A Compact 3H(p,gamma)4He 19.8-MeV Gamma-Ray Source for Energy Calibration at the Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory (SNO) is a new 1000-tonne D2O Cerenkov solar neutrino detector. A high energy gamma-ray source is needed to calibrate SNO beyond the 8B solar neutrino endpoint of 15 MeV. This paper describes the design and construction of a source that generates 19.8-MeV gamma rays using the 3H(p,gamma)4He reaction (``pt''), and demonstrates that the source meets all the physical, operational and lifetime requirements for calibrating SNO. An ion source was built into this unit to generate and to accelerate protons up to 30 keV, and a high purity scandium tritide target with a scandium-tritium atomic ratio of 1:2.0+/-0.2 was included. This pt source is the first self-contained, compact, and portable high energy gamma-ray source (E>10 MeV).Comment: 33 pages (including 2 table, 12 figures) This is the revised manuscript, accepted for publication in NIM A. This revision relfects minor editorial changes from the previous versio

Advancing exposure assessment approaches to improve wildlife risk assessment

The exposure assessment component of a Wildlife Ecological Risk Assessment aims to estimate the magnitude, frequency, and duration of exposure to a chemical or environmental contaminant, along with characteristics of the exposed population. This can be challenging in wildlife as there is often high uncertainty and error caused by broad-based, interspecific extrapolation and assumptions often because of a lack of data. Both the US Environmental Protection Agency (USEPA) and European Food Safety Authority (EFSA) have broadly directed exposure assessments to include estimates of the quantity (dose or concentration), frequency, and duration of exposure to a contaminant of interest while considering “all relevant factors.” This ambiguity in the inclusion or exclusion of specific factors (e.g., individual and species-specific biology, diet, or proportion time in treated or contaminated area) can significantly influence the overall risk characterization. In this review, we identify four discrete categories of complexity that should be considered in an exposure assessment—chemical, environmental, organismal, and ecological. These may require more data, but a degree of inclusion at all stages of the risk assessment is critical to moving beyond screening-level methods that have a high degree of uncertainty and suffer from conservatism and a lack of realism. We demonstrate that there are many existing and emerging scientific tools and cross-cutting solutions for tackling exposure complexity. To foster greater application of these methods in wildlife exposure assessments, we present a new framework for risk assessors to construct an “exposure matrix.” Using three case studies, we illustrate how the matrix can better inform, integrate, and more transparently communicate the important elements of complexity and realism in exposure assessments for wildlife. Modernizing wildlife exposure assessments is long overdue and will require improved collaboration, data sharing, application of standardized exposure scenarios, better communication of assumptions and uncertainty, and postregulatory tracking. Integr Environ Assess Manag 2023;00:1–25