Logo image
Back
Forecasting Dose from Unobserved Times: Case Study of Transient Workers at a Nuclear Power Plant
Journal article   Open access   Peer reviewed

Forecasting Dose from Unobserved Times: Case Study of Transient Workers at a Nuclear Power Plant

Kathryn McNamara, Christopher Peters and Igor Burstyn
Annals of work exposures and health, v 62(7), pp 808-817
01 Aug 2018
DOI: https://doi.org/10.1093/annweh/wxy057
PMID: 30107512
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1093/annweh/wxy057View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze),  Open

Abstract

Life Sciences & Biomedicine Public, Environmental & Occupational Health Science & Technology
Objectives: To evaluate the likelihood of exceeding the occupational exposure limit (OEL) for annual ionizing radiation doses among transient workers at the Hope Creek Nuclear Generating Station, and to propose a method for forecasting exposures among transient workers in general. Methods: We obtained personal dosimeter data from the Hope Creek Nuclear Generating Station for the period of January-December 2014, comprising 1955 monthly dose measurements from 498 transient workers.The majority of the transient workers (96%) did not report 12 months of data.The missing months indicate that transient workers may receive ionizing radiation doses at other nuclear power plants throughout the year. We estimated the likelihood of a worker exceeding the Nuclear Regulatory Commission's annual OEL of 5000 mrem.To do so, we had to account both for left-censored data below the limit of detection (27% of all measurements) and make assumptions about doses received during months not employed at the facility. We used a maximum likelihood estimation method for non-detected measurements that accounted for repeated measurements on an individual. To account for missing months of measurements, we considered two extreme scenarios: the best case of workers who receive zero exposures outside of the Hope Creek, and the illustrative worst case of workers who receive multiple exposures at other nuclear power plants with similar exposure scenarios to Hope Creek. We employed a bootstrap procedure to forecast annual personal doses under both scenarios, while imputing non-detected measurements. Results: None of the workers' reported measurements exceeded the OEL. Bootstrapped annual exposure doses revealed similar patterns, with a very small likelihood of exceeding the OEL, but great potential for variability. Some workers under the best-case scenario may reach Hope Creek's 2000 mrem internal action limit if exposed at the 98th percentile of their projected annual dose.This scenario becomes more likely when assuming that a worker received doses at other nuclear power plants besides Hope Creek throughout the year. Conclusions: The Hope Creek Nuclear Generating Station appears to be typical of its industry peers in terms of annual ionizing radiation doses, which makes it a good test subject for predicting worker doses received elsewhere. Transient workers may receive doses at more than one nuclear power plant throughout the year, which makes them especially at risk for overexposure. The presence of internal plant monitoring systems and the use of tools such as bootstrapping to predict compliance are therefore important for health protection. An argument can also be made for better tracking of exposures in real time of transient workers across facilities. Our method applies to transient workers in any industry for whom exposure assessment is complicated by gaps in exposure histories and records.

Metrics

5 Record Views
4 citations in Web of Science
3 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Public, Environmental & Occupational Health
Logo image