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Datasets for European Green Deal Objective for Sustainable Agriculture: Opportunities and Challenges to Reduce Pesticide Use
No full textThree indicators were used to assess the contribution of EU Member States: (1) use of pesticides per unit of arable land area (kg/ha); (2) the Harmonised Risk Indicator 1; (3) a result indicator from the CAP National Strategic Plans (SP) for 2023–2027 – R.24 “Sustainable and reduced use of pesticides”. This indicator shows the share of utilised agricultural area (UAA) under supported specific commitments which lead to a sustainable use of pesticides in order to reduce risks and impacts of pesticides, such as pesticides leakage. The region examined by the research covers 27 EU Member States: Austria (AT), Belgium (BE), Bulgaria (BG), Croatia (HR), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (ES) and Sweden (SE). In the case of Belgium, there are two CAP SPs for the regions of Wallonia and Flanders; therefore, the forecast indicators were analysed for each region
Public survey data of the research study “Ready for change? Sustainable management of common natural resources”: survey data from 2020 and 2021
No full textOngoing environmental collapse is putting increasing pressure on ecosystems and social communities, particularly, in the regions of Latvia.
Thus, representative survey of Latvia human population has been conducted to assess the societal response to environmental collapse in the context of the social and economic reality in the regions of Latvia.
The survey achieved a sample size of 1015 respondents - residents of the Republic of Latvia aged 18 and older.
The anonymized data set was obtained through a random digit dialing (RDD) method, involving the generation of random combinations of telephone numbers, and conducted through computer-assisted telephone interviews (CATI).
File code_book.xlsx contains the code book of the data set, value_of_variables.xlsx contains the variable values and RfC_Aptaujas_anketa.pdf contains the surve
Efficacy of gonioscopy-assisted transluminal trabeculotomy in different stages of pseudoexfoliative glaucoma: A prospective study
No full textThe data files contain information on patients with pseudoexfoliative glaucoma who participated in a prospective study to compare the efficacy of gonioscopy-assited transluminal trabeculotomy (GATT) between groups with mild to moderate and advanced pseudoexfoliative glaucoma. All patients underwent GATT or GATT in combination with cataract surgery.The data contain information on patient demographics, treatment, and ophthalmological examination results prior to GATT and follow-up visits 12 months after surgery. Data on best corrected visual acuity, visual field, intraocular pressure, number of glaucoma medications, and complications are included for one visit before surgery and seven postoperative visits
Preparation and characterization of the pressed ACB pellets for storage and thermal treatment experiments
No full textProject: Influence of sample handling conditions on radiation-induced effects in biphasic tritium breeding material for future thermonuclear fusion reactors (LU-BA-PG-2024/1-0007). WP-1. Preparation and characterization of the pressed ACB pellets for storage and thermal treatment experiments. DPP link: https://zenodo.org/records/16947437.
In this data set, the obtained results of various physical-chemical methods:
a) powder Xray diffractometry (PXRD), see file WP-1_PXRD_as-received_pebbles.xy;
b) attenuated total reflectance – Fourier transform infrared (ATRFTIR) spectroscopy, see file WP-1_ATR-FTIR_sample_preperation.csv;
c) thermogravimetry/differential scanning calorimetry (TG/DSC), see file WP-1_TG_DSC_as-received_pebbles.csv;
will be summarized for the pressed ACB pellets before storage and thermal treatment experiments
Spatial Dataset of Modified FAO Soil Unit Proportions and Climate Variables for Modelling Climate-Driven Zonal Soil Distribution
No full textThe dataset contains climate and soil data. The climate variable data were obtained from the WorldClim 1.4 database for the period 1965-1978.
The dataset was changed to align seasons in the Northern and Southern hemispheres (process shown in ClimSoil.html, R version 4.3.1). Furthermore, additional variables were calculated and added. The dataset also contains proportions of FAO 1974 soil groups in a 5x5 arc minute resolution cells. The data were obtained from the ISRIC WISE database and used in the study "The effect of climate change on the distribution of zonal soils within the next century" to create models linking climate and soil distribution. The models were then used to project zonal soil distribution at the global scale under climate change
Datasets for European Green Deal Objective: Potential Expansion of Organic Farming Areas
No full textTwo indicators were used to assess the contribution of EU Member States: (1) the share of utilised agricultural area (UAA) under organic farming (%); (2) a result indicator from the CAP National Strategic Plans (SP) for 2023–2027 — R.29 "Development of organic agriculture". This indicator reflects the share of UAA supported by the CAP for organic farming, with a split between maintenance and conversion. The region examined by the research covers 27 EU Member States: Austria (AT), Belgium (BE), Bulgaria (BG), Croatia (HR), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (ES) and Sweden (SE). In the case of Belgium, there are two CAP SPs for the regions of Wallonia and Flanders; therefore, the forecast indicators were analysed for each region
Datasets for Antimicrobial Sales Reduction Potential in the Context of the European Green Deal
No full textTwo indicators were used to assess the contribution of EU Member States: (1) sales of antimicrobials (AMs) in 2022 (mg/PCU) and the rate of change (%) in sales of AMs over the progress period (2018-2022); (2) a result indicator from the CAP National Strategic Plans (SP) for 2023–2027 – R.43 “Limiting antimicrobial use”. This indicator means limiting AMs use and is calculated as a share of livestock units concerned by supported actions to limit the use of AMs (prevention/reduction). The region examined by the research covers 27 EU Member States: Austria (AT), Belgium (BE), Bulgaria (BG), Croatia (HR), Czech Republic (CZ), Cyprus (CY), Denmark (DK), Estonia (EE), Finland (FI), France (FR), Germany (DE), Greece (EL), Hungary (HU), Ireland (IE), Italy (IT), Latvia (LV), Lithuania (LT), Luxembourg (LU), Malta (MT), Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Slovakia (SK), Slovenia (SI), Spain (ES) and Sweden (SE). In the case of Belgium, there are two CAP SPs for the regions of Wallonia and Flanders; therefore, the forecast indicators were analysed for each region
Compression Test of Concrete Reinforced with Oil Shale Ash
No full textThis dataset contains results of compressive strength tests conducted on several concrete mixtures reinforced with oil shale ash (OSA), which is an industrial by-product explored as a sustainable additive for improving concrete performance and reducing environmental impact. The data include averaged compression strength values (in MPa) for different material variants tested under controlled laboratory conditions at Riga Technical University. Each entry represents a test result for a particular material composition and sample number given below.
Concrete A: 0% Oil Shale Ash (by weight) - Material 1 Sample 1-8
Concrete A: 25% Oil Shale Ash (by weight) - Material 2 Sample 1-4
Concrete A: 30% Oil Shale Ash (by weight) - Material 3 Sample 1-3
Concrete B: 0% Oil Shale Ash (by weight) - Material 4 Sample 1-4
Concrete B: 10% Oil Shale Ash (by weight) - Material 5 Sample 1-5
Concrete B: 25% Oil Shale Ash (by weight) - Material 6 Sample 1-4
Concrete B: 30% Oil Shale Ash (by weight) - Material 7 Sample 1-5
Concrete B: 35% Oil Shale Ash (by weight) - Material 8 Sample 1-3
Concrete C: 0% Oil Shale Ash (by weight) - Material 9 Sample 1-6
Concrete C: 10% Oil Shale Ash (by weight) - Material 10 Sample 1-7
Concrete C: 15% Oil Shale Ash (by weight) - Material 11 Sample 1-7
Concrete C: 20% Oil Shale Ash (by weight) - Material 12 Sample 1-7
Concrete C: 25% Oil Shale Ash (by weight) - Material 13 Sample 1-7
Concrete C: 30% Oil Shale Ash (by weight) - Material 14 Sample 1-7
Concrete C: 35% Oil Shale Ash (by weight) - Material 15 Sample 1-
Bee colony temperature dynamics at the day of the swarming event
No full textThe dataset demonstrates bee colony temperature data on the day of the bee colony swarming. Specific day may vary from colony to colony.
The dataset consists of time-series measurements collected from 10 bee colonies, which swarmed during that day. Temperature readings capture thermal regulation inside the hive, which is critical for brood development, colony stability and swarming prediction. It is suitable for applications in ecological research, beekeeping management, and environmental monitoring. Measurements are taken each 1 minute
Scientific literature list on friendship from project "Flourishing for friendship: conceptual research on the interplay between deep friendship and moral development"
No full textThis dataset was collected within the Recovery and resilience Facility project “Internal and external consolidation of the University of Latvia” (No 5.2.1.1.i.0/2/24/I/CFLA/007), grant “Flourishing for friendship: conceptual research on the interplay between deep friendship and moral development” No LU-BA-ZG-2024/1-0028. It contains a curated collection of bibliographic records related to academic research on friendship including 198 units and more than 80 fields derived from reference-management structures (e.g., Item Type, Publication Year, Author(s), Title, Abstract, DOI / ISSN / ISBN, Publisher, Journal, Volume, Issue, Keywords and Notes and Additional metadata fields for classification and reference management)