Resultados de investigación

Dataset associated with the published article entitled: Use of Genus Cistus in Phytotechnologies: Application in a Closed Mercury Mine

This data set includes 16 files corresponding to the paper with doi:10.1016/j.mechmachtheory.2022.105115 plus a readme.txt file., This dataset is part of the research project PID2020-116107GB-I00 funded by MCIN/AEI/10.13039/501100011033

This dataset corresponds to yield, price and fuel consumption from organic rainfed almond orchards in SE Spain under different diversification and tillage practices. The objective is to carry out an integrated environmental (focused on the CO2 emissions) and economic assessment of farm operations under different diversification and tillage practices through a cradle-to-farm gate life cycle assessment (LCA) based on these data. These data correspond to the open-access article "Carbon emissions and economic assessment of farm operations under different tillage practices in organic rainfed almond orchards under semiarid Mediterranean conditions" published in Scientia Horticulturae. (https://doi.org/10.1016/j.scienta.2019.108978), funded by the European Commission Horizon 2020 project Diverfarming [grant agreement 728003].

Crop yield data, auxiliary data and methods metadata from a mandarin crop studied in Diverfarming project.

This dataset contains the results of a parametric mesh study to quantify the discretization uncertainty of steady state multi-reference frame simulations on a counter rotating pico-hydraulic turbine reference case [1][2]. The results of this study were used in the published article [3] for numerical validation purposes. The mesh was made with open-source tool Salome-Platform for the bulk domains and Ansys Turbogrid® for the blade row domains. The simulations where made with OpenFoamV8 open-source library. Three meshes where evaluated, taking in account an effective size ratio r=1.4 (eq. 1). The results where analyzed using the Roache's convergence index, obtaining for the medium mesh about 2% of discretization uncertainty on the total power, and less than 1% on pressure head. Additional simulations where made with the medium mesh to reconstruct the hydraulic efficiency curve. Main simulation results folders: picoTurbineValCase/sim/results/MS[0-2] contains the mesh study simulation results picoTurbineValCase/sim/results/curve contains the off-design simulation results On the meshStudy.org file a summary of the calculations is given.

This data set contains information from a choice experiment survey developed to value the socio-economic benefits of intercropping practices in Mediterranean agroecosystems. These data correspond to the open-access article "Valuing diversification benefits through intercropping in Mediterranean agroecosystems: A choice experiment approach" published in Ecological Economics. (https://doi.org/10.1016/j.ecolecon.2020.106593), funded by he European Commission Horizon 2020 project Diverfarming [grant agreement 728003].

Gas, erosion, runoff and soil data and metadata of the different cases studies and long terms from WP5 "Environmental impact and delivery of ecosystem services by crop diversification", derived from H2020 Diverfarming project. This workpackage has been designed to provide sound and robust scientific understanding of the benefits and drawbacks of the tailored diversified cropping systems for improvement of the environmental quality and delivery of ecosystem services in each pedoclimatic region. http://www.diverfarming.eu.

The collected Dataset presents a data collection based on Bluetooth Low Energy (BLE) technology and the use of smartphones for the purposes of vehicle localization and tracking. The system is based on a two-dimensional 8 switched-beam directive panel antennas mounted on an electronic toll collection (ETC) gateway. The multibeam antenna topology is installed on the ETC at a height of 4.7 m and the data collected from several experiments, together with the set-up and methodology, are reported here. The data collection can be divided into two main sections. First, the system was calibrated in an 8 x 8 meter area below the ETC. The distance between adjacent test points is 0.5 m, with a total of 100 samples measured for each test point in every 8 switched-beam panel antenna. Secondly, the results of dynamic test with vehicles passing at different speeds carrying smartphones and using BLE are detailed. As a validation of the dataset, a benchmark analysis for data visualization and localization/tracking estimation applying MUltiple SIgnal Classification and fingerprinting algorithms is included.

The consumption stage has been identified as the largest producer of food waste (FW) across the food supply chain (FSC), with fruit and vegetables being the most affected product category. The present study aims to determine the op- timal storage scenario at household level to avoid food waste and which has the lowest environmental footprint. Broc- coli was stored under different storage conditions: unbagged or bagged (periodically opened) in bioplastic bags inside a domestic refrigerator at 5 or 7 °C for 34 days and then analysed for relative humidity (RH), sensory properties and bioactive compounds. A life cycle assessment (LCA) was conducted to evaluate the environmental profile of 1 kg of broccoli purchased by the consumer (cradle-to-grave). At day 0 (base scenario) the carbon footprint was 0.81 kg CO2 eq/kg, with the vegetable farming being the main contributor to this environmental impact, mostly driven by fertiliser (production and its emissions to air and water) and irrigation (due to electricity consumption for water pumping). Quality and food waste depended on time and storage conditions: For short storage times, within three days, the best quality combined with the lowest environmental footprint was for unbagged broccoli at 7 °C and no household food waste. However, this scenario had the highest food waste level from day 3 onwards, with increased resource loss and overall environmental footprint. For long-term storage, using a bag and storing at 5 °C helped to re- duce food waste with the lowest environmental footprint. For example, at 16 days, this scenario (bagged at 5 °C) could save 4.63 kg/FU ofbroccoli and 3.16 kg CO2 eq/FU compared to the worst scenario (unbagged at 7 °C). Consumers are the key to reducing household food waste and this research provides the knowledge for improvement.