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Putting A Price Tag On Pollution

Aug. 4, 1998New Tools Could Help Public Agencies Charge Fees for Soil Contamination


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When public officials review plans for a new factory, they often face a tough environmental question: How much will it cost to clean up or limit the soil contamination caused by 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 tools that make reliable predictions about how contamination will spread through soil. With this information in hand, Ghanem says, public officials will be able to charge the builder an equitable fee 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 too costly to build on a particular site.

Government officials urgently need a credible method of predicting the spread of pollution so they can charge appropriate cleanup fees, the researcher says. When new housing tracts and shopping centers are proposed, local officials commonly charge fees to help pay for the new schools and roads needed to support these projects. Such fees are based on widely accepted ways of predicting population and traffic changes. But consider industrial plants, which often discharge toxic and non-toxic waste that seeps through the soil, affecting vegetation and water supplies. It is much harder to measure and predict the corresponding levels of contamination, but it must be done to justify the collection of fees.

"Right now," says Ghanem, "predictions about the spread of ground pollutants are not very reliable. Public officials cannot assess the magnitude of the pollution a project is going to produce, so they have no accurate model to base the fees on. But if they had a way to make accurate predictions, that would change. They could charge fees and use the money to prevent environmental damage or clean it up."

Still, the researcher cautions, "If you want to charge people for polluting, you have to have confidence in your predictions. Otherwise, it's not fair."

To ensure such fairness, Ghanem has spent four years developing mathematical models that 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 by studying how individual grains of sand interact with fluids, then moves up through larger and larger segments of earth.

Ghanem's next goal is to develop computer software that will allow builders and public officials 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 soil and landscape information gathered by space satellites, Ghanem says. If a site is already tainted by pollutants, his methods will help the land owner and public officials predict where and how quickly 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 to public officials to decide how much importance to assign to a project's pollution impact. For example, a city may decide to give a proposed factory a break on pollution fees if it is likely to generate a lot of new tax revenue.

"My method makes predictions about the physical fate of ground pollution," the Hopkins engineer says. "But there are other factors that ought to be considered, such as the impact on the local community and the need for new roads and traffic signals. It's a matter of giving different weights to different factors."

The National Science Foundation, Sandia National Laboratories and a number of industrial companies 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

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The above story is reprinted from materials provided by Johns Hopkins University.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.


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