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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.

Seeds of 52 species of herbaceous plants typical from European grassland ecosystems were obtained from a commercial supplier (Planta naturalis). When species germinated in Petri dishes the seedlings were then transplanted to plastic pots (11 x 11 x 12 cm height, 1L volume). Pots were filled with a mixture of a potting substrate (Biolan Murumuld) and sand. Pots were randomly placed in the greenhouse of the University of Tartu, Estonia. Then, we established monocultures with seven individuals of a single species per pot which were grown under well-watered conditions. One month after transplanting the seedlings to the pots, a drought treatment was applied to half of the pots (five pots per species). The experiment was harvested in late July 2020, when the first individuals started flowering, after month-long drought treatment. Plant traits related to drought responses and resource use strategies were selected and measured for each species following established protocols. These included seven above- and belowground traits: Vegetative plant height (H, cm), Leaf Area (LA, mm2), Specific Leaf Area (SLA, mm2 mg-1), Leaf Dry Matter Content (LDMC, mg g-1), Specific Root Length (SRL, cm g-1), Average root Diameter (AvgD, mm), Root Dry Matter Content (RDMC, mg g-1). Before harvesting, we measured the plant height and collected one leaf per individual for three individuals per pot. Afterward, we collected the aboveground biomass and belowground biomass of all the individuals in each pot. Due to the difficulty in untangling the roots of the different individuals in a pot, root traits were estimated at the pot level. Roots were washed and a sample of finest roots (10-50mg) was collected. Leaves and fine roots were scanned at 300dpi and 600dpi, respectively, using an Epson perfection 3200 Photo scanner for leaves and Epson V700 Photo scanner for fine roots. After scanning, leaves and roots were oven-dried at 60°C for 72h. AvgD and root length were determined using WinRHIZO Pro 2015 (Regent Instruments Inc., Canada), and leaf area with ImageJ software. We averaged all traits values at the species level, attaining a single value for each trait in each treatment. The total aboveground biomass and total belowground biomass of each pot were oven-dried at 60°C for 72h and weighed. Drought is expected to increase in future climate scenarios. Although responses to drought of individual functional traits are relatively well-known, simultaneous changes across multiple traits in response to water scarcity remain poorly understood despite its importance to understand alternative strategies to resist drought. We grew 52 herbaceous species in monocultures under drought and control treatments and characterized the functional space using seven measured above- and belowground traits: plant height, leaf area, specific leaf area, leaf dry matter content, specific root length, average root diameter, and root dry matter content. Then, we estimated how each species occupied this space and the amount of functional space occupied in both treatments using trait probability density functions. We also estimated intraspecific trait variability (ITV) for each species as the dissimilarity in trait values between the individuals of each treatment. We then mapped drought resistance and ITV in the functional space using generalized additive models. The response of species to drought strongly depended on their traits, with species that invested more in root tissues and conserved small size being both more resistant to drought and having higher ITV. We also observed a significant trend of trait displacement towards less conservative strategies. However, these changes depended strongly on the trait values of species in the control treatment, with species with different traits having opposing responses to drought. These contrasting responses resulted in lower trait variability in the species pool in drought compared to control conditions. Our results suggest strong trait filtering acting on conservative species as well as the existence of an optimal part in the functional space to which species converge under drought. Our results show that changes in species trait-space occupancy are key to understand plant strategies to withstand drought, highlighting the importance of individual variation in response to environmental changes, and suggest that community-wide functional diversity and biomass productivity could decrease in a drier future. Knowing these shifts will help to anticipate changes in ecosystem functioning facing climate change. The complete dataset is in the file.

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2021. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

In summer 2020 the energy company St1 carried out its second stimulation of deep geothermal wells in Otaniemi, Espoo, in the Helsinki metropolitan area, southern Finland. Institute of Seismology of University of Helsinki (ISUH) monitored the induced seismicity during the stimulation, and also months before and after it. In the second half of 2022 ISUH consulted the Australian company Institute of Mine Seismology (IMS, https://www.imseismology.org) for providing an automatic phase picking on the ISUH 2020 event and waveform data catalogue (doi:10.23729/cdfd937c-37d5-46b0-9c16-f6e0c10bc81f) using an algorithm based on machine learning (doi: 10.1785/0220210068). The dataset provided by IMS was later transferred to formats used by ISUH. The resulting dataset comprises of phase pickings and relevant waveforms of 85 induced earthquakes that occurred between 8 March 2020 to 8 December, 2020, with local magnitudes between -1.1 and 1.4. Note that the event location and other metadata of the resulting dataset are still based on the ISUH 2020 catalogue in order to preserve the consistency within the dataset as some events did not have enough automatic phase picks for reliable relocation. Waveform, location and timing data have been produced at ISUH using seismic stations of the Finnish National Seismic Network (doi: 10.14470/UR044600) including the Helsinki local broadband network, the temporary HEL broadband network in Helsinki and Espoo, the temporary borehole network of St1 (doi: 10.1785/0220190253), and a pool of lightweight mobile seismic instruments operated by ISUH (GIPP data cubes, doi: 10.5880/GIPP.201925.1; SmartSolos and Refteks, doi: 10.1785/0220210195). The deployment is described in Rintamäki et al., 2021, A Seismic Network to Monitor the 2020 EGS Stimulation in the Espoo/Helsinki Area, Southern Finland, doi:10.1785/0220210195. Event data, event metadata, and station metadata are provided in distinct directories, and for event data, each event is assigned a subdirectory. Data formats follow generally accepted seismological standards.

The analyses of future climate change over South Africa as described in the Third National Communication, are from the projections of the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Assessment Report (AR) 5 of the Intergovernmental Panel on Climate Change (IPCC). These projections are used to inform on the uncertainty range of the large-scale climate change futures over the southern African region. At the Council for Scientific Industrial Research (CSIR), a dynamic regional climate model CCAM (conformal-cubic atmospheric model) of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) was used to downscale CMIP5 CGCM projections to 50 km resolution over Africa. These downscalings were for both Representative Concentration Pathway (RCP) 8.5 and Representative Concentration Pathway (RCP) 4.5 of AR5 of the IPCC. RCP 4.5 describes a future with relatively ambitious emission reductions whereas RCP 8.5 describes a future with no reductions in emissions. Emissions in RCP 4.5 peak around 2040, then decline and in RCP 8.5 emissions continue to rise throughout the 21st century. The change in temperature is expressed as an anomaly, the difference between the average climate over a period of the last several decades (1971-2000), and the projected climate (short to medium term 2021 to 2050). The simulations were performed on supercomputers of the CSIRO and on the Centre for High Performance Computing (CHPC) of the Meraka Institute of the CSIR in South Africa.

CO2 refrigeration systems, as used e.g. for supermarket applications, often encounter a drastical decrease of COP when operation moves into a transcritical mode. There are several options to enhance the system efficiency to reduce this penalty. All of them influence the optimum value for discharge and intermediate pressure. This paper discusses these influences for parallel compression and for an additional booster compressor. For comparison a system simulation was performed. The compressor model in the simulation is based on a data map of a currently available compressor. As a result the system’s efficiency improvement potential of both methods is presented under consideration of optimized operation conditions.

Additional file 2. Detailed list of failure modes.

We simulated an experimental summer storm in large-volume (~1200 m3, ~16m depth) enclosures in Lake Stechlin (https://www.lake-lab.de) by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Size-fractionated Bacterial Protein Production (BPP) of particle associated (PA, >3.0 µm) and free-living bacteria (FL, 0.2-3.0 µm) (14C-Leu incorporation) as well as abundances of PA (microscopy of DAPI stained cells on 3.0 µm polycarbonate filters) and FL heterotrophic prokaryotes and picocyanobacteria (flow cytometry of SYBR green I stained cells) were monitored for 42 days after the experimental disturbance event. Mixing increased bacterial abundance and production about 3 weeks after mixing, which was associated to a mixing-induced stimulation of phytoplankton growth in the mixed enclosures compared to the controls. Simultaneously, decreased abundances of picocyanobacteria could be observed in mixed enclosures. Empty cells = NAFurther Project information: Core Facility grant; Award: GE 1775/2-1

A global dataset of steam-electric power generating units with location, technical information, performance characteristics and associated environmental stressors (GHG emissions, freshwater consumption, thermal emissions to freshwater) as well as stressor intensities (per GJ el. produced).