Pre-Operational Validation of Air Quality Forecasting Model SILAM for India | Abstract
Journal of Pollution Effects & Control

Journal of Pollution Effects & Control
Open Access

ISSN: 2375-4397


Pre-Operational Validation of Air Quality Forecasting Model SILAM for India

Arpit Tiwari*, Vijay Kumar Soni, Chinmay Jena, Anikendar Kumar, Sanjay Bist and Rostislav Kouznetsov

A pre-operational validation of the System for Integrated Modeling of Atmospheric Composition (SILAM) model for Indian application has been presented in this paper. The model configuration has been adjusted according to the atmospheric and emissive conditions of India. India is one of the most desired regions for Air Quality (AQ) research around the globe. The region is composed of different atmospheric and man-made pollution activities. The weather system of India is favorable for the deposition of particulate pollutants in the Indo-Gangetic plains; the northern part of the country. Stubble burning and lower planetary boundary layer height are significant factors that deteriorate the AQ of Delhi-NCR in post-monsoon and winter seasons. India Meteorological Department (IMD) is continuously monitoring the AQ of Delhi-NCR along with central pollution control board and state pollution control committees with stationary ambient air quality monitoring stations. This joint effort of all the agencies relies upon Graded Response Action Plan (GRAP); an initiative by the Government of India (GOI) for pollution control in the Delhi-NCR region. An accurate AQ forecasting system is needed for GOI to implement a decision support system in order to make citizens aware of their surroundings for outdoor activities. We have successfully deployed Indian application of SILAM model in collaboration with Finnish Meteorological Institute (FMI) in Environment Monitoring and Research Center, IMD. One month observations of coarse and fine mode particulate matter (PM 10 and PM 2.5) over Delhi have been compared with SILAM forecast f or December 2020. The modeled and observed values are reasonably correlated in general and model has successfully captured the pollution events throughout the time period. It is found that PM 10 forecasts over Delhi are fairly overestimated and PM 2.5 forecasts are slightly overestimated with a positive correlation of 0.7. Further research in surface emissions and extreme pollution events is needed to make the predictions more accurate.

Published Date: 2022-05-05; Received Date: 2022-04-04