Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous

Document Type : Research Article

Authors

1 Faculty of Environment, University of Tehran, Tehran, Iran

2 Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran

Abstract

Delijan, the main production center production of bitumen insulation, is one of the most polluted cities in Iran. Therefore, the measurement and analysis of emissions and the optimization of energy consumption, and, thus the reduction of emissions of these pollutants are particularly important. This study aimed to measure the gaseous pollutants emitted from the chimneys of one of the bitumen insulation production units in the industrial city of Delijan and also to improve the performance of the exhaust gas cleaning systems. For this purpose, first, the flow parameters of the chimney are measured with the KIMO gas analyzer, model KIGAS300, and then the pollutants Carbon monoxide, Hydrocarbons, and Nitrogen oxides are optimized of two methods in the MATLAB software using the Genetic Algorithm method and python software using the multiple regression with Sklearn and Statsmodels approach. An objective function was formed that has a non-linear relationship between the preheater outlet air temperature, the percent excess air, and the production of CO, CxHy and NOX pollutants. Statsmodels python regression were presented showing the effect of increasing or decreasing the preheater air temperature and the percent excess air (parameters for which the optimization is carried out) on the amount of pollutants production. According to the optimization results, the most suitable air temperature and percent excess air were selected to achieve the lowest pollutant emissions. Moreover, R2 values are at the 0.89 level and above. Finally, the proposed method can solve optimization problems and support environmental management decisions in the insulation industry.

Keywords

Main Subjects

References

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Environmental Energy and Economic Research
Volume 7, Issue 2
May 2023
Pages 1-14

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