The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

Concentrations of trace metals in soils from a grid of sites located around a disused (since 2003) smelting works in the Avonmouth, UK, area. The soil samples were collected on 4th and 5th October 2007 and were analysed for concentrations of Aluminium and Iron, using inductively-coupled plasma optical emission spectrometry (ICPOES), and Chromium, Copper, Zinc, Nickel, Arsenic, Cadmium, Mercury and Lead, using inductively-coupled plasma mass spectrometry (ICPMS). The dataset also includes information on soil pH and soil organic matter content (loss on ignition).

This dataset comprises operational data for a point-of-use drinking water treatment system (POU DWTS) located on the University of the West of England’s Frenchay campus. This dataset covers 34 months (November 2019 to September 2022). The POU DWTS was continuously operational throughout this period with parameters presented in this dataset including oxidation reduction potential, free available chlorine, flow rate, discharge pressure, filtration flux, ultrafiltration membrane permeability. Telemetry data is collected over a 5-minute period provide a rolling 5-minute average and is available in a .csv format. Full details about this dataset can be found at https://doi.org/10.5285/d3daab67-dc02-43a0-82c0-afff709c43f4