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This dataset includes the results summary from a lab-scale bioreactor experiment as discussed in the research paper with the same name, published at Processes MDPI (De Groof, V.; Coma, M.; Arnot, T.C.; Leak, D.J.; Lanham, A.B. Adjusting Organic Load as a Strategy to Direct Single-Stage Food Waste Fermentation from Anaerobic Digestion to Chain Elongation. Processes 2020, 8, 1487.). The study comprised two operational phases of duplicate reactors fed with food waste, each set to target a different product. The data comprises a summary on feedstock composition, microbial community analysis and operational conditions and product outcome per operational phase. The archaeal and bacterial community data includes the final sequences of the operational taxonomic units found and their relative abundance in each sample as determined by 16s rRNA amplicon sequencing. The raw data files have been submitted in the specialized EMBL-EBI database and are available under the accession number PRJEB39281. This dataset was prepared and processed in Microsoft Excel from raw analytical data. The bioinformatic processing prior to the microbial community summary in the spreadsheet was done as outlined in the publication, and results were processed via the DNASense data analysis app (applies Rstudio IDE v.3.5.1 with the ampvis v.2.5.8. package). This version includes rarefaction curves and values of alpha-diversity, richness and evenness per sample in the OTU_table tab. Analytical

Output data prepared for analysis of 25 diverse global cities by the Global Healthy and Sustainable City-Indicator Collaboration study, published in The Lancet Global Health Series on urban design, transport, and health. 2022. https://www.thelancet.com/series/urban-design-2022 Boeing, G. et al. (2022) ‘Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities’, The Lancet Global Health, 10(6), pp. e907–e918. Available at: https://doi.org/10.1016/S2214-109X(22)00072-9. Data outputs were generated through use of the global-indicators software tool, designed for this study and available from: https://github.com/global-healthy-liveable-cities/global-indicators Further detail on the methods used is provided in the following publication: Liu, S., Higgs, C., Arundel, J., Boeing, G., Cerdera, N., Moctezuma, D., Cerin, E., Adlakha, D., Lowe, M. and Giles-Corti, B. (2021), A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data. Geogr Anal. https://doi.org/10.1111/gean.12290 The study made use of OpenStreetMap, Global Human Settlements and custom data, and is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

This is the Global Fuel Exploitation Inventory (GFEI) which provides a 0.1 x 0.1 degree grid of methane emissions of fugitive emissions related to oil, gas, and coal activities (IPCC Sector 1B1 and 1B2). Subsector emissions are provided from exploration to distribution of the resource. The inventory emissions are based on individual country reports submitted in accordance with the United Nations Framework Convention on Climate Change (UNFCCC). For those countries that do not report we estimate emissions following IPCC methods. Emissions are allocated to infrastructure locations including mines, wells, pipelines, compressor stations, storage facilities, processing plants, and refineries. This version of the inventory (GFEI v3) inventory is for 2020 and presents an update of GFEI v2 and v1 which were for 2019 and 2016, respectively. Emission grids are also available for 2010-2019. In GFEI v3, for each sector (oil, gas, coal) and subsector (exploration, production, etc.) there are emission grids. File names are in netcdf format and should start with "Global_Fuel_Exploitation_Inventory_v3_2020_" followed by the sector or subsector name. Please contact us if you would like emissions for an alternate year. We will also make input data and code available upon reasonable request.

This dataset contains terrestrial fluxes of nitrous oxide (N2O), methane (CH4) and ecosystem respiration (carbon dioxide (CO2)) calculated from static chamber measurements in riparian buffers of oil palm plantations on mineral soil, in Riau, Sumatra, Indonesia. Measurements were made monthly, from January 2019 until September 2021, with a break from April 2019 to October 2019 to allow for felling and replanting, and another break from January 2021 to June 2021 due to Covid-19 restrictions. To help to reduce the environmental impact of oil palm plantations, riparian buffers are now required by regulations in many Southeast Asian countries. The experiments were conducted to investigate the impact of greenhouse gas emissions from the riparian buffers. Research was funded through NERC grant NE/R000131/1 Sustainable Use of Natural Resources to Improve Human Health and Support Economic Development (SUNRISE) Greenhouse gas concentrations were measured using static chambers, enclosed for 45 minutes. Multiple regressions (including linear and hierarchical multiple regression) were fitted to calculate the best fit flux, using the RCflux R package, written by Dr Peter Levy (UKCEH).

In recent years, there has been increased attention and focus from the public on the environmental impact of professional sports organizations. Significant opportunities exist for Major League Baseball (MLB) teams to both reduce their own environmental footprint, and that of their fans, through sustainability initiatives. Despite stadiums using upwards of ten million gallons of water per year and having the same energy needs as a small city, no MLB team has completed a public-facing quantification of their total environmental footprint. This project calculated the carbon footprint and water consumption of the Tampa Bay Rays for the 2019 regular season. We analyzed Scope 1, 2, and 3 GHG emissions to identify hotspots within the Rays’ operations, supply chains, and transportation. Fan transportation was found to be the largest source of GHGs, followed by food production for concessions. The cooling tower and restrooms were identified as the largest sources of onsite water usage. We created a repository of best practices as a resource for stadium managers that includes strategies to reduce GHGs and water use coupled with scenario analyses estimating potential reductions. The following recommendations are highlighted as the largest reduction opportunities: (1) prioritizing fan engagement to switch to more sustainable modes of transportation, and (2) offering and highlighting more vegetarian options at concessions. To further reduce emissions and water usage, MLB teams should prioritize sub-metering electricity and water lines and installing more efficient equipment. Data was provided by the Tampa Bay Rays and collected at Tropicana Field (where the Rays play) by Jordan Davis during the summer of 2021.

Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2010), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2010) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).

Twenty soil cores were collected from a field site in Lincolnshire in March 2011, three weeks after planting and Nitrogen fertiliser addition. Soil cores of 150-180 millimetre (mm) depth, containing approximately 1.6 kilogram soil (dry weight) were extracted in Polyvinyl chloride (PVC) pipes (height 215 mm depth 102 mm) and stored at 4 degrees centigrade for 30 days. A four-treatment factorial experiment was designed using soils un-amended or amended with biochar and un-wetted or wetted with deionised water (5 replicates per treatment). Soil in all the cores was mixed to 7 centimetre (cm) depth. To half of the cores, biochar (less than 2 mm) was mixed into the soil at a rate of 3 percent soil dry weight (approximately 22 tons per hectare (t ha-1)). After allowing for any potential Carbon dioxide (CO2) flush from newly-mixed soil to equilibrate for seven days, the cores were placed at 16 degrees centigrade in the dark. Un-wetted soil cores were maintained at 23 percent Gravimetric moisture content (GMC), whilst the GMC of 'wetted' soil cores was increased to 28 percent GMC at the time zero (t0) of four wetting events on day 17, 46, 67 and 116. These water addition rates were based on mean and maximum monthly soil GMC measured in the field between 2009-2010. Data from an investigation of the effects of biochar application to soil on greenhouse gas emissions using soil from a bioenergy crop (Miscanthus X. giganteus). Data include physical (bulk density) and chemical analyses of the soil (total carbon (C) and nitrogen (N), extractable ammonium and nitrate), and greenhouse gas (GHG) emissions (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)) during incubations. Data were collected during two incubation experiments investigating the effects of temperature, soil moisture and soil aeration on biochar induced suppression of GHG emissions. Biochar is a carbon rich substances which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions.

The data from which these carbon-emissions estimates were derived are values of fuel consumed: in billions of cubic feet, for natural gas; in millions of barrels, for petroleum products; and in thousands of short tons, for coal. The resulting emissions estimates are expressed as teragrams of carbon. A teragram is 1012 grams, or 106 metric tons. To convert from carbon to carbon dioxide, multiply by 44/12 (=3.67). Data are available for over 30 different petroleum products, with the exact breakdown varying somewhat from year to year. These products have been treated separately here until the final step of the estimation, at which time CO2 emissions were summed and attributed to liquid petroleum products. These fuel-consumption data are available from the Energy Information Administration of the U.S. Department of Energy. They are published in the Monthly Energy Review, and are available electronically from the Energy Information Administration.

*Updates for this V3: added a few more records and rearranged the sequence of the tables in order to support our new paper "Evaluation of Indirect and Direct Scoring Methods to Relate Biochemical Soil Quality Indicators to Ecosystem Services" accepted by the Soil Science Society of America Journal. We summarize peer reviewed literature reporting associations between for three soil quality indicators (SQIs) (��-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) and crop yield and greenhouse gas emissions. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: �����-glucosidase���, ���permanganate oxidizable carbon���, ���active carbon���, ���readily oxidizable carbon���, or ���fluorescein diacetate hydrolysis���, together with one or more of the following: ���crop yield���, ���productivity���, ���greenhouse gas���, ���CO2���, ���CH4���, or ���N2O���. Meta-data for records include the following descriptor variables and covariates useful for scoring function development: 1) identifying factors for the study site (location, duration of the experiment), 2) soil textural class, pH, and SOC, 3) depth of soil sampling, 4) units used in published works (i.e.: equivalent mass, concentration), 5) SQI abundances and measured ecosystem functions, and 6) summary statistics for correlation between SQIs and functions (yield and greenhouse gas emissions). *Note: Blank values in tables are considered unreported data.

The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress to freshwater resources. Ensuring that increases in irrigated production only occur in places where water is relatively abundant is a key objective of sustainable agriculture, and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet a spatially detailed understanding of the evolution of global area equipped for irrigation (AEI) is missing. Here we utilize the latest sub-national irrigation statistics (covering 17298 administrative units) from various official sources to develop a gridded (5 arc-min resolution) global product of AEI for the years 2000, 2005, 2010, and 2015. We find that AEI increased by 11% from 2000 (297 Mha) to 2015 (330 Mha) with locations of both substantial expansion (e.g., northwest India, northeast China) and decline (e.g., Russia). Combining these outputs with information on green (i.e., rainfall) and blue (i.e., surface and ground) water stress, we also examine to what extent irrigation has expanded unsustainably (i.e., in places already experiencing water stress). We find that more than half (52%) of irrigation expansion has taken place in regions that were already water stressed, with India alone accounting for 36% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security. Recommended citation: Mehta, P., Siebert, S., Kummu, M. et al. Half of twenty-first century global irrigation expansion has been in water-stressed regions. Nat Water (2024). https://doi.org/10.1038/s44221-024-00206-9 Open-access peer reviewed publication available at https://www.nature.com/articles/s44221-024-00206-9 Files G_AEI_*.ASC were produced using the GMIA dataset[https://data.apps.fao.org/catalog/iso/f79213a0-88fd-11da-a88f-000d939bc5d8]. Files MEIER_G_AEI_*.ASC were produced using Meier et al. (2018) dataset [https://doi.pangaea.de/10.1594/PANGAEA.884744].