Abstract:
Hydrogen sulfide (H₂S) is a toxic, corrosive, and malodorous gas generated in wastewater treatment systems, especially under anaerobic conditions. Its emission contributes to sewer infrastructure degradation, air quality deterioration, and public health hazards. Conventional approaches to managing H₂S emissions are mostly reactive and do not account for predictive control based on critical operational parameters. This study addresses this challenge by applying statistical modeling using Minitab to investigate and optimize the influence of key wastewater quality parameters temperature, pH, total suspended solids (TSS), chemical oxygen demand (COD), and hydraulic retention time on H₂S emissions. A Box-Behnken experimental design was employed to develop a response surface model, with the following parameter ranges; temperature (20–35 °C), pH (6.0–8.0), total suspended solids (TSS) (165–250 mg/L), chemical oxygen demand (COD) (445–900 mg/L), and retention time (1.0–4.0 days). Hydrogen sulfide concentration (ppm) was the response variable. Analysis of variance (ANOVA) and regression modeling revealed that pH, temperature and retention time were the most influential parameters, while TSS and COD showed minimal impact. Among the studied parameters, pH (26.52%) and temperature (32.82%) and retention time (21.09%) showed the highest contribution to the model, followed by while TSS (0.91%) and COD (0.13%) that had minimal influence on hydrogen sulfide emissions. The final model achieved a coefficient of determination (R²) of 89.32%, indicating strong predictive reliability. The study provides a data-driven decision support framework for wastewater operators to identify operational conditions that minimize H₂S emissions, reduce odor and corrosion risks.
