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This dataset entails various structural material data that was used to provide additional evidence for arguments presented in publication "Deposition of Sn-Zr-Se precursor by thermal evaporation and PLD for the synthesis of SnZrSe3 thin films". Mainly data consists of: SEM, XRD, Raman, Auger and TGA raw data. Summary of results is provided in Extended_data.pdf file

Industrial symbiosis, which allows the sharing of resources between different industries, could help to improve the overall feasibility of bio-based chemicals production. In that regard, this study focused on integrating the torrefaction of pulp industry sludge with anaerobic digestion. More specifically, anaerobic digestion (AD) of pulp sludge-derived torrefaction condensate (TC) was studied to evaluate the biomethane and volatile fatty acid (VFA) potential. The torrefaction condensate produced at 275 and 300 °C was used in AD. The volatile solid content (VS) was 6.69 and 9.01% for the condensate produced at 275 and 300 °C, respectively. The organic fraction of TC mainly contained acetic acid, 2-furanmethanol, and syringol. The methane yield was in the range of 481–772 mL/g VS for the mesophilic and 401–746 mL/g VS for the thermophilic process, respectively. The VFA yield was in the range of 1.1 to 3.4 g/g VS for mesophilic and from 1.5 to 4.7 g/g VS in thermophilic conditions, when methanogenesis was inhibited. Finally, pulp sludge TC is a feasible feedstock to produce platform chemicals like VFA. However, at higher substrate loading, signs of process inhibition were observed because of the relatively increasing concentration of microbial inhibitors

Recently, under COP26, several countries agreed to phase-out coal from their energy systems. Torrefaction industry can take advantage of this, as the fuel characteristics of the torrefied biomass are comparable to those of coal. However, in terms of economic feasibility, torrefied biomass pellets are not yet competitive with coal without subsidies because of the high price of woody biomass. Thus, there is a need to produce torrefied pellets from low-cost feedstock, and pulp industry sludge is one such feedstock. In that context, this study was focused on torrefaction of pulp industry sludge. Torrefaction experiments were carried out using a continuous reactor, at temperatures 250, 275, and 300 ℃. The heating value of the sludge increased from 19 to 22 MJ/kg after torrefaction at 300 ℃. The fixed carbon content increased from 16 wt.% for dried pulp sludge to 30 wt.% for torrefied pulp sludge. The fuel ratio was in the range of 0.27 to 0.61. The ash content of the pulp sludge is comparable to the agricultural waste, which is around 12 wt.% (dry basis). The cellulose content in the sludge reduced from 35 to 12 wt.% at 300 ℃. The ash related issues such as slagging, fouling and bed agglomeration tendency of the sludge were in the medium range. This study shows that torrefaction treatment can improve the fuel properties of the pulp industry sludge to a level comparable to that of low-rank coal.

Fossil pollen assemblages provide a record of past vegetation composition, both natural (climate-induced) and anthropogenic (human-induced). Pollen-based quantitative reconstruction of plant abundance (in percentage cover) require that biases due to differences between plants in pollen productivity and dispersal characteristics are corrected. Such correction is achieved by the “Regional Estimates of VEgetation Abundance from Large Sites”(REVEALS) model given that estimates of relative pollen productivity (RPPs) and fall speed of pollen (FSP) are available for the major plants building the plant cover. For details about the REVEALS model, see Sugita (2007).REVEALS estimates of the abundance of 31 taxa, 11 plant functional types (PFTs), and 3 land-cover types (LCTs) were produced for Europe at a 1˚x1˚ spatial scale for 25 consecutive time windows from 11.7 ka calibrated years BP* to present as part of the Swedish Research Council (VR) research project “LandClimII”. This is the second generation (version June 2021) of REVEALS reconstruction for Europe; it is based on a total of 1128 pollen records from pollen databases/archives and individual authors (See LandClimII Contributors). The first generation was published in Trondman et al. (2015) and Gaillard (2019). These pollen-based REVEALS estimates of land cover are currently used to quantify the effects of the biogeophysical forcing induced by human deforestation on the regional climate of Europe at 6 ka and 2.5 ka BP (VR LandClim II project), and to evaluate and revise the scenarios of anthropogenic land-cover change (ALCC) HYDE (Klein Goldewijk et al., 2017) and KK10 (Kaplan et al., 2009; 2011) .The gridded pollen-based REVEALS reconstructions cover Europe (30°-75°N, 25°W-50°E) and were performed at a spatial scale of 1° × 1° (ca. 100 km × 100 km), which is the estimated spatial scale of REVEALS plant-cover estimates using all available pollen records (1128) within a grid cell and all pollen counts within each time window to ensure reliable estimates of plant cover and minimize their error estimates. The REVEALS estimates and standard errors were reconstructed for 25 time windows covering the Holocene i.e. X to 100 BP, 100 – 350 BP, 350 – 700, 700 – 1200, 1200 -1700 BP and in 500 consecutive time windows from here to 11,700 BP (BP – before present (1950)). The RPP and FSP values used in this REVEALS reconstruction are found in csv table Taxa_to_PFT, PPE and FSP values. All details of the protocol used for this REVEALS reconstruction can be found in Trondman et al. (2015).All REVEALS estimates and their SEs are given in proportions of the grid cell (the total of all REVEALS estimates sum up to 1). There are 25 files labelled TW.(number of time window).RVestimates.jun21.csv and 25 files labelled TW.(number of time window).standarderrors.jun21.csv. The RVestimates.csv files contain the REVEALS estimates for each land-cover type (LCT), plant function type (PFT) and taxa which has a unique grid ID and corresponding longitude and latitude. The standard error csv files contain the standard errors for each land-cover type (LCT), plant function type (PFT) and taxa.* BP = before present (1950). The information about the quality (previously referred to as reliability (Trondman et al. 2015)) of the REVEALS estimates in each grid cell is provided in the GC_quality_by_TW.xlsx file. There are 3 categories i.e. 1 is high quality ( 1 or more large lakes, OR 2 or more sites of any site type), 2 is low quality (only 1 small lake, OR small bog OR large bog) and no data. Extra information about each site is provided in the metadata file. For the full list of contributors see: LandClimII_contributors.xlsxFile descriptions:1.) LANDCLIMII.RV.results.JUN2021.zip - contains 2 folders i.e.a.) LANDCLIMII.RV.means.JUN2021 - 25 csv files one for each time window containing the mean REVEALS estimates of the 31 taxa, 11 plant functional types (PFTs), and 3 land-cover types (LCTs) at each grid cell.b.) LANDCLIMII.RV.standarderrors.JUN2021 - 25 csv files one for each time window containing the standard errors for the REVEALS estimates of the 31 taxa, 11 plant functional types (PFTs), and 3 land-cover types (LCTs) at each grid cell.2.) GC_quality_by_TW.xlsx - contains information about the grid cell quality per time window.3.) LandClimII contributors.xlsx - contains the information for the individuals and databases owning or collating the analyzed pollen records.4.) LandClimII metadata.xlsx - contains all the information regarding the 1128 pollen records e.g. site name, location, source, data available, references etc5.) Taxa_to_PFT, PPE and FSP values.csv - contains the 31 taxa grouped into the 11 PFTs. It also contains the pollen productivity estimates and fall speed of pollen values used in the land-cover reconstruction.

Consumption data are measured in the real household for two weeks and then multiplied to the whole year. This is an average family with 4 members. Consumption behavior is quite similar whole the year. Production graph is measured in real wind generator as described in the paper and when scaled to certain annual production. 15_16_B_0.xlsx – hot water annual demand graph, with averaged 105120 5-min energy intervals, from 1. Dec. 2015-30. Nov 2016. 15_16_NS_0.xlsx – non-shiftable annual demand graph, with averaged 105120 5-min energy intervals, from 1. Dec. 2015-30. Nov 2016. 15_16_PWh_0.xlsx – wind generator annual hourly production graph, with averaged8760 1 h power/energy intervals, from 1. Dec. 2015-30. Nov 2016. 15_16_W_0.xlsx – wind generator annuaproduction graph, with averaged 105120 5-min energy intervals, from 1. Dec. 2015-30. Nov 2016.

This dataset corresponds to the pollen-based REVEALS estimates of 25 plant taxa for Europe and associated standard errors, published in Marquer et al. (2017). This is part of the results from the Swedish project LandClim I (Gaillard et al., 2010; Trondman et al., 2015; Marquer et al., 2014, 2017).The study area includes a large part of northern and Central Europe, i.e. Ireland, Great Britain and a latitudinal transect from the Alps in the south to northernmost Norway.These REVEALS estimates are based on 151 pollen records (small/large, lakes/bogs/mires) that were selected from the European Pollen Database (Fyfe et al., 2009; Giesecke et al., 2014), the Alpine Palynological Data-Base (University of Bern, Switzerland), or were provided directly by individual data contributors.The selected pollen records are grouped into 36 1° x 1° grid-cells.Twenty-five consecutive time windows over the last 11,700 years BP are used: 0-100, 100-350, 350-700 BP for the three first time windows, and 500 calendar years each from 700 to 11,700 BP.For details about the REVEALS model, see Sugita (2007).In the excel file, the folder "Metadata" contains the explanation of abbreviations in the data folders and information about the pollen records used for the REVEALS reconstructions. All REVEALS estimates and their SEs are given in proportions of the grid cell (the total of all REVEALS estimates sum up to 1). The codes of the 25 consecutive time windows are given in the folder "Code time windows". The results of the 36 grid cells are in the folder "REVEALS 36GCs" and the related standard errors in the folder "SE_REVEALS 36GCs". Note that in the folder "Metadata", the GPS coordinates correspond to the upper left (NW) corners of each grid cell. Supplement to: Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph M; Jönsson, Anna Maria; Smith, Benjamin; Kaplan, Jed O; Alenius, Teja; Birks, H John B; Bjune, Anne Elisabeth; Christiansen, Jörg; Dodson, John; Edwards, Kevin J; Giesecke, Thomas; Herzschuh, Ulrike; Kangur, Mihkel; Koff, Tiiu; Latalowa, Malgorzata; Lechterbeck, Jutta; Olofsson, Jörgen; Seppä, Heikki (2017): Quantifying the effects of land use and climate on Holocene vegetation in Europe. Quaternary Science Reviews, 171, 20-37