Performance Evaluation of AERMOD and ADMS-Urban for Total Suspended Particulate Matter Concentrations in Megacity Delhi

Regulatory models are useful tools for air quality management. However, application of models without proper evaluation may lead to erroneous conclusions and thus systematic model evaluation studies are essential prior to model application. Often, models are evaluated for a specific source and climatic condition and then find application to another source and climatic condition without this realization. In this context, two well known regulatory models namely; AERMOD (07026) and ADMS-Urban (2.2) are applied throughout the world in various countries without rigorous evaluation procedures. An attempt is made here to undertake performance evaluation of these models for a tropical city such as Delhi in India which is a well known megacity of the world. The models have been applied to estimate ambient particulate matter concentrations for the years 2000 and 2004 over seven sites in Delhi and model evaluation and inter-comparison is performed. Concentrations have been estimated for winter season in both years as the low temperature and low speed wind conditions in this season make it most significant from air pollution point of view. It has been found that though both the models have a tendency towards under-prediction, estimated values by both models agree with the observed concentrations within factor of two. However ADMS-Urban results show better trend correlation with observed values while bias between observed and estimated values is lower for AERMOD Results. The models include all the urban sources (ie. elevated point sources, vehicular traffic, domestic and other sources) in the city. The model validation is discussed in the light of emission inventory, requisite meteorological inputs and statistical performance measures. Performance evaluation of the above models is examined based on boundary layer parameterisations used in these models. Intercomparison of the model performances is envisaged to be useful for application to air quality management and further development of these models.