Analysis of environmental contamination resulting from catastrophic incidents: Part 1. Building and sustaining capacity in laboratory networks

Magnuson, Matthew L.; Ernst, Hiba; Griggs, John; Fitz-James, Schatzi; Mapp, Latisha; Mullins, Marissa; Nichols, Tonya; Shah, Sanjiv; Smith, Terry; Hedrick, Elizabeth

doi:10.1016/j.envint.2014.01.015

Cited by 5 publications

(4 citation statements)

References 3 publications

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“…UPLC conditions result in complete peak elution of all target analytes in less than 2.5 min, whereas HPLC analysis will require four times that interval for elution of all target analytes. Throughput of hundreds to tens of thousands of samples would be necessary during an all-hazards remediation incident . The ability to process numerous samples over a faster time period could be crucial for decision-makers when site clearance is needed.…”

Section: Resultsmentioning

confidence: 99%

“…Throughput of hundreds to tens of thousands of samples would be necessary during an all-hazards remediation incident. 34 The ability to process numerous samples over a faster time period could be crucial for decision-makers when site clearance is needed. All results presented below were acquired using UPLC; however, HPLC acquisition is possible when UPLC-based laboratory capacity is not available.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

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Investigation of the Persistence of Nerve Agent Degradation Analytes on Surfaces through Wipe Sampling and Detection with Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry

Willison

2014

Anal. Chem.

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The persistence of chemical warfare nerve agent degradation analytes on surfaces is important, from indicating the presence of nerve agent on a surface to guiding environmental restoration of a site after a release. Persistence was investigated for several chemical warfare nerve agent degradation analytes on indoor surfaces and presents an approach for wipe sampling of surfaces, followed by wipe extraction and liquid chromatography-tandem mass spectrometry detection. Commercially available wipe materials were investigated to determine optimal wipe recoveries. Tested surfaces included porous/permeable (vinyl tile, painted drywall, and wood) and largely nonporous/impermeable (laminate, galvanized steel, and glass) surfaces. Wipe extracts were analyzed by ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). UPLC provides a separation of targeted degradation analytes in addition to being nearly four times faster than high-performance liquid chromatography, allowing for greater throughput after a large-scale contamination incident and subsequent remediation events. Percent recoveries from nonporous/impermeable surfaces were 60-103% for isopropyl methylphosphonate (IMPA), GB degradate; 61-91% for ethyl methylphosphonate (EMPA), VX degradate; and 60-98% for pinacolyl methylphosphonate (PMPA), GD degradate. Recovery efficiencies for methyl phosphonate (MPA), nerve agent degradate, and ethylhydrogen dimethylphosphonate (EHDMAP), GA degradate, were lower, perhaps due to matrix effects. Diisopropyl methylphosphonate, GB impurity, was not recovered from surfaces. The resulting detection limits for wipe extracts were 0.065 ng/cm(2) for IMPA, 0.079 ng/cm(2) for MPA, 0.040 ng/cm(2) for EMPA, 0.078 ng/cm(2) for EHDMAP, and 0.013 ng/cm(2) for PMPA. The data indicate that laboratories may hold wipe samples for up to 30 days prior to analysis. Target analytes were observed to persist on surfaces for at least 6 weeks.

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Section: Resultsmentioning

confidence: 99%

Section: ■ Experimental Sectionmentioning

confidence: 99%

Investigation of the Persistence of Nerve Agent Degradation Analytes on Surfaces through Wipe Sampling and Detection with Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry

Willison

2014

Anal. Chem.

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“…The Prediction models are based on historical data acquired by a user, and these data are computed by statistical methods [5]. For instance, some of the research concerned with the prediction of using water budget [6], air pollution data prediction [7], emergency event prediction [8,9], and rainfall trends [10], wind speed behaviour [11][12][13][14], financial models and prediction [15]. The other approach of this survey is classified as strategic location and layout problems as static or deterministic location problems, dynamic location layout problems or location problems under uncertainty [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Estimating Risk Pressure Factor (RPF) with Artificial Neural Network (ANN) to Locate Search and Rescue (SAR) Team Station.

Macit¹

2019

Turkish Journal of Forecasting

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A B S T R A C TEarthquake is one of the natural disaster types that suddenly breaks regular human life. Rescue activities in disasters are one of the most critical stages of modern disaster management. This management stage, as mentioned earlier, includes all the activities that need to be done after the disaster. Search and Rescue (SAR) teams perform one of these most critical activities after the earthquake post-disaster period. Search and rescue teams that will rescue and relief after a disaster are selected according to the criteria selected. Location layout selection problems are NP-Hard, and obtaining hard results is in the class of these problems. One of these criteria is the Risk Pressure Factor (RPF) used in determining the priorities of the risk areas. Determining the level of risk level is very difficult and also these are difficult to predict. In this study, it is aimed to estimate this parametric value by using an artificial neural network (ANN) method which is applied in many fields. And then in this study, a prediction model was constructed by using the backpropagation method which is a suitable propagation method in the ANN method and results are obtained from the MATLAB program. The resulting risk-pressure factor (RPF) value can be used as a parameter in the proposed mathematical model. As a result of the study, the missing parameter of the mathematical model will be found in the estimation of a parameter belonging to the proposed mathematical model. 27In this study, we propose a model including risk pressure factor and forecast the Search and Rescue (SAR) team location and layout mathematical model with the artificial neural network (ANN) method. The aim of this study predicts the risk pressure factor by means of ANN methods. The proposal mathematical model locates the SAR station in exact time window with planning long term period. Literature ReviewANN method can be classified into four main groups such as time-series, simulation, qualitative and cause-effect methods. ANN has many advantages consider to other forecasting methods. Developing better forecasting approaches to reduce or eliminate computation time and its total cost. The Prediction models are based on historical data acquired by a user, and these data are computed by statistical methods [5]. For instance, some of the research concerned with the prediction of using water budget [6], air pollution data prediction [7], emergency event prediction [8,9], and rainfall trends [10], wind speed behaviour [11][12][13][14], financial models and prediction [15]. The other approach of this survey is classified as strategic location and layout problems as static or deterministic location problems, dynamic location layout problems or location problems under uncertainty [16]. Emergency service, medical plant, and ambulance service point location and layout problem are surveyed by many authors [17][18][19][20][21][22][23][24]. While some surveys cover only location layout, the other relatives from these research area such as disaster [25][26][27]. S...

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“…8 Joint biopreparedness calls for cross-sector cooperation at a national level, but at the same time needs to be coordinated with regional and local operations within the various sectors. 9 There are several existing examples of national cross-sector laboratory response networks—that is, networks of laboratories that can identify high-consequence pathogens and respond to different biological threats in a country.…”

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confidence: 99%

Network Experiences from a Cross-Sector Biosafety Level-3 Laboratory Collaboration: A Swedish Forum for Biopreparedness Diagnostics

Thelaus¹,

Lindberg²,

Lambertz³

et al. 2017

Health Security

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The Swedish Forum for Biopreparedness Diagnostics (FBD) is a network that fosters collaboration among the 4 agencies with responsibility for the laboratory diagnostics of high-consequence pathogens, covering animal health and feed safety, food safety, public health and biodefense, and security. The aim of the network is to strengthen capabilities and capacities for diagnostics at the national biosafety level-3 (BSL-3) laboratories to improve Sweden's biopreparedness, in line with recommendations from the EU and WHO. Since forming in 2007, the FBD network has contributed to the harmonization of diagnostic methods, equipment, quality assurance protocols, and biosafety practices among the national BSL-3 laboratories. Lessons learned from the network include: (1) conducting joint projects with activities such as method development and validation, ring trials, exercises, and audits has helped to build trust and improve communication among participating agencies; (2) rotating the presidency of the network steering committee has fostered trust and commitment from all agencies involved; and (3) planning for the implementation of project outcomes is important to maintain gained competencies in the agencies over time. Contacts have now been established with national agencies of the other Nordic countries, with an aim to expanding the collaboration, broadening the network, finding synergies in new areas, strengthening the ability to share resources, and consolidating long-term financing in the context of harmonized European biopreparedness.

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Analysis of environmental contamination resulting from catastrophic incidents: Part 1. Building and sustaining capacity in laboratory networks

Cited by 5 publications

References 3 publications

Investigation of the Persistence of Nerve Agent Degradation Analytes on Surfaces through Wipe Sampling and Detection with Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry

Investigation of the Persistence of Nerve Agent Degradation Analytes on Surfaces through Wipe Sampling and Detection with Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry

Estimating Risk Pressure Factor (RPF) with Artificial Neural Network (ANN) to Locate Search and Rescue (SAR) Team Station.

Network Experiences from a Cross-Sector Biosafety Level-3 Laboratory Collaboration: A Swedish Forum for Biopreparedness Diagnostics

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