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In 2016, the U.S. Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), and state partners investigated nine Listeria monocytogenes infections linked to frozen vegetables. The investigation began with two environmental L. monocytogenes isolates recovered from Manufacturer A, primarily a processor of frozen onions, that were a match by whole genome sequencing (WGS) to eight clinical isolates and historical onion isolates with limited collection details. Epidemiologic information, product distribution, and laboratory evidence linked suspect food items, including products sourced from Manufacturer B, also a manufacturer of frozen vegetable/fruit products, with an additional illness. The environmental isolates were obtained during investigations at Manufacturers A and B. State and federal partners interviewed ill people, analyzed shopper card data, and collected household and retail samples. Nine ill persons between 2013 and 2016 were reported in four states. Of four ill people with information available, frozen vegetable consumption was reported by three, with shopper cards confirming purchases of Manufacturer B brands. Two identified outbreak strains of L. monocytogenes (Outbreak Strain 1 and Outbreak Strain 2) were a match to environmental isolates from Manufacturer A and/or isolates from frozen vegetables recovered from open and unopened product samples sourced from Manufacturer B; the investigation resulted in extensive voluntary recalls. The close genetic relationship between isolates helped investigators determine the source of the outbreak and take steps to protect public health. This is the first known multistate outbreak of listeriosis in the United States linked to frozen vegetables and highlights the significance of sampling and WGS analyses when there is limited epidemiologic information. Additionally, this investigation emphasizes the need for further research regarding food safety risks associated with frozen foods.

This paper describes a recent study on using fly ash for backfilling abandoned room and pillar mines. Detailed investigations on fly ash properties such as the strength and stiffness of settled fly ash, flowability of fly ash grout, as well as chemistry and environmental aspects of fly ash backfill have been undertaken in the laboratory. Numerical modelling was also conducted to quantify the effects of fly ash backfill on the stability of underground pillars. The laboratory tests showed that with a solid concentration of approximate 50%, fly ash grout has an excellent flowability and very low viscosity. It is capable of penetrating and filling almost any voids underground if designed properly and settling as a reasonably stiff solid to provide support to the pillars. Several different types of strength tests proved that a consolidated fly ash should exhibit a friction angle above 42°. 3D numerical modelling on interaction between fly ash backfill and underground pillars has shown that fly ash backfill to 90% roadway height can raise the factor of safety (FoS) of a marginally stable area to above 1.6, which is the number often used in rock engineering design for long term stability. Chemistry and leachate analysis of representative fly ash samples from a local power station showed that the elemental concentrations in the fly ash solid sample are lower than the allowed contaminant threshold and specific contaminant concentration levels. Geotechnical monitoring in the high risk areas of an abandoned mine has been carried out as part of the risk management and control for potential subsidence. The monitoring has been very helpful in understanding the ground behaviour around the abandoned mine which can provide timely information to the parties concerned in order to make correct decisions to control the subsidence risk. Keywords: Abandoned mine, Backfill, Fly ash, Laboratory tests, Monitoring, Modelling

This paper presents a new dynamic environmental risk model, with intended use within a new, dynamical approach for risk based ship traffic prioritisation. The philosophy behind this newly developed approach is that shipping risk can be reduced by directing efforts towards ships and areas that have been identified as high priority (high risk), prior to a potential accident. The risk model proposed in this paper separates itself from previous models by drawing on available information on dynamic factors and by focusing on the ship's surroundings. The model estimates the environmental risk of drift grounding accidents for oil tankers in real time and in forecast mode, combining the probability of grounding with oil spill impact on the coastline. Results show that the inherent dynamic risk introduced by an oil tanker sailing along the North Norwegian coast depends, not surprisingly, significantly upon wind and ocean currents, as well as tug position and cargo oil type. Results of this study indicate that the risk model is well suited for real time risk assessment, and effectively separates low risk and high risk situations. The model is well suited as a tool to prioritise oil tankers and coastal segments. This enables dynamic risk based positioning of tugs, using both real-time and projected risk, for effective support in case of a drifting ship situation.

The paper describes a model, which estimates the risk levels of individual crude oil tankers. The intended use of the model, which is ready for trial implementation at The Norwegian Coastal Administrations new Vardø VTS (Vessel Traffic Service) centre, is to facilitate the comparison of ships and to support a risk based decision on which ships to focus attention on. For a VTS operator, tasked with monitoring hundreds of ships, this is a valuable decision support tool. The model answers the question, "Which ships are likely to produce an oil spill accident, and how much is it likely to spill?".