New Tools Could Help Public Agencies Charge Fees for Soil Contamination
When public officials review plans for a new factory, they often face a toughenvironmental question: How much will it cost to clean up or limit the soil contamination causedby the factory?
A Johns Hopkins University researcher wants to help them answer such questions.
Roger Ghanem, an associate professor of civil engineering, is creating computational toolsthat make reliable predictions about how contamination will spread through soil. With thisinformation in hand, Ghanem says, public officials will be able to charge the builder an equitablefee to cover the cost of keeping these pollutants in check.
Private builders will benefit, too, Ghanem says. Even before they present plans to city hall,companies could use the same tools to decide whether pollution impact fees will make it toocostly to build on a particular site.
Government officials urgently need a credible method of predicting the spread of pollutionso they can charge appropriate cleanup fees, the researcher says. When new housing tracts andshopping centers are proposed, local officials commonly charge fees to help pay for the newschools and roads needed to support these projects. Such fees are based on widely accepted waysof predicting population and traffic changes. But consider industrial plants, which often dischargetoxic and non-toxic waste that seeps through the soil, affecting vegetation and water supplies. It ismuch harder to measure and predict the corresponding levels of contamination, but it must bedone to justify the collection of fees.
"Right now," says Ghanem, "predictions about the spread of ground pollutants are notvery reliable. Public officials cannot assess the magnitude of the pollution a project is going toproduce, so they have no accurate model to base the fees on. But if they had a way to makeaccurate predictions, that would change. They could charge fees and use the money to preventenvironmental damage or clean it up."
Still, the researcher cautions, "If you want to charge people for polluting, you have tohave confidence in your predictions. Otherwise, it's not fair."
To ensure such fairness, Ghanem has spent four years developing mathematical modelsthat show how pollutants are likely to move through different types of soil. For example,pollutants spread quickly through sandy soil but are slowed by clay content. The scientist starts bystudying how individual grains of sand interact with fluids, then moves up through larger andlarger segments of earth.
Ghanem's next goal is to develop computer software that will allow builders and publicofficials to begin using his methods to make reliable predictions about the spread of pollution.When a builder picks a site for a new building, the software will be able to draw on regional soiland landscape information gathered by space satellites, Ghanem says. If a site is already tainted bypollutants, his methods will help the land owner and public officials predict where and howquickly the contamination will move if it is not cleaned up.
Ghanem believes his system could be put into use within three years. Then, it will be up topublic officials to decide how much importance to assign to a project's pollution impact. Forexample, a city may decide to give a proposed factory a break on pollution fees if it is likely togenerate a lot of new tax revenue.
"My method makes predictions about the physical fate of ground pollution," the Hopkinsengineer says. "But there are other factors that ought to be considered, such as the impact on thelocal community and the need for new roads and traffic signals. It's a matter of giving differentweights to different factors."
The National Science Foundation, Sandia National Laboratories and a number of industrialcompanies have provided funding for Ghanem's research.
Related Web Pages:
Johns Hopkins Department of Civil Engineering: http://www.ce.jhu.edu/
Roger Ghanem's Home Page: http://www.ce.jhu.edu/fac/ghanem/default.htm
Materials provided by Johns Hopkins University. Note: Content may be edited for style and length.
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