cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19422320.v1
title: Biogas production by co-digestion of sodium hydroxide pretreated Napier grass and food waste for community sustainability

description: Community agricultural waste-to-energy management, especially in developing countries, can respond to sustainable development goals by the United Nations. Co-digestion techniques for waste from phytomass in fields as Napier grass (NP) and debris from consumption in the community as food waste (FW) into biogas production by conventional anaerobic digestion technology contribute to sustainable energy communities. However, lignocellulose requires proper pretreatment of the material type. Therefore, low sodium hydroxide (NaOH) concentration for Napier grass pretreatment and varying the co-digestion ratio with food waste from the community under conventional batch conditions were optimized to be economically cost-effective with elementary technology. The results showed the highest methane yield at 0.285 m<sup>3</sup>/kg VS<sub>added</sub> at the 4% concentration of sodium hydroxide pretreatment with significant content of FW added with biomass. The best conditions of co-substrates can increase methane yields by up to 3.54 times compared to a single substrate. The energy and cost estimation based on energy consumption and chemical input cost showed that co-digestion with NaOH pretreatment could achieve the net benefits by increasing the biogas production (242 US$/tonne TS). This study confirms the application of waste management in agricultural communities that can be used as fuel in households to increase biogas and economic value. The authors expect this work to be a successful case study for further results that lack government financial support and limitations of advanced technology for a sustainable community.
DOI: 10.5281/zenodo.13834303
title: SPARCS_WP3_Espoo_City_District heating production by fuel in Espoo, Finland

description: District heat production in Espoo, Finland, divided by fuel. Provided by the Helsinki Region Environmental Authority. 2000-2023
DOI: 10.5281/zenodo.13834304
title: SPARCS_WP3_Espoo_City_District heating production by fuel in Espoo, Finland

description: District heat production in Espoo, Finland, divided by fuel. Provided by the Helsinki Region Environmental Authority. 2000-2023
DOI: 10.15468/dl.93mxwa
title: Occurrence Download

description: A dataset containing 1617 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Tragus racemosus (L.) All."
 ]
}

 The dataset includes 1617 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028460-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ag8mjk
title: Occurrence Download

description: A dataset containing 258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Ergaticus versicolor (Salvin, 1863)"
 ]
}

 The dataset includes 258 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028462-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5523/bris.6hu7y9f09t12l1goe5ln0vhz
title: Data from Drewitt et al. RSI 2024

description: This deposit contains the image analysis data, software, and videos of a range of acoustically levitated materials, as reported in Drewitt et al. (2024) "MightyLev: An acoustic levitator for high-temperature containerless processing of medium to high-density materials" in Review of Scientific Instruments.
DOI: 10.5281/zenodo.13834314
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 participants in Smart Otaniemi events

description: Number of participants in Smart Otaniemi, and other related, events completed during SPARCS Work Package 3 (WP3)
DOI: 10.5281/zenodo.13834315
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 participants in Smart Otaniemi events

description: Number of participants in Smart Otaniemi, and other related, events completed during SPARCS Work Package 3 (WP3)
DOI: 10.15468/dl.jq8dx3
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is Solidago shortii Torr. & A.Gray"
 ]
}

 The dataset includes 110 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028463-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.2909/f97c9bdc-3bdc-45e9-8f28-e687702096d7
title: EUNIS coastal habitat types, predicted distribution of habitat suitability - version 1, Nov. 2021

description: This metadata corresponds to the EUNIS Coastal habitat types, predicted distribution of habitat suitability dataset.

Coastal habitats are those above spring high tide limit (or above mean water level in non-tidal waters) occupying coastal features and characterised by their proximity to the sea, including coastal dunes and wooded coastal dunes, beaches and cliffs. Includes free-draining supralittoral habitats adjacent to marine habitats which are normally only very rarely subject to any type of salt water, in as much as they may be inhabited predominantly by terrestrial species, strandlines characterised by terrestrial invertebrates and moist and wet coastal dune slacks and dune-slack pools. Supralittoral sands and wracks may be found also in marine habitats (M). Excludes supralittoral rock pools and habitats, the splash zone immediately above the the mean water line, as well the spray zone and zone subject to sporadic inundation with salt water in as much as it may be inhabited predominantly by marine species, which are included in marine (M).

The modelled suitability for EUNIS coastal habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitability modelling not only climate and soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables, like land use, vegetation height, phenology, and LAI (Leaf Area Index). Because the EBV's are restricted by the extent of the remote sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.
DOI: 10.2909/169b69b5-a1f8-4aed-8042-bfcb4c1e4948
title: EUNIS forest and other wooded land habitat types, predicted distribution of habitat suitability - version 1, Nov. 2021

description: This metadata corresponds to the EUNIS forest and other wooded land habitat types, predicted distribution of habitat suitability dataset. 

The forest and other wooded land habitat type is the land where the dominant vegetation is, or was until very recently, trees with a canopy cover of at least 10%. It includes temporarily unstocked areas due to clear-cutting as part of a forest management practice or natural disasters which are expected to be regenerated within 5 years but does not include land that is predominantly under agricultural or urban land use. Trees are defined as woody plants, typically single-stemmed, that can reach a height of at least 5 m at maturity unless stunted by poor climate or soil. Includes Alnus and Populus swamp forest and riverine Salix forest. Excludes Corylus avellana scrub and Salix and Frangula carrs. Excludes lines of trees, coppices, regularly tilled tree nurseries. Excludes stands of climatically-limited dwarf trees (krummholz) &lt; 3m high, such as occur at the arctic or alpine tree limit which are considered scrub (section S) . Excludes tree stands in agricultural production systems, such as fruit tree plantations, olive orchards and agroforestry systems (dehesa and montado) where crops are grown under tree cover - canopy less than 10%, which are listed under sparsely wooded grasslands. Old plantations which have many of the characteristics of natural or semi-natural forests are included, more intensively managed, and less natural, forests are included in vegetated man-made habitats.

The modelled suitability for EUNIS forest and other wooded land habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitability modelling not only climate and soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables, like land use, vegetation height, phenology, and LAI (Leaf Area Index). Because the EBV's are restricted by the extent of the remote sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.
DOI: 10.2909/70fbb9d1-b61b-4bdc-973b-fec4d8835ccd
title: EUNIS grasslands and lands dominated by forbs, mosses or lichens habitat types, predicted distribution of habitat suitability - version 1, Nov. 2021

description: This metadata corresponds to the EUNIS grasslands and lands dominated by forbs, mosses or lichens habitat types, predicted distribution of habitat suitability dataset.

These habitat types correspond to non-coastal land which is dry or only seasonally wet (with the water table at or above ground level for less than half of the year) with greater than 30% vegetation cover. The vegetation is dominated by grasses and other non-woody plants, including mosses, macrolichens, ferns, sedges and herbs. Includes semiarid steppes with scattered Artemisia scrub. Includes successional weedy vegetation. Excludes regularly tilled habitats (V1) dominated by cultivated herbaceous vegetation such as arable fields and managed grasslands such as recreation fields and lawns.

The modelled suitability for the EUNIS grasslands and lands dominated by forbs, mosses or lichens habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, and LAI (Leave Area Index). Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.
DOI: 10.48597/878g-hz4q
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/jgqh-gf3s
title: Measurement of VOC (hydrocarbons) at Puy de Dôme

description: Measurement of VOC (hydrocarbons) at Puy de Dôme
DOI: 10.48597/tujx-k4ek
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/ycgv-xpyp
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.2909/156377d3-14ee-42f9-855e-71d8c710d441
title: EUNIS heathland, scrub and tundra habitat type, predicted distribution of habitat suitability - version 1, Nov. 2021

description: This metadata corresponds to the EUNIS heathland, scrub and tundra habitat types, predicted distribution of habitat suitability dataset. 

These habitat types correspond to non-coastal land which is dry or only seasonally inundated (with the water table at or above ground level for less than half of the year) with greater than 30% vegetation cover. Tundra is characterised by the presence of permafrost. Heathland and scrub are defined as vegetation dominated by shrubs or dwarf shrubs of species that typically do not exceed 5 m maximum height. Includes shrub orchards, vineyards, hedges (which may have occasional tall trees). Also includes stands of climatically-limited dwarf trees (krummholz) &lt; 3 m high, such as occur in extreme alpine conditions. Includes Salix and Frangula carrs. Excludes coppice (T47) and Alnus and Populus swamp forest (T15).

The modelled suitability for EUNIS heathland, scrub and tundra habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, and LAI (Leave Area Index). Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.
DOI: 10.48597/2xjc-q273
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/57pk-a8yp
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/9q2u-2udg
title: VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/hszz-nkzu
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/2avv-rhpy
title: VOC (hydrocarbons) at Puy de Dôme

description: Measurement of VOC (hydrocarbons) at Puy de Dôme
DOI: 10.48597/5umr-865x
title: Measurement of VOC (hydrocarbons) at Puy de Dôme

description: Measurement of VOC (hydrocarbons) at Puy de Dôme
DOI: 10.48597/x94b-vmz4
title: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory

description: Measurement of VOC (volatile organic compounds) at SIRTA Atmospheric Research Observatory
DOI: 10.48597/zqeq-jsjq
title: Measurement of VOC (hydrocarbons) at Puy de Dôme

description: Measurement of VOC (hydrocarbons) at Puy de Dôme
DOI: 10.5281/zenodo.13834326
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 blockchain key performance indicators in Espoo

description: Key Performance Indicators (KPI's) calculated to assess the blockchain report prepared during the work of SPARCS Work Package 3 (WP3)
DOI: 10.5281/zenodo.13834327
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 blockchain key performance indicators in Espoo

description: Key Performance Indicators (KPI's) calculated to assess the blockchain report prepared during the work of SPARCS Work Package 3 (WP3)
DOI: 10.2909/96b7f7df-3f79-4001-b489-1d918c813a62
title: EUNIS Inland habitats with no or little soil and mostly with sparse vegetation, predicted distribution of habitat suitability - version 1, Nov. 2021

description: This metadata corresponds to the EUNIS Inland habitats with no or little soil and mostly with sparse vegetation, predicted distribution of habitat suitability dataset. 

These habitat types are non-coastal habitats on substrates with no or little development of soil, mostly with less than 30% vegetation cover which are dry or only seasonally wet (with the water table at or above ground level for less than half of the year). Habitats which may have a high vegetation cover include crevices of rocks, screes or cliffs and habitats formed by carpets of moss. Includes subterranean non-marine caves and passages including underground waters and disused underground mines and habitats characterised by the presence of permanent snow and surface ice other than marine ice bodies.

The modelled suitability for EUNIS inland habitats with no or little soil and mostly with sparse vegetation, is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. However, note that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, LAI(Leave Area Index) and Population density. Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.

The Training map files show the modelled suitable distribution, omitting the 10% of occurrence records in the least suitable environment under the assumption that they are not representative of the overall suitable habitat distribution. The 10 percentile training presence is an arbitrary threshold which omits all regions with habitat suitability lower than the suitability values for the lowest 10% of occurrence records.
DOI: 10.15468/dl.9wxm83
title: Occurrence Download

description: A dataset containing 296 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trianthema parvifolium E.Mey."
 ]
}

 The dataset includes 296 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028466-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13834330
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 5G key performance indicators in Espoo

description: Key Performance Indicators (KPI's) calculated to assess the 5G report prepared during the work of SPARCS Work Package 3 (WP3)
DOI: 10.5281/zenodo.13834331
title: SPARCS_WP3_Espoo_City_SPARCS-WP3 5G key performance indicators in Espoo

description: Key Performance Indicators (KPI's) calculated to assess the 5G report prepared during the work of SPARCS Work Package 3 (WP3)
DOI: 10.15468/dl.jkaaj9
title: Occurrence Download

description: A dataset containing 573 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 573 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028470-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kdpfxy
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tribulus pentandrus var. pterophorus (C.Presl) P.Singh & V.Singh"
 ]
}

 The dataset includes 112 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028471-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zyawmn
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Crassostrea virginica (Gmelin, 1791)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is less than or equal to 2023",
 "Country is one of (United States of America)",
 "StateProvince is one of (Georgia)"
 ]
}

 The dataset includes 67 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028472-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6nqwm8
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Uniola paniculata L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is less than or equal to 2023",
 "Country is one of (United States of America)",
 "StateProvince is one of (Georgia)"
 ]
}

 The dataset includes 102 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028473-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tx5m2f
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Balaenoptera brydei Olsen, 1913"
 ]
}

 The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028474-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13834200
title: The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity - dataset

description: Dataset to paper: Błońska E., Jankowiak R., Lasota J., Krzemińska N., Zbyryt A., Ciach M. 2024. The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity. Environmental Science and Pollution Research 31, 2: 2583-2594. https://doi.org/10.1007/s11356-023-31383-x

This study was financially supported by the National Science Centre, Poland (grant no. 2021/41/B/NZ8/03456).
DOI: 10.5281/zenodo.13834201
title: The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity - dataset

description: Dataset to paper: Błońska E., Jankowiak R., Lasota J., Krzemińska N., Zbyryt A., Ciach M. 2024. The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity. Environmental Science and Pollution Research 31, 2: 2583-2594. https://doi.org/10.1007/s11356-023-31383-x

This study was financially supported by the National Science Centre, Poland (grant no. 2021/41/B/NZ8/03456).