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CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

Abstract Activated carbon is commonly used as a material for contaminant-adsorption processes in aqueous systems. However, its use is more restricted to charcoal than to coal, for the most part, in view of the fact of the higher cost (~ 40%) if the mineral is a fossil fuel which needs to be extracted from the earth by mining. For this reason, the peach stone that comes from alimentary industrial tailings can be a good choice for the separation of pollutants from aqueous suspensions and other soluble substances. The purpose of this research was the development of a low-cost filter, using stones to remove atrazine from water. Appraisal and characterization studies were performed along with batch experiments to investigate dosing effects of the activated carbon, atrazine concentration, contact time, and adsorption pH on removal procedures. From the results of the experiment, an excellent removal of the analyte in question was observed under conditions that can be considered as close as possible to the environment, such as pH = 6.5, room temperature and 10 minutes of agitation time, always choosing the best alternative with the lowest cost of energy and time. Batch system application has been recommended as versatile for utilization in seasonal problems such as pesticide contamination.

Πρόκειται για τη συλλογή των γεωμετριών των δασικών περιοχών που βρίσκονται στο έδαφος της περιφέρειας Friuli Venezia Giulia. Οι περισσότερες από αυτές τις περιοχές καταλαμβάνονται από δάση, όπως ορίζονται στον περιφερειακό νόμο για τα δάση (αριθ. 9/2007). Οι γεωμετρίες προέρχονται από δύο διαφορετικές βάσεις δεδομένων: «Τύποι Forestali 1998», που επικαιροποιήθηκαν το 2010 και «Ολοκλήρωση του ΣΓΠ των τύπων δασών Friuli Venezia Giulia» που πραγματοποιήθηκαν το 2011 και επικυρώθηκαν οριστικά το 2013. Is é an bailiúchán de geometries na limistéar foraoise atá suite i gcríoch Réigiún Friuli Venezia Giulia. Tá an chuid is mó de na limistéir sin á n-áitiú ag foraoisí mar a shainítear leis an Dlí Réigiúnach Foraoise (Uimh.9/2007). Tagann na geoiméadrachtaí ó dhá bhunachar sonraí éagsúla: “Cineálacha Forestali 1998”, a tugadh cothrom le dáta in 2010 agus “Comhlánú GIS de Chineálacha Foraoise Friuli Venezia Giulia” a rinneadh in 2011 agus a bailíochtaíodh go cinntitheach in 2013. Es la colección de las geometrías de las zonas forestales ubicadas en el territorio de la región de Friuli Venezia Giulia. La mayor parte de estas zonas están ocupadas por bosques tal como se definen en la Ley Forestal Regional (N.º9/2007). Las geometrías provienen de dos geodatabases diferentes: «Tipos Forestali 1998», actualizado en 2010 y «Completación del SIG de los tipos forestales de Friuli Venezia Giulia», llevado a cabo en 2011 y validado definitivamente en 2013. Il s’agit de la collection des géométries des zones forestières situées sur le territoire de la région du Frioul-Vénétie Giulia. La plupart de ces zones sont occupées par des forêts telles que définies par la loi forestière régionale (No.9/2007). Les géométries proviennent de deux bases de données différentes: «Types Forestali 1998», mis à jour en 2010 et «Achevée du SIG des types forestiers du Frioul Venezia Giulia» réalisée en 2011 et validée définitivement en 2013. Costituisce la raccolta delle geometrie delle aree forestali situate nel territorio della Regione Friuli Venezia Giulia. In buona parte si tratta di superfici occupate da boschi così come definiti dalla vigente legge forestale regionale (n.9/2007). Le geometrie provengono da due diversi geodatabase: "Tipi Forestali 1998", aggiornato nel 2010 e "Completamento del GIS dei Tipi forestali del Friuli Venezia Giulia" realizzato nel 2011 e validato definitivamente nel 2013. Het is de verzameling van de geometrieën van de bosgebieden gelegen op het grondgebied van de regio Friuli Venezia Giulia. De meeste van deze gebieden worden bewoond door bossen zoals gedefinieerd in de Regional Forest Law (nr.9/2007). De geometrieën zijn afkomstig van twee verschillende geodatabases: „Types Forestali 1998”, bijgewerkt in 2010 en „Voltooiing van het GIS van de bossoorten Friuli Venezia Giulia”, uitgevoerd in 2011 en definitief gevalideerd in 2013. Huwa l-ġbir tal-ġeometriji taż-żoni forestali li jinsabu fit-territorju tar-Reġjun ta’ Friuli Venezia Giulia. Il-biċċa l-kbira ta’ dawn iż-żoni huma okkupati minn foresti kif definit mil-Liġi Reġjonali dwar il-Foresti (Nru.9/2007). Il-ġeometriji ġejjin minn żewġ ġeobażijiet tad-data differenti: “Types Forestali 1998”, aġġornata fl-2010 u “Tlestija tal-GIS tat-Tipi ta’ Foresti ta’ Friuli Venezia Giulia” imwettqa fl-2011 u vvalidata b’mod definittiv fl-2013. Este colecția geometriilor zonelor forestiere situate pe teritoriul regiunii Friuli Venezia Giulia. Cele mai multe dintre aceste zone sunt ocupate de păduri, astfel cum sunt definite în Legea regională privind pădurile (nr.9/2007). Geometriile provin din două baze de date geografice diferite: „Tipuri Forestali 1998”, actualizat în 2010 și „Finalizarea GIS a tipurilor de păduri de Friuli Venezia Giulia”, efectuată în 2011 și validată definitiv în 2013. É a coleção das geometrias das áreas florestais localizadas no território da Região Friuli Venezia Giulia. A maior parte destas áreas é ocupada por florestas, tal como definidas na Lei Regional das Florestas (n.º 9/2007). As geometrias vêm de duas bases de dados geométricas diferentes: «Tipos Forestali 1998», atualizado em 2010 e «Conclusão do SIG dos Tipos Florestais de Friuli Venezia Giulia», realizado em 2011 e validado definitivamente em 2013. It is the collection of the geometries of the forest areas located in the territory of the Friuli Venezia Giulia Region. Most of these areas are occupied by forests as defined by the Regional Forest Law (No.9/2007). The geometries come from two different geodatabases: “Types Forestali 1998”, updated in 2010 and “Completion of the GIS of the Forest Types of Friuli Venezia Giulia” carried out in 2011 and validated definitively in 2013.

Supplementary Information is available for this paper.

It show point estimates of GHG emissions from pesticide production from 1990 to 2016 at provincial level in China.

Wheat Biomass for Kherson and Poltava regions in Ukraine The dataset contains Dry Above Ground Biomass (DAM) estimates over the Kherson and Poltava regions in Ukraine for years 2020,2021 and 2022. - Processing:The processing is done using the AgriCarbon-EOv1.5 processing chain, using the TREX processing centre at CNES France.The input remote sensing data are L2A Sentinel-2 surface reflectances provided by the MAJA processing chain based on the Copernicus Sentinel-2 L1C data.The Landcover maps are provided using ML Deep learning based on the Copernicus L2A data.The daily weather data is extracted from ERA5Land products (C3S). -Geophysical variable:Dry Above ground biomass of winter wheat in g/m2. - Extents: * DAM estimates over the Copernicus Sentinel-2 tile 36TWT cover the Kherson region.* DAM estimates over the Copernicus Sentinel-2 tile 36UVA cover the Poltava region. - Spatial resolution:10m resolution estimlates over wheat plots identified in the landcover map. - Temporal coverage:Estimates are provided at the end of the wheat cycle for cycles:* The year 2020 correspond to cycle: 2019-2020* The year 2021 corresponds to cycle : 2020-2021* The year 2022 corresponds to cycle : 2021-2022 - Projection: EPSG:32636 - File content: Each Raster file has 2 bands containing respectively: * band1: mean value of DAM in g/m2. * band2: standard deviation of DAM in g/m2. - List of maps:* Dry_aboveground_biomass_2020_T36TWT_Kherson_Ukraine.tif* Dry_aboveground_biomass_2020_T36UVA_Poltava_Ukraine.tif* Dry_aboveground_biomass_2021_T36TWT_Kherson_Ukraine.tif* Dry_aboveground_biomass_2021_T36UVA_Poltava_Ukraine.tif* Dry_aboveground_biomass_2022_T36TWT_Kherson_Ukraine.tif* Dry_aboveground_biomass_2022_T36UVA_Poltava_Ukraine.tif

Dataset for the fresh and hardened properties of self-healing concrete, and the bond properties of steel reinforcement in self-healing concrete

Heavy trucks contribute significantly to climate change, and in 2020 were responsible for 7% of total Swedish GHG emissions and 5% of total global CO2 emissions. Here we study the full lifecycle of cargo trucks powered by different energy pathways, comparing their biomass feedstock use, primary energy use, net biogenic and fossil CO2 emission, and cumulative radiative forcing. We analyse battery electric trucks with bioelectricity from standalone or combined heat and power (CHP) plants, and pathways where bioelectricity is integrated with wind and solar electricity. We analyse trucks operated on fossil diesel fuel and on dimethyl ether (DME). All energy pathways are analysed with and without carbon capture and storage (CCS). Bioelectricity and DME are produced from forest harvest residues. Forest biomass is a limited resource, so in a scenario analysis we allocate a fixed amount of biomass to power Swedish truck transport. Battery lifespan and chemistry, the technology level of energy supply, and the biomass source and transport distance are all varied to understand how sensitive the results are to these parameters. The scenario spans 100 years into the future. We find that pathways using electricity to power battery electric trucks have much lower climate impacts and primary energy use, compared to diesel and DME based pathways. The pathways using bioelectricity with CCS result in negative emissions leading to global cooling of the earth. The pathways using diesel and DME have significant and very similar climate impact, even with CCS. The robust results show that truck electrification and increased renewable electricity production is a much better strategy to reduce the climate impact of cargo transport and much more primary energy efficient than the adoption of DME trucks. This climate impact analysis includes all fossil and net biogenic CO2 emissions as well as the timing of these emissions. Considering only fossil emissions is incomplete and could be misleading. This dataset contains data on 4 metrics (primary energy use, biomass feedstock use, cumulative CO2 emissions, and cumulative radiative forcing) resulting from scenario modeling of cargo truck use in Sweden powered by different energy pathways. The energy pathways include battery electric trucks powered by bioelectricity, solar photovoltaic electricity and wind electricity, and internal combustion trucks powered by fossil diesel and dimethyl ether. The scenario spans 100 years into the future. The Excel sheet "tables" contains input data for the scenario modeling, with sources listed where applicable. The remaining sheets contains the modeled results and generated figures that are also a published in the associated article Sathre & Gustavsson (2023). Refer to the method description and reference list in the included documentation files for details. Tunga lastbilar bidrar kraftigt till klimatförändringarna och stod 2020 för 7% av de totala svenska växthusgasutsläppen och 5% av de totala globala CO2-utsläppen. Här studerar vi hela livscykeln för lastbilar som drivs av olika energivägar, jämför deras användning av biomassaråvaror, primär energianvändning, biogena och fossila CO2-utsläpp netto och kumulativ strålningstvingning. Vi analyserar batterielektriska lastbilar med bioel från fristående eller kraftvärmeverk och vägar där bioel integreras med vind- och solkraft. Vi analyserar lastbilar som drivs med fossilt dieselbränsle och med dimetyleter (DME). Alla energivägar analyseras med och utan avskiljning och lagring av koldioxid (CCS). Bioelektricitet och DME produceras av skogsavverkningsrester. Skogsbiomassa är en begränsad resurs, så i en scenarioanalys avsätter vi en fast mängd biomassa för att driva svenska lastbilstransporter. Batteriets livslängd och kemi, tekniknivån för energiförsörjning och biomassakällan och transportavståndet varierar alla för att förstå hur känsliga resultaten är för dessa parametrar. Scenariot sträcker sig 100 år in i framtiden. Vi finner att vägar som använder el för att driva batterielektriska lastbilar har mycket lägre klimatpåverkan och primär energianvändning, jämfört med diesel- och DME-baserade vägar. De vägar som använder bioelektricitet med CCS resulterar i negativa utsläpp som leder till global kylning av jorden. Vägarna med diesel och DME har betydande och mycket liknande klimatpåverkan, även med CCS. De robusta resultaten visar att elektrifiering av lastbilar och ökad förnybar elproduktion är en mycket bättre strategi för att minska godstransporternas klimatpåverkan än införandet av DME-lastbilar, och mycket mer primärenergieffektiv. Denna klimatkonsekvensanalys omfattar alla fossila och biogena CO2-utsläpp samt tidpunkten för dessa utsläpp. Att bara ta hänsyn till fossila utsläpp är ofullständigt och kan vara missvisande. Detta dataset innehåller data om 4 mätvärden (primär energianvändning, biomassaråvara, kumulativa CO2-utsläpp och kumulativ strålkraftspåverkan) som härrör från scenariomodellering av lastbilsanvändning i Sverige som drivs av olika energivägar. Energivägarna inkluderar batterielektriska lastbilar som drivs av bioelektricitet, solcellselektricitet och vindkraft samt förbränningsbilar som drivs av fossil diesel och dimetyleter. Scenariot sträcker sig 100 år in i framtiden. På arket "tables" i Excelfilen återfinns den indata som använts i modelleringen med angivna källor där detta är tillämpligt. Övriga ark innehåller resultat samt figurer som också publiceras i den samhörande artikeln Sathre & Gustavsson (2023). Se metodbeskrivning samt referenslista i tillhörande dokumentationsfiler för detaljer.