Optimal field-scale groundwater remediation using neural networks and the genetic algorithm

Article Abstract:

The high costs of environmental cleanup have prodded scientists to develop approaches that offer cost-effective alternatives. In the study, a nonlinear optimization model using artificial neural networks and genetic algorithm were used in creating contaminant transport models that can be applied in groundwater management initiatives. Application of the model in the cleanup of a Superfund site revealed efficient groundwater transport prediction. This suggests that the approach offers wide potentials for reducing cleanup costs.

Methods, Management, Computer networks, Neural networks, Groundwater flow, Mathematical optimization, Optimization theory

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Modeling the indoor environment

Article Abstract:

Several computer models can assess the exposure of people to indoor air pollutants. The type of model to use depends on the factors that are being considered. These factors include the pollutants, the source of the pollutants and the specification of emission rates. Most models of exposure are either 'what if' models, deterministic models or probabilistic models. One of the most flexible models is IAQM, which can model virtually any pollutant, regardless of the source or averaging time.

Evaluation, Cover Story, Indoor air quality

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A cross-media approach to saving the Chesapeake Bay

Article Abstract:

Chesapeake Bay Program officials integrated three environmental computer models, the watershed model, the Chesapeake Bay Water Quality Model and the EPA's Regional Acid Deposition airshed model, to address acid deposition in the bay. The models are also being used to develop strategies that would reduce eutrophication in the bay.

Models, Pollution, Chesapeake Bay, Water quality management, Environmental protection

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