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The data in this dataset was collected during the GridFlex Heeten project, as part of Victor Reijnders' PhD project.The data was collected between August 2018 and August 2020 in 77 households all situated in Heeten (The Netherlands) and consists of electricity consumption and gas usage per minute per household. All participating households specified their anonymous data could be used in further research. The data of this project was collected in accordance with a privacy-by-design approach.

Meteo measurements at the Sand Motor. Air temperature, humidity, pressure, solar radiation, precipitation, wind speed and wind direction are measured. Contributor: Verheijen, A.H. (Anne) [orcid:0000-0002-2131-7619]

As part of global efforts to reduce dependence on carbon-based energy sources there has been a rapid increase in the installation of renewable energy devices. The installation and operation of these devices can result in conflicts with wildlife. In the marine environment, mammals may avoid wind farms that are under construction or operating. Such avoidance may lead to more time spent travelling or displacement from key habitats. A paucity of data on at-sea movements of marine mammals around wind farms limits our understanding of the nature of their potential impacts. Here, we present the results of a telemetry study on harbour seals Phoca vitulina in The Wash, south-east England, an area where wind farms are being constructed using impact pile driving. We investigated whether seals avoid wind farms during operation, construction in its entirety, or during piling activity. The study was carried out using historical telemetry data collected prior to any wind farm development and telemetry data collected in 2012 during the construction of one wind farm and the operation of another. Within an operational wind farm, there was a close-to-significant increase in seal usage compared to prior to wind farm development. However, the wind farm was at the edge of a large area of increased usage, so the presence of the wind farm was unlikely to be the cause. There was no significant displacement during construction as a whole. However, during piling, seal usage (abundance) was significantly reduced up to 25 km from the piling activity; within 25 km of the centre of the wind farm, there was a 19 to 83% (95% confidence intervals) decrease in usage compared to during breaks in piling, equating to a mean estimated displacement of 440 individuals. This amounts to significant displacement starting from predicted received levels of between 166 and 178 dB re 1 μPa(p-p). Displacement was limited to piling activity; within 2 h of cessation of pile driving, seals were distributed as per the non-piling scenario. Synthesis and applications. Our spatial and temporal quantification of avoidance of wind farms by harbour seals is critical to reduce uncertainty and increase robustness in environmental impact assessments of future developments. Specifically, the results will allow policymakers to produce industry guidance on the likelihood of displacement of seals in response to pile driving; the relationship between sound levels and avoidance rates; and the duration of any avoidance, thus allowing far more accurate environmental assessments to be carried out during the consenting process. Further, our results can be used to inform mitigation strategies in terms of both the sound levels likely to cause displacement and what temporal patterns of piling would minimize the magnitude of the energetic impacts of displacement. Wash_diagWash_diag.xlsx is the historic location data (pre windfarm construction) for the 19 individuals used in the analysis described in Russell et al.

Study data and figure results.

This data publication contains research data associated with the European Union's Horizon 2020 REFLECT project which aims to obtain data relevant to the production of geothermal waters at extreme conditions. Results given here are part of REFLECT deliverable 2.2: Report on gas solubility and degassing kinetic (type C). A link to the deliverables of this project is given below as reference. It contains experimental results from the degassing process of CO2-water mixtures at conditions relevant to the production of geothermal waters with a specific focus on high salinity fluids.

This research evaluates the current carbon footprint of vertical farming systems by comparing the impact of one kilogram of butterhead lettuce produced in an operational vertical farm to that of conventional open-field farming (OF), soil-based greenhouse cultivation (GH(s)) and hydroponic greenhouse cultivation (GH(h)) in the Netherlands. A typical farm is defined for OF, GH(s) and GH(h) in the Netherlands, based on existing databases. It is not yet possible to define a typical vertical farm (VF) due to the breadth of approaches. Therefore, an operational vertical farm was used as a case study. Within the dataset the baseline activity data has been collected within the tabs ‘OF’, ‘GH(s)’, GH(h) and ‘VF’. The carbon footprint of each case study was calculated by accounting for all the GHG emissions from activities within the system boundaries, from cradle-to-grave, for the life cycle of both the crop and the farm. These GHG emissions were calculated as follows: CO₂-eq = activity data x EF, where CO2-eq is the carbon footprint of the activity in kg CO2-eq, and EF is the emission factor of the activity in kg CO₂-eq per unit of the activity data, assessed by referring to the IPCC GWP100a characterisation method in SimaPro 9.0.0, which is based on the Ecoinvent 3.6 database. Tab ‘EF’ provides an overview of the emissions factor sources used for activities within the study. Country-specific emission factors for the Netherlands were used for natural gas and electricity consumption to reflect the correct energy mix. By combining the collected activity data with the EFs, the carbon footprints of each farming system were calculated within the tabs ‘FIG04’ and ‘FIG05’. Three scenarios were created to improve the comparability of the baseline data as well as present potential carbon savings as a result of transitioning to renewable energy, which included: the lost carbon sequestration potential as a result of land-use change (FIG06), assuming identical sales packaging for all farming systems (FIG07, FIG08, FIG09), and a transition to renewable energy (FIG10). These scenarios, when considered collectively, greatly reduced the disparity between the carbon footprints of the three farming systems (FIG11 and FIG12). Electricity use represented the largest share in the carbon fooptrint of both baseline and alternative scenario, therefore, the electricity consumption of the VF was compared to that of other VF from literature in the tabs ‘FIG13’ and ‘FIG14’.

Many species are too slow to track their poleward moving climate niche under global warming. Pesticide exposure may contribute to this by reducing population growth and impairing flight ability. Moreover, edge populations at the moving range front may be more vulnerable to pesticides because of the rapid evolution of traits to enhance their rate of spread that shunt energy away from detoxification and repair. We exposed replicated edge and core populations of the poleward moving damselfly Coenagrion scitulum to the pesticide esfenvalerate at low and high densities. Exposure to esfenvalerate had strong negative effects on survival, growth rate and development time in the larval stage and negatively affected flight-related adult traits (mass at emergence, flight muscle mass and fat content) across metamorphosis. Pesticide effects did not differ between edge and core populations, except that at the high concentration the pesticide-induced mortality was 17% stronger in edge populations. Pesticide exposure may therefore slow down the range expansion by lowering population growth rates, especially because edge populations suffered a higher mortality, and by negatively affecting dispersal ability by impairing flight-related traits. These results emphasize the need for direct conservation efforts toward leading-edge populations for facilitating future range shifts under global warming. MAIN DATAEVA-2015-167-OA DATA.xlsSUPPLEMENTARY DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS)EVA-2015-167-OA DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS).xls

First, this data complies CO2 emissions, final energy consumption, GDP, share of zero emitting electricity for Annex B countries of Kyoto Protocol and east state in U.S. Second, this data also complies all the CDM projects and monitoring reports until the end of the first commitment period of the Kyoto Protocol. The all the projects complies the result of additonality assessment.