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The attribution of human health outcomes to climate change: transdisciplinary practical guidance
Get PDFFor over 30 years, detection and attribution (D&A) studies have informed key conclusions in international and national assessments of climate science, providing compelling evidence for the reality and seriousness of anthropogenic effects on the global climate. In the early twenty-first century, D&A methods were adapted to assess the contribution of climate change to longer-term trends in earth system processes and extreme weather events. More recently, attribution research quantified the health and economic impacts of climate change. Here we provide practical guidance to inform transdisciplinary collaboration among health, climate, and other relevant scientific disciplines and interested parties in designing, conducting, interpreting, and reporting robust and policy-relevant attribution analyses of human health outcomes. This guidance resulted from discussions among experts in health and climate science. Recommended steps include co-developing the research questions across disciplines; establishing a transdisciplinary analytic team with fundamental grounding in the core disciplines; engaging meaningfully with relevant interested parties and decision-makers to define an appropriate study design and analytic process, including defining the exposure event or trend; identifying, visualizing, and describing linkages in the causal pathway from exposure to weather/climate variables to the health outcome(s) of interest; choosing appropriate counterfactual climate data, and where applicable, to evaluate the skill of the climate and health impact model(s) used in D&A research; quantifying the attributable changes in climate variables; quantifying the attributable health impacts within the context of other determinants of exposure and vulnerability; and reporting key results, including a description of how recommendations were incorporated into the analytical plan. Implementation of guidance would benefit diverse interested parties including researchers, research funders, policymakers, and climate litigation by harmonizing methods and increasing confidence in findings
First steps towards bridging integrated assessment modeling and high-resolution energy system models: A scenario matrix for a low-emissions sector-coupled European energy system
Get PDFThe rollout of variable renewable energy (VRE) generators, along with the electrification of heating and transport sectors and the production of synthetic fuels for hard-to-abate industries, is a key strategy for mitigating climate change. Energy infrastructure planning models must accurately capture the high spatio-temporal variability of VRE to avoid misestimating their contribution to the power generation. Integrated Assessment Models (IAMs), which operate at a global scale with low spatio-temporal resolution, often rely on simplified VRE representations with predetermined parameters— potentially leading to suboptimal or infeasible scenarios. To address this limitation, we present the first study to impose forced VRE shares in the high-resolution sector-coupled energy system model for Europe, PyPSA-Eur, for the purpose of IAM parameterization. For a nearly net-zero CO2-emissions system that disregards existing energy infrastructure and builds the optimal capacity mix overnight, we assess the European potential of each technology type across a scenario space with varying forced VRE shares. We derive economic and technical parameters, providing insights applicable to models with lower spatio-temporal resolution
The carbon footprint of machine tools and metal working machinery in U.S. manufacturing
Get PDFRecent research suggests that one-third of the global supply of metals is used to produce machinery and industrial equipment (ME). ME production causes 8% of global greenhouse gas emissions. Yet, our understanding of how much different types of ME contribute is limited. While the energy use needed to operate machines usually enters life cycle assessments, the production of the machines is often neglected, mostly because data is lacking. Here we explore the use of detailed economic input-output data for the United States (USEEIO) to produce cradle-to-gate life cycle inventories for machinery for material handling and metalworking, machine tools, dies, fixtures, and industrial molds. The cradle-to-gate GHG emissions of the investigated machinery were 38 million tonnes CO2e (0.5% of US emissions), compared to 330 Mt for all ME. Materials contributed 46-63% to the carbon footprint of the ME in question, the production of electricity and fuels used in production processes other than materials production contributed 13-28%. Important uses of ME as capital products were in the manufacturing of vehicles, refining, and metal industries. Important uses as intermediate inputs were oil and gas production, mining, as well as manufacturing and commercial structures. This manuscript demonstrates the feasibility of using detailed input-output tables for life cycle inventory modelling of the production and use of ME
Reflections and Future Directions for Multi-Hazard Risk in the Context of the Sendai Framework and Discussions Beyond
Get PDFMulti-hazard events pose increasingly complex challenges to societies worldwide, as natural hazards interact in cascading and compounding ways that amplify risks beyond individual hazards. Understanding these complex interactions is critical for effective disaster risk management, preparedness, and response strategies. National and international frameworks have increasingly recognised these risk dynamics, most notably the Sendai Framework for Disaster Risk Reduction 2015–2030. With the Sendai Framework approaching its conclusion, there is a pressing need to address current shortcomings and contribute meaningfully to shaping the next generation of global disaster risk reduction (DRR) frameworks. Acknowledging this need, the 3rd International Conference on Natural Hazards and Risks in a Changing World took place on June 12–13, 2024, with the objective of strengthening the integration of multi-hazard risk into scientific research and policy practice in support of the Sendai Framework for Disaster Risk Reduction. Here, we document the arc of the scientific discussions held at the conference, synthesise the main findings from sessions, and set forth expert knowledge on how state-of-the-art science can fill gaps outlined by the Sendai Framework Mid Term Review by identifying four perspective themes: (1) assessments and tools for risk understanding and decision-making; (2) complex risk landscapes; (3) emerging technologies for risk and resilience; and (4) multi-level governance for coordinated risk management. Ultimately, there was a strong call from the conference for moving beyond siloed thinking toward greater integration of multi-hazards, vulnerability dynamics, multi-level governance, stakeholder engagement, and scientific disciplines across spatial and temporal dimensions, while recognising that the challenge ahead lies in finding the optimal balance between sufficient integration and manageable complexity. This perspective emphasises that effective DRR must initiate transformative processes to build resilience against increasing global challenges while informing the development of post-2030 frameworks and supporting broader Sustainable Development Goals
Water temperature regulations could help to balance biodiversity and energy security
No full textThermoelectric power plants discharge heat into water, which can harm aquatic species. Some regions regulate water discharge temperatures, but these regulations can cause outages, which makes compliance under global warming difficult to ensure. In this Comment, we argue that locally specific, optimized policies can help to balance biodiversity protection and energy demand
Science diplomacy. Using global environmental change as an opportunity for public diplomacy
No full textPublic diplomacy involves explaining US policy and perspectives and building relationships to foster greater collaboration and understanding of the US and the world. Science and technology increasingly permeate daily life in a multitude of ways, from providing healthy food, clean water, and new materials to enabling highly complex medical procedures and technological advances. As a result, public diplomacy relies on supplementing traditional diplomatic exchanges of education and culture with science and technology to foster international collaboration. Public diplomacy can use these scientific and technological advances to connect citizens, students, and scientific communities around the world as never before. Global environmental challenges (e.g., climate change, pollution, biodiversity loss, food and water insecurity) encompass a series of interconnected issues that increase risks to well-being and security. These common threats unite people around the world in new ways and forge connections to scientists, educators, and entrepreneurs in the search for sustainable and just solutions. Global challenges do not recognize national borders and cannot be solved by individual nations, meaning that diplomats occupy solution spaces where they enable trusted relationships and cultural understanding among scientists, policymakers, and communities by integrating science and technology into public diplomacy activities. Solutions that provide benefits from science and technology to human societies require productive relationships among stakeholder groups, including public engagement with science to promote collective action from citizens and policymakers at local, regional, subnational, or national levels (Biden, 2021). Here, we capitalize on the opportunity to contribute a chapter on science diplomacy with a focus on global environmental challenges to illustrate the positive outcomes and impact that can be achieved by integrating science with public diplomacy
Digital transformation in the Shared Socioeconomic Pathways
Get PDFDigital transformation refers to the widespread use of digital technologies in ways that reshape societal and economic activity, with significant impacts on sustainable development and climate challenges—both for better and for worse. Using statistical models calibrated to historical evidence in 62 countries across 12 world regions, we project future digital transformation within the Shared Socioeconomic Pathways (SSPs), adding contextual richness to this scenario framework used extensively in global climate research. In some scenarios, we find a pervasive and prolonged digital divide with up to 45% of the assessed population by mid-century still residing in countries with relatively low levels of digital transformation despite ever-deepening digitalisation in wealthier countries. We set out six use cases for how our explicit representation of digital transformation within the SSPs enables quantitative assessment of digitalisation’s impact on energy, emissions, climate policy, and Sustainable Development Goals. We also discuss challenges with using empirically calibrated models to project digital transformation given its rapid evolution and socioeconomic implications
Statistical atlas of European agriculture: gridded data from the agricultural census 2020 and the spatial distribution of CAP contextual indicators
Get PDFInternational organizations have voiced the need to integrate geographical information from agricultural holdings into official statistics to gain a better understanding of the spatial dynamics of the European agricultural sector. This paper presents a set of thematic maps based on the European 2020 agricultural census to explore the major structural differences between regions and countries. To comply with the confidentiality requirements associated with the census data, we applied a multi-resolution gridded approach by varying the resolution of the grid cells as a function of the density, dominance, and quality of individual observations. The datasets contain a mixture of grid resolutions ranging from 1 to 40 km, preserving a hierarchical structure where higher-resolution grid cells are aggregated into lower resolutions until the statistical disclosure requirements are met. The variables presented here correspond to the Contextual Indicators of the Performance Monitoring and Evaluation Framework of the Common Agricultural Policy and are divided into three broad categories: structural components (i.e., agricultural holdings, land use, livestock patterns, and labor input); the demographics of farmers (i.e., age, gender, and skills); and agricultural production methods (i.e., irrigation and organic farming). Our exploratory analysis indicates that high farm density occurs in plains, lowlands, and fertile soil in valleys; that high shares of organic farming tend to be concentrated in certain areas with high proportions of grassland; and that agricultural holdings managed by young farmers are located in a belt stretching from France through to Switzerland, Austria, Czechia, Slovakia, and Poland. These novel datasets are highly versatile, not only allowing policies to evaluate funding schemes at more local levels, but also offering researchers new opportunities to draw causal spatial inference from the multi-resolution gridded data. The dataset is the first attempt to create an unprecedented harmonized view of European agriculture with high spatial resolution and is available at https://doi.org/10.5281/zenodo.14852709
The role of artificial intelligence in climate change scientific assessments
Get PDFClimate change scientific assessments prepared by the Intergovernmental Panel on Climate Change (IPCC) face interconnected dual challenges: the exponential growth of literature, hindering synthesis efficiency, and the increasing length of its reports, impeding accessibility. Building upon the emerging discussion of adopting artificial intelligence (AI) tools in scientific assessments, this essay develops specific operational and governance frameworks to guide the IPCC’s integration of these tools. It makes three distinct contributions. First, it develops a systematic framework for AI-augmented evidence synthesis, detailing how machine learning (ML) can be integrated into each stage of the assessment workflow. Second, it provides a critical analysis of Large Language Models' (LLMs) use for reports communication through the lens of ‘addressable’ versus ‘inherent’ limitations, clarifying which risks require technical solutions versus those that demand robust governance. Finally, it proposes a novel governance structure for the IPCC based on two institutional roles, the ‘producer’ and the ‘assessor’ of AI products, to ensure scientific integrity is maintained. This essay provides a clear path for the responsible, expert-led integration of AI, ensuring it serves to augment, not replace, human expertise
Heterogeneity among Venezuelan migrants in terms of coping in the context of the population exodus from Venezuela
Get PDFThis study concentrates on the unparalleled exodus of Venezuelans in recent years. By June 2024, the global population of Venezuelan migrants and refugees had reached 7.7 million, with 6.6 million settling in Latin America. This represents one of the most significant migration outflows of the 21st century, with estimated numbers exceeding those of emigration from Afghanistan, Ukraine and Syria. However, coping strategies and integration of Venezuelans in hosting countries is understudied phenomenon in comparison to other migration movements. The aim of this paper is to examine patterns of coping among Venezuelan migrants. By analyzing coping strategies, we aim to contribute to enhance understanding of the characteristics of Venezuelan migrants in the context of their adaptation in the host countries in Latin America. We conducted a survey among Venezuelan migrants in Peru in 2023. The study is based on the Lazarus and Folkman model of stress and coping. A Coping Strategy Inventory-SF instrument and a Latent Class Analysis method were employed to distinguish three homogeneous subgroups in terms of coping strategies. We found three such subgroups: problem engagers, hybrid engagers and mixed strategy users. These groups exhibit distinct characteristics with regards to age, sex, education and optimism. The article highlights the heterogeneity in the use of coping strategies among Venezuelan migrants. To the best of our knowledge, this study is the first one to apply Lazarus and Folkman’s model in conjunction with Latent Class Analysis in the field of migration studies. We strongly believe the proposed approach is useful in increasing our understanding about coping strategies and integration among migrant populations