere-egu26-694, 2026.