Stochastic Cost Optimization of Multistrategy DNAPL Site Remediation

This paper investigates numerical optimization of dense nonaqueous phase liquid (DNAPL) site remediation design considering effects of prediction and measurement uncertainty. Results are presented for a hypothetical problem involving remediation using thermal source reduction (TSR) and bioremediation with electron donor (ED) injection. Pump-and-treat is utilized as a backup measure if compliance criteria are not met. Remediation system design variables are optimized to minimize expected net present value (ENPV) cost. Adaptive criteria are assumed for real-time control of TSR and ED duration. Source zone dissolved concentration data enabled more reliable and lower cost operation of TSR than soil concentration data, but using both soil and dissolved data improved results sufficiently to more than offset the additional cost. Decisions to terminate remediation and monitoring or to initiate pump-and-treat are complicated by measurement noise. Simultaneous optimization of monitoring frequency, averaging period, and lookback periods to confirm decisions, in addition to remediation design variables, reduced ENPV cost. Results indicate that remediation design under conditions of uncertainty is affected by subtle interactions and tradeoffs between design variables, compliance rules, site characteristics, and uncertainty in model predictions and monitoring data. Optimized designs yielded cost savings of up to approximately 50% compared with a nonoptimized design based on common engineering practices. Significant improvements in accuracy and reductions in cost were achieved by recalibrating the model to data collected during remediation and re-optimizing design variables. Repeating this process periodically is advisable to minimize total costs and maximize reliability.     

Fingerprinting TCE in a bedrock aquifer using compound-specific isotope analysis

A dual isotope approach based on compound-specific isotope analysis (CSIA) of carbon (C) and chlorine (Cl) was used to identify sources of persistent trichloroethylene (TCE) that caused the shut-down in 1994 of a municipal well in an extensive fractured dolostone aquifer beneath Guelph, Ontario. Several nearby industrial properties have known subsurface TCE contamination; however, only one has created a comprehensive monitoring network in the bedrock. The impacted municipal well and many monitoring wells were sampled for volatile organic compounds (VOCs), inorganic parameters, and CSIA. A wide range in isotope values was observed at the study site. The TCE varies between -35.6‰ and -21.8‰ and from 1.6‰ to 3.2‰ for δ(13) C and δ(37) Cl, respectively. In case of cis-1,2-dichloroethene, the isotope values range between -36.3‰ and -18.9‰ and from 2.4‰ to 4.7‰ for δ(13) C and δ(37) Cl, respectively. The dual isotope approach represented by a plot of δ(13) C vs. δ(37) Cl shows the municipal well samples grouped in a domain clearly separate from all other samples from the property with the comprehensive well network. The CSIA results collected under non-pumping and short-term pumping conditions thus indicate that this particular property, which has been studied intensively for several years, is not a substantial contributor of the TCE presently in the municipal well under non-pumping conditions. This case study demonstrates that CSIA signatures would have been useful much earlier in the quest to examine sources of the TCE in the municipal well if bedrock monitoring wells had been located at several depths beneath each of the potential TCE-contributing properties. Moreover, the CSIA results show that microbial reductive dechlorination of TCE occurs in some parts of the bedrock aquifer. At this site, the use of CSIA for C and Cl in combination with analyses of VOC and redox parameters proved to be important due to the complexity introduced by biodegradation in the complex fractured rock aquifer. It is highly recommended to revisit the study when the municipal well is back into full operation.     

Do binaries in clusters form in the same way as in the field?

We examine the dynamical destruction of binary systems in star clusters of different densities. We find that at high densities  (10⁴– 10⁵ M_⊙ pc⁻³)  almost all binaries with separations  >10³  au are destroyed after a few crossing times. At low densities [     ], many binaries with separations  >10³  au are destroyed, and no binaries with separations  >10⁴  au survive after a few crossing times. Therefore, the binary separations in clusters can be used as a tracer of the dynamical age and past density of a cluster.
We argue that the central region of the Orion nebula cluster was ∼100 times denser in the past with a half-mass radius of only 0.1–0.2 pc as (i) it is expanding, (ii) it has very few binaries with separations  >10³  au and (iii) it is well mixed and therefore dynamically old.
We also examine the origin of the field binary population. Binaries with separations  <10²  au are not significantly modified in any cluster, therefore at these separations the field reflects the sum of all star formation. Binaries with separations in the range  10²– 10⁴  au are progressively more and more heavily affected by dynamical disruption in increasingly dense clusters. If most star formation is clustered, these binaries must be overproduced relative to the field. Finally, no binary with a separation  >10⁴  au can survive in any cluster and so must be produced by isolated star formation, but only if all isolated star formation produces extremely wide binaries.     

Using portfolio theory to guide reforestation and restoration under climate change scenarios

The general problem addressed by this study is that of designing a decision support system for planned adaptation to climate change that uses the principles of modern portfolio theory to minimise risk and maximise return of adaptive actions in an environment of deep uncertainty over future climate scenarios. Here we show how modern portfolio theory can use the results of a climate change impact model to select an optimal set of seed sources to be used in regenerating forests of white spruce in an environment of multiple, equally plausible future climates. This study shows that components of solutions are not selected to perform equally well across all plausible futures; but rather, that components are selected to specialise in particular climate scenarios. The innovation of this research rests in demonstrating that the powerful and widely used principles of quantifying and planning for risk and return in the uncertain environment of asset markets can be applied successfully to serve the objectives of planned adaptation to climate change.     

Stimulated dissipation of magnetic discontinuities and the origin of solar flares

It is proposed that the principal cause of the confined solar flare is the dissipation of magnetic energy at the many small-scale pre-existing tangential dscontinuities in the local bipolar magnetic field. The discontinuities are a consequence of the continuous shuffling and intermixing of the footpoints of the bipolar field by the turbulent photospheric granules. The X-ray corona within the bipolar field is presumed to be a consequence of the continuing dissipation by reconnection at these discontinuities. A flare results when static deformation and/or internal agitation of the field stimulates the onset of rapid reconnection at the many small internal discontinuities. The discontinuities are partially exhausted by the flare, so that the post-flare X-ray emission of that particular loop is substantially below the pre-flare level for a period of some hours while the discontinuities are being rejuvenated.This work was supported in part by the National Aeronautics and Space Administration under NASA grant NGL 14-001-001.     

Analysis of solute transport with a hyperbolic scale-dependent dispersion model

An empirical hyperbolic scale-dependent dispersion model, which predicts a linear growth of dispersivity close to the origin and the attainment of an asymptotic dispersivity at large distances, is presented for deterministic modelling of field-scale solute transport and the analysis of solute transport experiments. A simple relationship is derived between local dispersivity, which is used in numerical simulations of solute transport, and effective dispersivity, which is estimated from the analysis of tracer breakthrough curves. The scale-dependent dispersion model is used to interpret a field tracer experiment by nonlinear least-squares inversion of a numerical solution for unsaturated transport. Simultaneous inversion of concentration-time data from several sampling locations indicates a linear growth of the dispersion process over the scale of the experiment. These findings are consistent with the results of an earlier analysis based on the use of a constant dispersion coefficient model at each of the sampling depths.     

Limitations on the parameters of the solar wind in modelling lunar electromagnetic induction

Summary. A striking feature of the day-side response of the Moon to periodic fluctuations in the solar wind is the rapid rise, and subsequent fall, in the amplitude of the transfer function as the inducing field frequency increases. This behaviour can be characterized by the amplitude values at the two frequencies 24 and 40 mHz. Before the response of a conductivity model representing the Moon can be calculated at a given frequency, the parameters (ν, θ) (where ν is the solar wind speed and θ is the angle between the solar wind velocity and the magnetic field propagation direction) have to be specified. By applying some results due to Parker (1972) to the above two data points, we have determined constraints on the parameter space (ν, θ). In particular, we determine the region of the (ν, θ) space in which conductivity models may be found that satisfy our data pair. Outside this region, there are no conductivity models satisfying the data pair, and hence many (ν, θ) values are inconsistent with the original data and the model assumptions.