In many cases, human health risk from biological agents is associated with aerosol exposures. Because air concentrations decline rapidly after a release, it may be necessary to use concentrations found in other environmental media to infer future or past aerosol exposures. This article presents an approach for linking environmental concentrations of Bacillus. anthracis (B. anthracis) spores on walls, floors, ventilation system filters, and in human nasal passages with human health risk from exposure to B. anthracis spores. This approach is then used to calculate example values of risk-informed concentration standards for both retrospective risk mitigation (e.g., prophylactic antibiotics) and prospective risk mitigation (e.g., environmental clean up and reoccupancy). A large number of assumptions are required to calculate these values, and the resulting values have large uncertainties associated with them. The values calculated here suggest that documenting compliance with risks in the range of 10(-4) to 10(-6) would be challenging for small diameter (respirable) spore particles. For less stringent risk targets and for releases of larger diameter particles (which are less respirable and hence less hazardous), environmental sampling would be more promising.
The M W 7.1 Darfield (Canterbury) earthquake, 4 September 2010, generated widespread hydrological effects in New Zealand ranging from instantaneous changes of piezometric levels, to more sustained postseismic changes in spring flow, river discharge and groundwater levels, and increased turbidity and declined yields of water abstracted from wells. Four years later, piezometric levels remained elevated in deeper (>40 m) aquifers along the north-western (upper) side of the Canterbury Plains near the Greendale Fault, with changes in mean piezometric level reaching 113 m. Linear reservoir modeling (eigen modeling) suggests that sustained high groundwater was not the result of changes in abstraction or land surface recharge.Step-drawdown tests at six wells within 15 km of Greendale Fault were carried out prior to the earthquake and were retested following fault rupture. Eden-Hazel analysis of discharge/drawdown relationships discriminates potential sources of head losses, and how these changed (or otherwise) as a result of the earthquake. Objective application of Eden-Hazel analysis provided confidence levels for the interpretation, including when step tests provide reliable/unreliable estimates of transmissivity change. Increases in both aquifer losses and well losses were observed in four wells, reflecting both a change in sediment transmissivity and decrease in well efficiency. At two locations, the data were unable to provide results that can be interpreted with confidence. As the majority of local groundwater flow occurs through high-permeability open framework gravel lenses, we suggest that reduction in the permeability of these gravels, due to finesediment incursion, is the cause of the reduction in transmissivity and increase in well losses.
Recently, it has been proposed that spontaneous seismic activity could be used in the estimation of hydrological parameters of aquifers such as permeability and storage. Approximate wave propagation models such as ray tracing, which are commonly used in hydrological parameter estimation with active sources and backscattering geometry, are not feasible with passive seismological imaging. With respect to full wave propagation models, the most accurate known model for aquifers is the poroelastic model while bedrock is usually modelled as an elastic medium. Using a poroelastic model in the forward model can be a computationally impractical choice. In this paper, we carry out a feasibility study in which we attempt to estimate the aquifer depth and water table using a highly approximate elastic model also for the aquifer. We adopt the Bayesian approximation error approach in which a statistical model is constructed for the errors that are induced by using model approximations such as sparse meshing and simplified physical models. We consider the problem in a simple two-dimensional geometry and show that straightforward adoption of approximate models leads to inconsistent parameter estimates, that is, the true parameters have essentially vanishing posterior density. On the other hand, using the Bayesian approximation error approach, the parameter estimates are consistent.
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