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OEMC Project Use Case: Tools and Data for Improved Biomass Estimation
No full textImproved biomass estimation reduces uncertainties of the terrestrial carbon sink assessment. Current methods of estimating forest biomass, such as cutting down trees and weighing them, are not feasible on a large scale. ESA CCI Biomass maps, for example, minimize estimation errors globally but can have suboptimal performance when locally assessed, particularly in regions with highly heterogeneous forests. Biomass validation is important for developing reliable biomass models but is also challenging because of the lack of field data and because most national forest inventory data are not open. Therefore, this use case will focus on developing auxiliary tools and data for improved biomass estimation for the ESA CCI biomass map over forests with reported lower performance. This will involve the preparation of high-quality satellite LiDAR data and their integration with other satellite imagery and forest management data using advanced modeling techniques. We will also analyze the potential of a mobile citizen-science biomass app to provide open forest field measurements and support the validation of EO-based biomass maps. This app will allow users to estimate biomass in the field quickly using a mobile phone. The goal is to provide high-quality satellite LiDAR heights that can be readily used to produce more accurate carbon maps and make the tools and data open and accessible so that a wide range of communities can use them
Priority climate and health modelling needs
Get PDFClimate and health modelling is necessary for improving understanding of the current and future distribution and timing of climate-related health risks. However, underinvestment in this area has limited the understanding required to inform policies that enable multisectoral interventions to safeguard health. We synthesised insights from a survey of 65 global climate and health modelling experts and 36 participants in a hybrid meeting to identify priority strategies for enhancing the validity, utility, and policy relevance of climate and health models. Foundational investments to support modelling included strengthening research capacity, establishing a network of multinational centres of excellence for transdisciplinary research and capacity building, improving data collection and sharing infrastructure, investing in scenario development and quantitative elaboration, assessing adaptation effectiveness, and committing to intermodel comparisons and interdisciplinary modelling activities. Specific recommendations included updating the 2014 WHO Quantitative Risk Assessment to cover a wider range of causal pathways and health endpoints, using interdisciplinary methods that facilitate model intercomparisons. Additional recommendations included supporting modelling of a broader set of climate-health outcomes, developing models to support early warning systems and investments in their implementation, evaluation, and maintenance, and improving health system capacity for modelling in low-resource settings
Myopic versus perfect foresight target setting for Indonesia’s net zero electricity transition
Get PDFIn the effort to align with Paris goals, decision-makers set targets that usually concern milestones earlier than 2100. These targets can be derived from different considerations of long-term implications of actions. This study investigates the implications of deciding on emissions targets based on myopic vis-à-vis perfect foresight using long-term energy system optimization model. The study reveals cost discrepancies correspond to the gaps between emissions derived from mixed integer linear programming (MILP) solution in perfect foresight scenarios versus exogenous values in myopic scenarios. When considering myopic approach, our study suggests that avoiding drastic emissions reduction can deliver minimum cost discrepancies relative to what can be achieved with perfect foresight. However, this poses a dilemma where less drastic emissions targets may risk increasing fossil power generation under lenient emissions reduction targets. Complementing less drastic emissions reduction targets with more ambitious policies promoting renewables is necessary to avoid the risk of increased reliance on fossil power generation
Assessing Community Resilience: Validating a Universally Applicable Flood Resilience Measurement Framework and Tool
Get PDFUnderstanding and strengthening community-level resilience to natural hazard-induced disasters is critical for the management of adverse impacts of such events and the growth of community well-being. A key gap in achieving this is limited standardized and validated disaster resilience measurement frameworks that operate at local levels and are universally applicable. The Flood Resilience Measurement for Communities (FRMC) is a foremost tool for community flood resilience assessment. It follows a structured approach to comprehensively assess community flood resilience across five classes of capacities (capitals) to support strategic investment in resilience strengthening initiatives. The FRMC is a further development of an earlier version (the FRMT, the Flood Resilience Measurement Tool). The FRMT has been developed and applied between 2015 and 2017 in 118 flood prone communities across nine countries. It has been validated in terms of content and face validity as well as in terms of reliability. To reduce redundancy and survey effort, the FRMC holds a lesser number of indicators (44 versus 88) and has now been applied in over 320 communities across 20 countries. We examine the validation for the revised resilience construct and the new community applications and present a comprehensive overview of the statistical and user validation process and outcomes in both practical and scientific terms. The results confirm the validity, reliability as well as usefulness of the FRMC framework and tool. Furthermore, our approach and results provide insights for other resilience measurement approaches and their validation efforts. We also present a comprehensive discussion about the dynamic aspects of flood resilience at community level, and the many validation aspects that need to be incorporated both in terms of quantification efforts as well as usability on the ground
Legacy leaks, lasting liabilities: elevating abandoned oil and gas wells in climate change mitigation policy
Get PDFAn integrated modelling framework for evaluating the synergistic impacts of low-carbon transitions and air pollution controls on air quality and health in Guangzhou, China
Get PDFClimate policies that target carbon emissions can induce co-benefits for air quality. Previous urban studies have typically focused on either carbon reduction or air pollution control independently, but few have examined their combined effects on reducing carbon emissions and consequential environmental gains. We develop an integrated modelling framework to assess the impacts of different low-carbon transitions and end-of-pipe controls on PM2.5 and ozone concentrations and associated premature mortality in the megacity of Guangzhou. The results show that the implementation of both deep carbon mitigation and aggressive air pollution control policies can reduce the city's pollutant emissions to 34%–51% of the 2020 levels by 2035. Consequently, the population-weighted PM2.5 concentration in 2035 is projected to decrease by 5 μg/m3 compared to the 2035 baseline scenario. However, the ozone concentration is expected to rise by 35 μg/m3 due to the reduced titration effect of NO on ozone. These changes are estimated to prevent approximately 3.0 thousand (95% CI: 2.0–3.9) PM2.5-related premature deaths, while increasing ozone-related premature deaths by approximately 1.6 thousand (95% CI: 0.7–2.7). Moreover, implementing multiregional integrated control measures in Guangzhou and its neighbouring cities yields greater air quality and health benefits for Guangzhou compared to local enforcement alone, resulting in 1.5 times more avoided PM2.5-related premature deaths. Additionally, the increase in ozone-related premature deaths from these cooperative emission control strategies is merely 0.3 times the figure observed under local enforcement alone. The transport and industry sectors play a crucial role in reducing air pollutant emissions, whereas reductions in the solvent use sector can help mitigate the adverse effects of reduced NOx on ozone pollution. These findings highlight the need for comprehensively multiregional strategies to balance the trade-offs between reducing PM2.5 and ozone-related health impacts, offering valuable insights for urban policy makers aiming to optimize both climate and air quality goals on a broader scale
Decoupling carbon emissions, economic growth, and health costs toward carbon neutrality in China's regions
No full textIn response to climate change, understanding regional and sectoral carbon emissions is essential for guiding China's low-carbon transition. This study analyzes carbon emission trends across provinces and industries in China from 2006 to 2020, covering the 11th to 13th Five-Year Plan (FYP) periods. Using the Logarithmic Mean Divisia Index (LMDI) method and Tapio decoupling model, we identify key emission drivers and decoupling patterns. Results reveal significant regional disparities: carbon emissions in the Northwest increased by 55 % during the 12th FYP and 46 % in the 13th FYP, reaching 380 million tons, while the Beijing-Tianjin region saw only an 8 % increase and achieved strong decoupling in the 13th FYP. Economic growth remains the main driver of emissions, particularly in the Central and Northern Coast regions, whereas energy intensity and industrial restructuring play important mitigating roles. The share of health expenditures in GDP rose from 4.7 % to 7.1 %, with the Northwest region peaking at 9.1 %, indicating links between emissions and health costs. The findings offer practical insights for region-specific policy design, including energy structure optimization, technological upgrading, and public health considerations
Developing Multi-Risk Drm Pathways – Lessons from Four European Case Studies
Get PDFIn the context of climate change and socioeconomic developments, disaster risk is intensifying, driven not only by more frequent and severe hazard events but also by complex interactions between these events and underlying vulnerabilities. These interactions can amplify impacts and trigger cascading failures across sectors. Using the Canary Islands, the Danube Region, the North Sea, and Scandinavia as four case study regions, this research explores how the Dynamic Adaptive Policy Pathways for Multi-Risk (DAPP-MR) framework can support the development of integrated, adaptive disaster risk management (DRM) strategies to reduce risk while addressing these complex interactions. We examine how DAPP-MR enables a deeper understanding of multi-risk systems, facilitates stakeholder engagement, and structures the development of robust, cross-sectoral DRM pathways in these four qualitative applications. The findings indicate that DAPP-MR enables integrated, cross-sectoral thinking and encourages balancing short-term priorities and long-term needs. This research demonstrates that DAPP-MR offers a structured approach to unravelling the complex dynamics between hazards and sectors, while maintaining flexibility in analytical focus. This flexibility allows context-specific priorities to guide the analysis, but it can also make comparing outcomes across different applications more challenging. This study further underscores the need for additional tools to manage and explore the information to support the development and evaluation of multi-risk DRM pathways
Citizen science and Earth Observation Data for “Rescuing” the SDGs
No full textThe UN Sustainable Development Goals (SDGs), adopted by the UN General Assembly in 2015, represent a global call to action to tackle the world’s most pressing challenges, from poverty to environmental degradation. Achieving these goals requires a data-driven approach, grounded in accurate, timely, and comprehensive data to guide policy and decision-making. Despite improvements in data availability over the past decade, with less than five years remaining to achieve the SDGs, substantial data gaps remain, limiting the ability to effectively monitor progress and guide policies and actions. Traditional data sources, such as censuses and household surveys, are insufficient to address these data gaps. New data sources, including Earth Observation (EO) data and citizen science, defined as public participation in scientific research and knowledge production, offer innovative and complementary solutions. Scientific literature has demonstrated the potential of these alternative data sources to fill critical gaps. For example, Fraisl et al. (2020) conducted a systematic review of SDG indicators and citizen science initiatives, showing that citizen science data are already contributing or could potentially contribute to monitoring 33% of SDG indicators. Their analysis also revealed a significant overlap with EO data contributions. According to GEO (2017), EO data are relevant to 29 SDG indicators, and Fraisl et al. found that citizen science could support 24 of these, demonstrating the complementarity between the two. Since publishing the aforementioned study in 2020, Fraisl et al. have been working with National Statistical Offices (NSOs) and UN agencies to demonstrate how this potential can be realized. A notable example is their collaboration with the Ghana Statistical Service, the Environmental Protection Agency in Ghana, and UNEP (as the custodian agency), which resulted in existing citizen science data on marine plastic litter being integrated into Ghana’s official statistics, as well as into the monitoring and reporting of SDG indicator 14.1.1b, Plastic Debris Density, under the leadership of the Ghana Statistical Service (GSS). This initiative bridged local data collection efforts with national and global monitoring processes and policy agendas through the SDG framework. The results were included in Ghana’s 2022 Voluntary National Review of the SDGs, reported on the UN SDG Global Database, and are informing national policies in Ghana. This makes Ghana the first country to use citizen science data for monitoring and reporting an SDG indicator. Their findings, published in Fraisl et al. (2023), provide valuable lessons for the EO community, not only from a technical perspective but also in building effective partnerships with NSOs, UN agencies, civil society organizations, academia, and other stakeholders to leverage EO data for SDG monitoring and reporting and sustainable development. This example highlights one of the ways citizen science is being utilized to support the SDGs. The oral presentation will showcase additional examples that emphasize the synergy between citizen science and EO in bridging SDG data gaps, informing or reshaping policies, and mobilizing action. It will also feature initiatives such as the Citizen Science Global Partnership (CSGP), hosted by the International Institute for Applied Systems Analysis (IIASA), which seeks to advance citizen science for a sustainable world and foster collaboration with the EO community to leverage the combined potential of citizen science and EO data for achieving sustainability. References: Fraisl D, Campbell J, See L et al (2020) Mapping citizen science contributions to the UN sustainable development goals. Sustain Sci 15:1735–1751. https://doi.org/10.1007/s11625-020-00833-7 GEO (2017) Earth Observations 2030 Agenda for Sustainable Development, V1.1. Japan Aerospace Exploration Agency (JAXA) on behalf of GEO under the EO4SDG Initiative. Available at: https://www.earthobservations.org/documents/publications/201703_geo_eo_for_2030_agenda.pdf Fraisl, D., See, L., Bowers, R. et al. The contributions of citizen science to SDG monitoring and reporting on marine plastics. Sustain Sci 18, 2629–2647 (2023). https://doi.org/10.1007/s11625-023-01402-
Water-Energy-Food Nexus in Tigris and Euphrates River Basin Through Systemic Lenses
Get PDFThis study investigates the systemic interconnections among the Water, Energy, and Food (WEF) sectors within the Tigris and Euphrates (TigER) basin, focusing on the historical trajectories and resource competition among its four main riparian states: Turkey, Syria, Iraq, and Iran. It examines how domestic political decisions influence cross-sectoral dynamics and impact the ecological integrity of shared transboundary resources. The research employs a multifaceted approach, combining a comprehensive literature review with an in-depth examination of state-level statistical data, drawing from academic sources, policy documents, and reports. In parallel, sectoral data was collected from reputable international organizations and structured within the WEF nexus framework. Our study highlights the intricate interdependencies that govern resource management within complex systems. The findings indicate that unilateral infrastructure projects—particularly Turkey’s GAP hydropower initiative with the goal of energy supply—have substantially reduced downstream water availability, most notably affecting Iraq’s agricultural productivity and food security. Crucially, the study demonstrates that WEF systems follow the ecological logic of the basin, transcending national boundaries. The study underscores the necessity of a cooperative, systems-based approach to resource management, emphasizing that ecological interdependence in the TigER basin requires regional coordination. Lasting stability depends on leveraging complementary sectoral strengths to achieve sustainable and equitable development