Research reveals that a “finite pool of worry” constrains concern about and action on climate change. Nevertheless, a longitudinal panel survey of 1,858 UK residents, surveyed in April 2019 and June 2020, reveals little evidence for diminishing climate change concern during the COVID-19 pandemic. Further, the sample identifies climate change as a bigger threat than COVID-19. The findings suggest climate change has become an intransigent concern within UK public consciousness.

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The Chernobyl nuclear power plant meltdown has to date been the single largest release of radioactivity into the environment. As a result, radioactive contamination that poses a significant threat to human health still persists across much of Europe with the highest concentrations associated with Belarus, Ukraine, and western Russia. Of the radionuclides still prevalent with these territories Cs presents one of the most problematic remediation challenges. Principally, this is due to the localised spatial and vertical heterogeneity of contamination within the soil (~10's of meters), thus making it difficult to accurately characterise through conventional measurement techniques such as static in situ gamma-ray spectrometry or soil cores. Here, a practical solution has been explored, which utilises a large number of short-count time spectral measurements made using relatively inexpensive, lightweight, scintillators (sodium iodide and lanthanum bromide). This approach offers the added advantage of being able to estimate activity and burial depth ofCs contamination in much higher spatial resolution compared to traditional approaches. During the course of this work, detectors were calibrated using the Monte Carlo Simulations and depth distribution was estimated using the peak-to-valley ratio. Activity and depth estimates were then compared to five reference sites characterised using soil cores. Estimates were in good agreement with the reference sites, differences of ~25% and ~50% in total inventory were found for the three higher and two lower activity sites, respectively. It was concluded that slightly longer count times would be required for the lower activity (<1MBqm) sites. Modelling and reference site results suggest little advantage would be gained through the use of the substantially more expensive lanthanum bromide detector over the sodium iodide detector. Finally, the potential of the approach was demonstrated by mapping one of the sites and its surrounding area in high spatial resolution.

There are a large number of sites across the UK and the rest of the world that are known to be contaminated with (226)Ra owing to historical industrial and military activities. At some sites, where there is a realistic risk of contact with the general public there is a demand for proficient risk assessments to be undertaken. One of the governing factors that influence such assessments is the geometric nature of contamination particularly if hazardous high activity point sources are present. Often this type of radioactive particle is encountered at depths beyond the capabilities of surface gamma-ray techniques and so intrusive borehole methods provide a more suitable approach. However, reliable spectral processing methods to investigate the properties of the waste for this type of measurement have yet to be developed since a number of issues must first be confronted including: representative calibration spectra, variations in background activity and counting uncertainty. Here a novel method is proposed to tackle this issue based upon the interrogation of characteristic Monte Carlo calibration spectra using a combination of Principal Component Analysis and Artificial Neural Networks. The technique demonstrated that it could reliably distinguish spectra that contained contributions from point sources from those of background or dissociated contamination (homogenously distributed). The potential of the method was demonstrated by interpretation of borehole spectra collected at the Dalgety Bay headland, Fife, Scotland. Predictions concurred with intrusive surveys despite the realisation of relatively large uncertainties on activity and depth estimates. To reduce this uncertainty, a larger background sample and better spatial coverage of cores were required, alongside a higher volume better resolution detector.

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