The current loss of freshwater habitats and biodiversity calls for an immediate mobilization and application of existing data and tools to contribute to the development of sound strategies for their long-term conservation. However, one particular challenge for obtaining a baseline regarding the spatial distribution of freshwater habitats and biodiversity is the need for standardized high-resolution environmental information, which ideally can provide a characterization of freshwater habitats anywhere in the world. To address this challenge, we present the Environment90m dataset which aggregates a large number of environmental layers into each of the 726 million sub-catchments of the Hydrography90m dataset, corresponding to single stream segments. Specifically, Environment90m includes 45 variables related to topography and hydrography, 19 climate variables for the observation period of 1981-2010, as well as projections for 2041-2070 and 2071-2100 under the Shared Socioeconomic Pathways (SSPs) 1.26, 3.70 and 5.85, and three global circulation models (UKESM, MPI and IPSL). Moreover, Environment90m includes 22 land cover categories for the annual time-series data from 1992-2020. In addition, we provide 15 soil variables and information on aridity and modelled streamflow. Summary statistics (i.e., mean, min, max, range, sd) are provided for all continuous variables while for categorical data, the proportion of each category is calculated within each of the sub-catchments. The data is available at https://hydrography.org/environment90m. To facilitate data download and processing, we provide dedicated functions within the hydrographr R-package. For all underlying calculations, we used the open-source tools GDAL/OGR, GRASS-GIS and AWK, so that custom data can be easily generated using the hydrographr R-package. Environment90m, along with the tools, provides an array of opportunities for research and application in spatial freshwater biodiversity science, specifically biogeographical analyses and conservation in freshwater ecosystems.