Dr. Jianmin Ma Atmospheric Environment Service (AQRI) 4905 Dufferin Street, Downsview, Ontario, Canada. M3H 5T4 Tel: (416) 739-4857, Fax:(416) 739-4288 e mail: jianmin.ma@ec.gc.ca
Lead Deposition to Great Lakes Simulated Using Sources from Canada and United States
S. M. DAGGUPATY1 and JIANMIN MA2 1. ARQI, Atmospheric Environment Service, Downsview, Ontario M3H 5T4, Canada 2. Skiman Modlling, 4905 Dufferin Street, Downsview, Ontario M3H 5T4, Canada
Abstract - A modelling study has been made to identify the contributions of lead emission sources in United States and Canada to the lead deposition over Great lakes. The lead emission data collected from two emission inventories TRI (Toxics Release Inventory of U.S) and NRPI (National Pollutant Release Inventory of Canada) were partitioned to U.S. sources, Eastern Canadian sources and total sources of U.S. and Canada. These three types of sources were input separately to a three dimensional, regional scale atmospheric dispersion model to simulate the lead deposition over Great lakes. The numerical experiments were carried out for two years (1994-1995) using the different lead emission data and objectively analyzed and predicted meteorological data (such as wind components, temperature, precipitation) from Global Environmental Multi-scale model (GEM) of CMC (Canadian Meteorological Center). A detailed analysis of model simulated monthly and seasonal lead concentration, dry, wet and total (dry + wet) depositions were made to investigate the contributions of different sources to the lead loading over each lake. Overall results show that the emission data reveal that the lead emission reduced considerably in 1995 compared with 1994 both in Canada and U.S., the contributions of the lead emission sources from Canada and U.S. to each individual lake also changed. However, the ratio of the contributions of the different sources to the Great lakes did not change significantly. Comparison of the model derived concentration and deposition to lakes with IADN (Integrated Acid Deposition Network) monitored and estimated data will be discussed.