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Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

Data set with reference scenarios. As it is not possible to include the entire dataset in this report, we only include two Tables on final energy demand. Table 1 shows the Final Energy Demand projections per industrial subsector and EU28 country in the Reference Scenario and Table 2 the Final Energy Demand projections per industrial subsector and EU28 country in the Frozen Efficiency Scenario. The full dataset, including physical production (in ktonnes) and fuel and electricity demand (in TJ) per industrial sub-sector, per fuel type and per EU 28 country is available upon request to the project coordinator.

Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

Input data set for OPHELIA optimisation model investigating optimal heat decarbonization pathways through electrification for net zero economy in Great Britain. 

Anthropogenic structures (e.g. weirs and dams) fragment river networks and restrict the movement of migratory fish. Poor understanding of behavioural response to hydrodynamic cues at structures currently limits the development of effective barrier mitigation measures. This study aimed to assess the effect of flow constriction and associated flow patterns on eel behaviour during downstream migration. In a field experiment, we tracked the movements of 40 tagged adult European eels (Anguilla anguilla) through the forebay of a redundant hydropower intake under two manipulated hydrodynamic treatments. Interrogation of fish trajectories in relation to measured and modelled water velocities provided new insights into behaviour, fundamental for developing passage technologies for this endangered species. Eels rarely followed direct routes through the site. Initially, fish aligned with streamlines near the channel banks and approached the intake semi-passively. A switch to more energetically costly avoidance behaviours occurred on encountering constricted flow, prior to physical contact with structures. Under high water velocity gradients, fish then tended to escape rapidly back upstream, whereas exploratory ‘search’ behaviour was common when acceleration was low. This study highlights the importance of hydrodynamics in informing eel behaviour. This offers potential to develop behavioural guidance, improve fish passage solutions and enhance traditional physical screening. Fish_detections_UL_CHFish positions derived from acoustic telemetry contained within excel file with 5 columns. 'Record' denotes tag detection numbered consecutively in sequence; 'tag_number' denotes the fish identification number; ‘PosX’ denotes fish x coordinate in UTM; ‘PosY’ denotes fish y coordinate in UTM, ‘Treatment’ denotes experimental treatment

# Replication code and data for: Aging in a warming world: global projections of cumulative and acute heat exposure of older adults By Giacomo Falchetta, Enrica De Cian, Ian Sue Wing and Deborah Carr Software requirements: - R v4.3+: https://cran.r-project.org/bin/windows/base/ - RStudio: v2023.06.0+: https://posit.co/download/rstudio-desktop/ - Package dependencies: raster, sf, tidyverse, rasterVis, rgdal, maptools, pbapply, terra, knitr, kableExtra, modelsummary, openxlsx, xtable, ggforce, maptools, weights, spatstat, rworldmap, scales, patchwork, stars, viridis, devtools, stargazer, readxl, nominatimlite, urbnmapr To replicate the analysis: - Clone the replication code repository from https://github.com/giacfalk/aging_climate - Download input data from this Zenodo data repository - Download all the 1km age and gender-stratified global population counts rasters from the following WorldPop page https://hub.worldpop.org/geodata/summary?id=24798 and put them in a subdirectory of the working directory called "AGEPOP" - Run the "project_pop.R" script to generate gridded age-stratified population data for each SSP scenario - Run the "compare_pop_projections.R" file to compare the generated gridded age-stratified population data with an array of pre-existing sources from different countries and produce a summary comparison table (NOTE: before running the script, decompress the "new_comparison_data.zip" folder into the working directory) - Run "projections_exposure_m.R" to quantify heat exposure and generate the figures and tables reported in the paper To process the data and run succesfully, the script requires a computer with at least 32GB RAM. The running time varies based on CPU characteristics, but a runtime of at least 2 hours should be expected to generate all the output data, figures, and tables. All output files are saved in the working directory. Manuscript under peer review. Upon publication, a link to the paper will be made available at this repository. ___ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

We discontinued this version of the dataset.

This dataset contains measurements of downwelling short wave irradiance, measured in a small scale grid setup at Falkenberg: 20 sensors in 4 by 5 grid with a 50 meter grid spacing. Another 4 sensors were placed in all direction about 5 km away from the main grid at Falkenberg. The sampling rate is 10 Hz, to catch all irradiance variability, and is calibrated against a high quality sun tracker. The strength of this dataset is not the absolute accuracy, but rather the spatial measurements and ability to catch variability. Quality: Accuracy is estimated to be within 5% of a conventional pyranometer. Quality varies depending on weather type, but is best for high solar elevation angles (solar noon +/- 4 hours). Data is manually quality controlled, with detailed quality flags included in the dataset. Some anomalous data is not caught, in particular noisy data due to many insects on the sensor or small dirt from birds that reduces the signal slightly. These effects are much smaller than the driving weather patterns. The data is unsuitable for calculating radiation balances, but it is particularly useful for studying variability and patterns of solar irradiance on small scales. Funding: Dutch Research Council (NWO), Shedding Light On Cloud Shadows: VI.Vidi.192.068 Project: FESSTVaL (Field Experiment on submesoscale spatio-temporal variability in Lindenberg), a measurement campaign initiated by the Hans-Ertel-Center for Weather Research.