Using response surface method (RSM) to develop a soil optimization model for designing a natural wastewater treatment filter (Case study: Shahid Tondgoyian Petrochemical Company)

Document Type : Research Paper


1 Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran

2 Department of Management , Faculty of Management and Finance, Khatam University, Tehran, Iran

3 Natural Resources Engineering Department, Faculty of Agriculture and Natural Resources, Yasouj University, Yasouj, Iran


Petrochemical manufacturing processes incorporate toxic and dangerous chemicals, making petrochemical wastewater treatment one of the world's most critical environmental issues today. As a result, this research presents an optimization model of soil characteristics for designing a natural filter for the wastewater treatment of Shahid Tondgoyan Petrochemical Company using the response surface method (RSM). After selecting and sampling soils in Bahmaei city of Kohgiluyeh and Boyer-Ahmad provinces, the physicochemical characteristics of the studied soils were determined, including their acidity (pH), electrical conductivity (EC), percentage of organic matter (OM), and percentage of clay (Clay). Following that, 12 small natural soil filters were designed in the laboratory, and effluent filtration tests were conducted after preparing the effluent from Tondgoyan Petrochemical Company. As response variables, four parameters were determined for the effluent from the filters: acidity (pH), total suspended solids (TSS), iron content (Fe), and manganese content (Mn). We fitted regression models between the four soil parameters (independent variables) and each of the effluent parameters using Design-Expert statistical software (response variables). The PSO algorithm was used to optimize regression models to obtain the optimal values for soil physicochemical parameters to produce the best effluent with the least amount of pollution. The results indicated that parameters such as acidity, electrical conductivity, organic matter, and a high percentage of soil clay would increase the acidity and decrease the total suspended solids, iron, and manganese in the effluent, thereby assisting in the treatment of petrochemical effluent. Additionally, the optimization algorithm determined that an EC of approximately 0.03 dS/cm, an acidity of 7.9, an organic matter percentage of 2.95, and a clay content of 50% are the optimal values for soil parameters whose effluent output parameters included neutral acidity greater than 7, TSS 90, iron 1, and manganese 2.3 mg / l. The findings may aid in the construction of a large-scale soil filter.


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