Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs.
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http://dx.doi.org/10.1016/j.scitotenv.2021.148549 | DOI Listing |
J Epidemiol Glob Health
December 2024
Environmental Health Department, Harvard T.H. Chan School of Public Health, 401 Park Dr, 4th floor, Room 412G, Boston, MA, 02115, USA.
Background: The Middle East, especially Kuwait, is experiencing rapidly rising temperatures due to climate change. Cardiovascular diseases (CVD) are the leading cause of mortality in the country, and extreme heat is expected to exacerbate hospitalizations for cardiovascular diseases. There is limited data quantifying the historical and future impacts of heat on hospitalizations for cardiovascular diseases in Kuwait.
View Article and Find Full Text PDFAccurate historical records of Earth's surface temperatures are central to climate research and policy development. Widely-used estimates based on instrumental measurements from land and sea are, however, not fully consistent at either global or regional scales. To address these challenges, we develop the Dynamically Consistent ENsemble of Temperature (DCENT), a 200-member ensemble of monthly surface temperature anomalies relative to the 1982-2014 climatology.
View Article and Find Full Text PDFSci Data
August 2024
European Commission, Joint Research Centre (JRC), Ispra, Italy.
Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.
View Article and Find Full Text PDFHeliyon
April 2024
School of Forest, Fisheries, and Geomatics Sciences University of Florida, Gainesville, FL, USA.
Iran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply to address the challenges posed by future climate change. Over the next two to three decades, the effects of climate change, such as precipitation and temperature, are expected to worsen, posing greater risks to water resources, agriculture, and infrastructure stability.
View Article and Find Full Text PDFSci Total Environ
June 2024
DAMO Academy, Alibaba Group, Hangzhou 310023, China.
Fine-resolution land surface phenology (LSP) is urgently required for applications on agriculture management and vegetation-climate interaction, especially over heterogeneous areas, such as agricultural lands and fragmented forests. The critical challenge of fine-resolution LSP monitoring is how to reconstruct the spatiotemporal continuous vegetation index time series. To solve this problem, various data fusion methods have been devised; however, the comprehensive inter-comparison is lacking across different spatial heterogeneity, data quality, and vegetation types.
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