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Kaminski MD, Daiyega N, Magnuson M. A Review of the Resuspension of Radioactively Contaminated Particles by Vehicle and Pedestrian Traffic-Current Theory, Practice, Gaps, and Needs. HEALTH PHYSICS 2024; 126:216-240. [PMID: 38381971 DOI: 10.1097/hp.0000000000001797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
ABSTRACT The resuspension of radioactively contaminated particles in a built environment, such as from urban surfaces like foliage, building exteriors, and roadways, is described empirically by current plume and dosimetry models used for hazard assessment and long-term risk purposes. When applying these models to radiological contamination emergencies affecting urban areas, the accuracy of the results for recent contamination deposition is impacted in two main ways. First, the data supporting the underlying resuspension equations was acquired for open, quiescent conditions with no vehicle traffic or human activities, so it is not necessarily representative of the urban environment. Second, mechanical disturbance by winds in urban canyons and during emergency operations caused by vehicle traffic and human activities are not directly considered by the equations. Accordingly, plume and dosimetry models allow the user to input certain compensating values, but the models do not necessarily supply users instructions on what values to use. This manuscript reviews the available literature to comprehensively and consistently pool data for resuspension due to mechanically induced resuspension applicable to urban contamination. Because there are few studies that directly measured radioactive resuspension due to vehicles and pedestrians, this review novelly draws on a range of other studies involving non-radioactive particles, ranging from outdoor air pollution emissions to indoor allergen transport. The results lead to tabulated, recommended values for specific conditions in the emergency phase to help users of plume and dosimetry models maintain the conservativeness needed to properly capture the potential radiation dose posed by mechanically induced resuspension. These values are of benefit to model users until better data are available. The results also suggest the types of data that may result in improved plume and dose modeling.
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Affiliation(s)
| | - Nico Daiyega
- Department of Physics, University of Illinois, Urbana-Champaign
| | - Matthew Magnuson
- US Environmental Protection Agency, Office of Research and Development/Center for Environmental Solutions and Emergency Response/Homeland Security and Materials Management Division
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Qian J, Lu ZX, Mancuso CP, Jhuang HY, Del Carmen Barajas-Ornelas R, Boswell SA, Ramírez-Guadiana FH, Jones V, Sonti A, Sedlack K, Artzi L, Jung G, Arammash M, Pettit ME, Melfi M, Lyon L, Owen SV, Baym M, Khalil AS, Silver PA, Rudner DZ, Springer M. Barcoded microbial system for high-resolution object provenance. Science 2020; 368:1135-1140. [PMID: 32499444 DOI: 10.1126/science.aba5584] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 03/31/2020] [Indexed: 02/22/2024]
Abstract
Determining where an object has been is a fundamental challenge for human health, commerce, and food safety. Location-specific microbes in principle offer a cheap and sensitive way to determine object provenance. We created a synthetic, scalable microbial spore system that identifies object provenance in under 1 hour at meter-scale resolution and near single-spore sensitivity and can be safely introduced into and recovered from the environment. This system solves the key challenges in object provenance: persistence in the environment, scalability, rapid and facile decoding, and biocontainment. Our system is compatible with SHERLOCK, a Cas13a RNA-guided nucleic acid detection assay, facilitating its implementation in a wide range of applications.
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Affiliation(s)
- Jason Qian
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
- Biological and Biomedical Sciences Program, Harvard Medical School, Boston, MA 02115, USA
| | - Zhi-Xiang Lu
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Christopher P Mancuso
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
| | - Han-Ying Jhuang
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | | | - Sarah A Boswell
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | | | - Victoria Jones
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Akhila Sonti
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
| | - Kole Sedlack
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
| | - Lior Artzi
- Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Giyoung Jung
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mohammad Arammash
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Mary E Pettit
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Melfi
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Lorena Lyon
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Siân V Owen
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Baym
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Ahmad S Khalil
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA 02215, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
| | - Pamela A Silver
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
| | - David Z Rudner
- Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA 02115, USA
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