In the present study, air quality dispersion analysis was performed for the area near the Rajpura Thermal Power Plant, located in the Punjab province of India. The emission inventory was prepared from point source emissions of the power plant and two representative large-scale industries to differentiate the impact of the thermal power plant alone. Prediction of ground-level concentrations of air pollutants viz. SO₂, NO₂, and SPM was performed by the United States Environment Protection Agency‑approved air quality dispersion models, namely Industrial Source Complex-Short Term Version 3 (ISCST3) and American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD). The spatial dispersion of maximum concentration for the sources of thermal power plant showed that AERMOD predicted higher concentrations near the source when compared with ISCST3 for daily averaging periods. The predicted ground-level concentrations of both the models with data from all the sources’ inventory were found to be similar to the predicted ground-level concentrations of both the models with inputs limited to the source emission data of the thermal power plant alone. The predicted concentrations by two models were compared with each other and validation of models was done with the actual observed concentrations at eight major receptor sites within the study area for the better model performance. The coefficient of correlation graphs suggested that the overall results of AERMOD predictions were better than those of ISCST3 predictions.

在本研究中，对印度旁遮普省拉杰普拉热电厂附近地区进行了空气质量分散分析。排放清单是根据电厂和两个有代表性的大型行业的点源排放量编制的，以区分火电厂本身的影响。预测空气污染物的地面浓度。SO ₂，NO ₂，SPM由美国环境保护局批准的空气质量扩散模型执行，即工业源综合短期术语第3版（ISCST3）和美国气象学会/环境保护局管制模型（AERMOD）。火力发电厂源的最大浓度在空间上的分散表明，与ISCST3相比，AERMOD预测在源附近的平均浓度更高。发现两个模型的预测地平面浓度与来自所有来源的清单的数据相似，两个模型的预测地平面浓度与输入仅限于火力发电厂的源排放数据相似。将两个模型的预测浓度相互比较，并使用研究区域内八个主要受体位点的实际观察浓度对模型进行验证，以获得更好的模型性能。相关系数图表明，AERMOD预测的总体结果优于ISCST3预测的结果。