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Emerging Threats of Synthetic Biology and Biotechnology : Addressing Security and Resilience Issues (2021)

Trump, Benjamin D. [editor.] ; Florin, Marie-Valentine. [editor.] ; Perkins, Edward. [editor.] ; [et al.]

Dordrecht :Springer Netherlands :

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Keywords: Biotechnology. ; Environmental engineering. ; Bioremediation. ; Security, International. ; Criminology. ; Environmental Law. ; Biotechnology. ; Environmental Engineering/Biotechnology. ; International Security Studies. ; Crime Control and Security. ; Biotechnology. ; Environmental Law.

Description / Table of Contents: Chapter 1: Biosecurity for Synthetic Biology and Emerging Biotechnologies: Critical Challenges for Governance -- Chapter 2: Emerging Biosecurity Threats and Responses: A Review of Published and Gray Literature -- Chapter 3: Opportunities, Challenges, and Future Considerations for Top-Down Governance for Biosecurity and Synthetic Biology -- Chapter 4: Biological standards and biosecurity: The unexplored link -- Chapter 5: Responsible Governance of Biosecurity in Armenia -- Chapter 6: Addressing Emerging Synthetic Biology Threats: The Role of Education and Outreach in Fostering Effective Bottom-Up Grassroots Governance -- Chapter 7: Cybersecurity and Public Health in the Age of COVID-19 -- Chapter 8: Synthetic Biology Brings New Challenges to Managing Biosecurity and Biosafety -- Chapter 9: Emerging Biotechnology and Information Hazards -- Chapter 10: Technical Aspects of Biosecurity: Screening Guidance, Attribution, and Traceability -- Chapter 11: The Soil Habitat and Considerations for Synthetic Biology -- Chapter 12: Foresight in Synthetic Biology and Biotechnology Threats -- Chapter 13: Predicting Biosecurity Threats: Deployment and Detection of Biological Weapons -- Chapter 14: Promoting Effective Biosecurity Governance: Using Tripwires to Anticipate and Ameliorate Potentially Harmful Development Trends. .

Abstract: Synthetic biology is a field of biotechnology that is rapidly growing in various applications, such as in medicine, environmental sustainability, and energy production. However these technologies also have unforeseen risks and applications to humans and the environment. This open access book presents discussions on risks and mitigation strategies for these technologies including biosecurity, or the potential of synthetic biology technologies and processes to be deliberately misused for nefarious purposes. The book presents strategies to prevent, mitigate, and recover from ‘dual-use concern’ biosecurity challenges that may be raised by individuals, rogue states, or non-state actors. Several key topics are explored including opportunities to develop more coherent and scalable approaches to govern biosecurity from a laboratory perspective up to the international scale and strategies to prevent potential health and environmental hazards posed by deliberate misuse of synthetic biology without stifling innovation. The book brings together the expertise of top scholars in synthetic biology and biotechnology risk assessment, management, and communication to discuss potential biosecurity governing strategies and offer perspectives for collaboration in oversight and future regulatory guidance.

Type of Medium: Online Resource

Pages: XV, 225 p. 15 illus., 13 illus. in color. , online resource.

Edition: 1st ed. 2021.

ISBN: 9789402420869

Series Statement: NATO Science for Peace and Security Series C: Environmental Security,

URL: https://doi.org/10.1007/978-94-024-2086-9

DOI: 10.1007/978-94-024-2086-9

DDC: 660.6

Language: English

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Absolute Risk or Relative Risk? A Study of Intraspecies and Interspecies Extrapolation of Chemical-Induced Cancer Risk (2002)

Kuo, Jeanne ; Linkov, Igor ; Rhomberg, Lorenz ; [et al.]

Oxford UK : Blackwell Publishing, Inc.

Risk analysis 22 (2002), S. 0

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ISSN: 1539-6924

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering

Notes: We have used the CBDS database of the National Toxicology Program to study the difference between absolute risk and relative risk models for interspecies and intersex predictions of cancer risk. For no combination (class) of tumor and site is the prediction good for all chemicals. The variation in predicted risk between chemicals exceeds the difference in risks resulting from application of these two models. On the whole, it appears that relative risk is a better model.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/0272-4332.t01-1-00012

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Role of Comparative Risk Assessment in Addressing Environmental Security in the Middle East (2004)

Tal, Alon ; Linkov, Igor

350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.

Risk analysis 24 (2004), S. 0

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ISSN: 1539-6924

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering

Notes: During the 21st century, environmental challenges are likely to intensify across the world and possibly lead to violent conflicts. Strategies for conflict avoidance will be incomplete unless they recognize, discuss, and mitigate regional environmental stress factors. Comparative risk assessment (CRA) is one of the most critical tools emerging to influence modern environmental policies and is increasingly used to create a common language to help reconcile competing interests in development and environmental disputes around the world. This article considers the environmental challenges facing the Middle East in light of their “transboundary” nature and proposes CRA as a framework for setting environmental priorities and reducing tensions in the region.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/j.0272-4332.2004.00522.x

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Model Uncertainty and Choices Made by Modelers: Lessons Learned from the International Atomic Energy Agency Model Intercomparisons (2003)

Linkov, Igor ; Burmistrov, Dmitriy

350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Publishing, Inc.

Risk analysis 23 (2003), S. 0

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ISSN: 1539-6924

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering

Notes: The treatment of uncertainties associated with modeling and risk assessment has recently attracted significant attention. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte Carlo modeling are often recommended. However, the issue of model uncertainty is still rarely addressed in practical applications of risk assessment. The use of several alternative models to derive a range of model outputs or risks is one of a few available techniques. This article addresses the often-overlooked issue of what we call “modeler uncertainty,” i.e., difference in problem formulation, model implementation, and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit Working Group, which was created under the International Atomic Energy Agency (IAEA) BIOMASS program (BIOsphere Modeling and ASSessment). Model-model and model-data intercomparisons reviewed in this study were conducted by the working group for a total of three different scenarios. The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that parameter uncertainty (as evaluated by a probabilistic Monte Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in risk characterization.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/j.0272-4332.2003.00402.x

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[ohne Titel] (2002)

Von Stackelberg, Katherine E. ; Burmistrov, Dmitriy ; Vorhees, Donna J. ; [et al.]

Malden, USA : Blackwell Publishing, Inc.

Risk analysis 22 (2002), S. 0

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ISSN: 1539-6924

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering

Notes: Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas(1,2) by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/0272-4332.00033

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Remedial Policies in Radiologically-Contaminated Forests: Environmental Consequences and Risk Assessment (1997)

Linkov, Igor ; Morel, Benoit ; Schell, William R.

Oxford, UK : Blackwell Publishing Ltd

Risk analysis 17 (1997), S. 0

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ISSN: 1539-6924

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering

Notes: As a result of the Chernobyl nuclear power plant accident in 1986, large forested areas in Europe were contaminated by radionuclides. Extensive societal pressure has been exerted to decrease the radiation dose to the population and to the environment. Thus, in making abatement and remediation policy decisions not only economic costs, but also human and environmental risk assessment are desired. Forest remediation by organic layer removal, one of the most promising cleanup policies, is considered in this paper. Ecological risk assessment requires evaluation of the radionuclide distribution in forests. The FORESTPATH model(1,2) is used for predicting the radionuclide fate in forest compartments after deposition as well as for evaluating the application of the remedial policy. Time of intervention and radionuclide deposition profile was predicted as being crucial for the remediation efficiency. Risk assessment conducted for a critical group of forest users in Belarus shows that consumption of forest products (berries and mushrooms) leads to about 0.004% risk of a fatal cancer. Cost-benefit analysis for forest cleanup suggests that complete removal of organic layer is too expensive for application in Belarus.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/j.1539-6924.1997.tb00844.x

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Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study (2012)

Convertino, Matteo ; Baker, Kelsie ; Lu, Connie ; [et al.]

PANGAEA

In: Supplement to: Convertino, Matteo; Baker, Kelsie; Lu, Connie; Vogel, John T; Suedel, Burton; Linkov, Igor (2013): Use of multi-criteria decision analysis to guide metrics selection for ecosystem restorations. Ecological Indicators, 26, 76-86, https://doi.org/10.1016/j.ecolind.2012.10.005

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Publication Date: 2023-01-13

Description: The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

Type: Dataset

Format: application/zip, 3.2 MBytes

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