Acid deposition in the eastern United States and neural network predictions for the future

Abstract

Back-propagation type neural networks were trained on total sulphur dioxide emissions from power plants and measured field data on precipitation chemistry. These trained networks were then able to predict seasonal changes in sulphate, hydrogen, nitrate, and ammonium ion concentrations caused by projected decreases in sulphur dioxide emissions from power plants in the eastern United States. Results showed that by 2010 the proposed reductions in sulphur dioxide emissions by the U.S. electric power utilities would just be sufficient to reduce acid rain conditions to the levels where human health problems are avoided. However, pollution from acid rain would still be impacting considerable regions of the north-eastern United States and south-eastern Canada causing other environmental damage such as loss of fish in acidic lakes. Key words: acid rain, desulphurization, modelling, neural networks, pollution.