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ABSTRACT The progression of the organic loading rate (OLR) up to a certain limit increases biogas production. The limit and operation range vary according to the configuration of the reactor and are associated with other variables that generate different results with respect to biogas yield (BY) and biogas productiveness (BP). The aim of this study was to investigate the effect of the OLR on the BY and BP from swine manure in continuous stirred tank reactors (CSTRs) and upflow anaerobic sludge blanket reactors (UASBs). In the assay with the CSTR, the best operational condition was at an OLR of 0.7 gVS add L−1 reactor d−1 and a hydraulic retention time (HRT) of 18 days. At this operational condition, 0.8 LN biogas gVS add−1 of BY and 0.6 LN biogas L−1 reactor d−1 of BP were obtained. In the assay with the UASB, the best operational condition was at an OLR of 2.2 gVS add L−1 reactor d−1 and an HRT of two days, and 0.7 LN biogas gvs add−1 of BY and 1.6 LN biogas L−1 reactor d−1 of BP were obtained. The results demonstrate the effects of OLR changes on the biogas production in the CSTR and UASB, avoiding the underutilization or overloading of such equipment and enabling collaboration in projects for power generation from biogas in swine farms.

This climate change impact data (future scenarios on temperature-induced GDP losses) and climate change mitigation cost data (REMIND model scenarios) is published under doi: 10.5281/zenodo.3541809 and used in this paper: Ueckerdt F, Frieler K, Lange S, Wenz L, Luderer G, Levermann A (2018) The economically optimal warming limit of the planet. Earth System Dynamics. https://doi.org/10.5194/esd-10-741-2019 Below the individual file contents are explained. For further questions feel free to write to Falko Ueckerdt (ueckerdt@pik-potsdam.de). Climate change impact data File 1: Data_rel-GDPpercapita-changes_withCC_per-country_all-RCP_all-SSP_4GCM.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, RCP (and a zero-emissions scenario), SSP and 4 GCMs (spanning a broad range of climate sensitivity). Negative (positive) values indicate losses (gains) due to climate change. For figure 1a of the paper, this data was aggregated for all countries. File 2: Data_rel-GDPpercapita-changes_withCC_per-country_all-SSP_4GCM_interpolated-for-REMIND-scenarios.csv Content: Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP and 4 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). File 3: Data_rel-GDPpercapita-changes_withCC_per-country_SSP2_12GCM_interpolated-for-REMIND-scenarios.csv Content: Same as file 2, but only for the SSP2 (chosen default scenario for the study) and for all 12 GCMs. Data of relative change in absolute GDP/CAP levels (compared to the baseline path of the respective SSP in the SSP database) for each country, SSP-2 and 12 GCMs (spanning a broad range of climate sensitivity). The RCP (and a zero-emissions scenario) are interpolated to the temperature pathways of the ten REMIND model scenarios used for climate change mitigation costs. Hereby the set of scenarios for climate impacts and climate change mitigation are consistent and can be combined to total costs of climate change (for a broad range of mitigation action). In addition, reference GDP and population data (without climate change) for each country until 2100 was downloaded from the SSP database, release Version 1.0 (March 2013, https://tntcat.iiasa.ac.at/SspDb/, last accessed 15Nov 2019). Climate change mitigation cost data The scenario design and runs used in this paper have first been conducted in [1] and later also used in [2]. File 4: REMIND_scenario_results_economic_data.csv File 5: REMIND_scenarios_climate_data.csv Content: A broad range of climate change mitigation scenarios of the REMIND model. File 4 contains the economic data of e.g. GDP and macro-economic consumption for each of the countries and world regions, as well as GHG emissions from various economic sectors. File 5 contains the global climate-related data, e.g. forcing, concentration, temperature. In the scenario description “FFrunxxx” (column 2), the code “xxx” specifies the scenario as follows. See [1] for a detailed discussion of the scenarios. The first dimension specifies the climate policy regime (delayed action, baseline scenarios): 1xx: climate action from 2010 5xx: climate action from 2015 2xx climate action from 2020 (used in this study) 3xx climate action from 2030 4x1 weak policy baseline (before Paris agreement) The second dimension specifies the technology portfolio and assumptions: x1x Full technology portfolio (used in this study) x2x noCCS: unavailability of CCS x3x lowEI: lower energy intensity, with final energy demand per economic output decreasing faster than historically observed x4x NucPO: phase out of investments into nuclear energy x5x Limited SW: penetration of solar and wind power limited x6x Limited Bio: reduced bioenergy potential p.a. (100 EJ compared to 300 EJ in all other cases) x6x noBECCS: unavailability of CCS in combination with bioenergy The third dimension specifies the climate change mitigation ambition level, i.e. the height of a global CO2 tax in 2020 (which increases with 5% p.a.). xx1 0$/tCO2 (baseline) xx2 10$/tCO2 xx3 30$/tCO2 xx4 50$/tCO2 xx5 100$/tCO2 xx6 200$/tCO2 xx7 500$/tCO2 xx8 40$/tCO2 xx9 20$/tCO2 xx0 5$/tCO2 For figure 1b of the paper, this data was aggregated for all countries and regions. Relative changes of GDP are calculated relative to the baseline (4x1 with zero carbon price). [1] Luderer, G., Pietzcker, R. C., Bertram, C., Kriegler, E., Meinshausen, M. and Edenhofer, O.: Economic mitigation challenges: how further delay closes the door for achieving climate targets, Environmental Research Letters, 8(3), 034033, doi:10.1088/1748-9326/8/3/034033, 2013a. [2] Rogelj, J., Luderer, G., Pietzcker, R. C., Kriegler, E., Schaeffer, M., Krey, V. and Riahi, K.: Energy system transformations for limiting end-of-century warming to below 1.5 °C, Nature Climate Change, 5(6), 519–527, doi:10.1038/nclimate2572, 2015.

Biodiesel, known as a mixture of fatty acid ethyl/methyl esters, is seen as an alternative, ecofriendly, biodegradable and renewable non-fossil fuel. The use of heterogeneous catalysts for biodiesel synthesis can solve several problems associated with the homogeneous alkaline catalyzed-transesterification. Therefore, this work reports the evaluation of the commercial resin Amberlyst A26OH, a strong anion exchange resin, as a heterogeneous catalyst for the batch transesterification of refined palm olein with ethanol. It was studied the effects of the main operational parameters, considering the molar ratio of the reaction mixture (MRRM), namely the molar ratio of ethanol to olein taking into account only the ethanol added to the reaction system, and the total molar ratio (TMR), in this case considering also the amount of ethanol carried by the resin after its pretreatment. It was determined an optimal range of operational conditions by response surface methodology, guaranteeing conversion to ethyl esters higher than 96% with a catalyst amount corresponding to a range from 10.4 to 11.4% of the oil quantity, a temperature within the range of 55 to 60 ºC and a MRRM within the range from 3.5:1 to 6.0:1.

This dataset contains global raster maps to calculate particulate matter life cycle impacts from primary fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3) emissions. It also includes the R source code to reproduce these maps, a case study on the particulate matter health impacts of global coal power generation, and aggregated characterization factor tables for several spatial resolutions that are commonly used in life cycle assessment (LCA) (for example in the ecoinvent life cycle inventory (LCI) database).

Plot design and harvesting Twelve sampling plots (16 m × 16 m) in three P. deltoides plantations were established based on systematic random design. To minimize edge effects, surrounding rows were not considered during sampling. The age of the stands was 18-20 years old. In each sampling plot, the DBH (diameter at breast height 1.3 m above the ground) of the individual trees was measured with a caliper in two perpendicular directions and the mean DBH determined. Tree height was measured by Haglöf-Vertex IV hypsometer. Based on the DBH and height measurements, 10 DBH classes from 15 to 42 cm (3 cm intervals) were established. The value of each DBH class represented the central value (i.e., class 15 included all DBH from 12.5 to 17.5 cm). In each DBH class, one representative tree was selected and harvested for a total of 10 P. deltoides trees. Measurements of bark percentagesThe stems of harvested trees were marked and cut into 2 m-segments. The mid-length diameter of each segment was measured outside the bark in two perpendicular directions with a caliper to determine the mean diameter. A 5 cm-thick disc was cut from the middle of each segment. A total of 123 discs were obtained and brought to the laboratory. All the discs were arranged into 2-cm wide diameter classes. The value of each disc class represents the central value (i.e., class 20 included all discs whose diameters ranged from 19.5 to 20.5 cm). Bark was separated from the wood using a peeler knife for each disc. Fresh bark and wood were weighted separately, oven-dried at 80 °C until constant weight, and the oven-dry weight measured. The bark percentage of each disc was considered as bark percentage of a 2 m-segment for fresh and dry weight. Finally, the bark percentage of the whole stem in each DBH class was calculated by adding the 2 m-segments. Bark biomass as an energy source has a high economic value. Bark content variations and production helps recognize the potential of this bioenergy source spatially before harvesting. The percentage of fresh and dry bark in Populus deltoides grown under a monoculture system was examined in the temperate region of northern Iran. Diameter at breast height (DBH) and total height data were analyzed based on an initial inventory. Ten sample trees were felled, separated into 2 m-segments, and weighted in the field. A 5-cm-thick disc from each segment was extracted for determining fresh and dry bark percentages. These were statistically significantly different in disc diameter classes and decreased with increasing disc diameters. Bark percentage of the disc classes ranged from 21.8 to 24.4% in small-sized diameters to 8.1‒9.3% in large-sized diameters. The differences between fresh and dry bark percentages depended on water content variations. Allometric power equations were fitted to data of fresh and dry bark percentages and disc diameters as well as DBH. The values of R2 ranged from 0.89 to 0.90. In addition, allometric power equations provided the best fits for relationships between total stem dry biomass, dry bark biomass, and DBH, R2 = 0.986 and 0.979 for the total stem dry biomass and stem dry bark biomass, respectively. The allometric models can be used to estimate bark percentage and bark production of P. deltoides in segments and for the whole stem for a wide range of segment diameters (8‒44 cm) and DBH (15‒45 cm).

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.

The dataset originates from microgrid platform (MGP, https://www.microgrid-qehna.com/) located in QehnA lab (https://www.qehna.com/) of the National School of Engineers of Tunis (ENIT) and serves as a testbed for various energy-related studies. The platform includes two microgrids, namely Pla-NeTE and SMARTNESS. Pla-NeTE, which stands for Platform for investigations of New Technologies of the Energy is a microgrid platform, designed for the investigation of new energy technologies in the case of massive residential photovoltaics integration and its impact on the distribution network. On the other hand, SMARTNESS, which stands for Smart Micro-grid plAtfoRm wiTh aN Energy SyStem, is a laboratory-scale microgrid designed for the exploration of emerging energy technologies and associated concepts such as collective self-consumption and energy management systems. Both microgrids are connected to the low-voltage distribution network. The dataset comprises samples of electrical data collected from the microgrid platform. It offers a valuable resource for researchers and analysts to study real-world electrical data and gain insights into the microgrid's performance, encompassing aspects such as energy consumption, renewable energy generation, and energy storage systems while considering residential microgrid in Tunisia. The dataset primarily consists of electrical data samples recorded from both microgrids while considering different operating conditions. It provides a granular view of the microgrids’ real-time electrical performance according to given test procedure. This dataset does not encompass detailed information about the microgrid's physical structure or components, but these later can be found in the related publications. Researchers can use this data to analyse the microgrids’ operational patterns and performance in the context of electrical energy management. The dataset's applicability extends to various research areas, including residential load management, renewable energy integration, and power quality improvement.

Operating measurements from three multi-week test campaigns of the natural circulation FLiBe loop. This system is investigating thermal hydraulic behavior of the molten salt BeF_2 -LiF (33 - 67 mol %). The system behaves in a stable fashion, but shows unusual local transients, such as flow break-down in the riser and thermal jumps at the cooler exit. Heat transfer shows promising trends that FLiBe will behave as a normal heat transfer fluid, as long as salt purity can be maintained. The most recent test shows heat transfer degradation that is likely a result of oxides and impurities. The data archive contains as-built dimensions, Matlab analysis codes, and the raw data files.