Appraisal of Heavy Metal Risk Hazards of <i>Eisenia fetida</i>-Mediated Steel Slag Vermicompost on <i>Oryza sativa</i> L.: Insights from Agro-Scale Inspection and Machine Learning Analytics

Abstract

The steel industry drives world economic growth, yet it generates heavy metal-rich steel slag, which jeopardizes the environment. The utilization of vermi-technology is essential for the sustainable transformation of toxic steel waste slag (SW) into organic amendments, although field-scale use of vermiprocessed SW remains unexplored. To bridge the gap, this study evaluated the efficacy of vermiprocessed SW as an organic supplement for rice field cultivation, focusing on heavy metal (HM) bioavailability, human health risk, and yield in comparison to raw slag and NPK fertilizer. The results indicated a considerable decrease in the bioavailable fraction of heavy metals in T4 (1:1 SW vermicompost 50% + 50% fertilizer). In treatments, T9 (100% SW) and T10 (50% SW + 50% fertilizer) (FIAM) free ion activity modeling confirmed grain absorption of HMs, and the FIAM HQ values indicated the health risk for the direct application of steel slag waste on the field. The risk factor evaluation of HMs’ presence in treatments T9 and T10 established the possible cancer risk for living beings. Similarly, machine learning models like SOBOL sensitivity analysis and artificial neural networks revealed potential threats associated with HMs on different treatments, respectively. The correlation coefficient revealed the negative effects of bioavailable HMs on various soil microbial and enzymatic properties. Moreover, the abundant yield of rice was attributed to the combination treatment (1:1 50% + NPK 50%), which paved the way for an alternative agronomic approach based on the utilization of vermicomposted steel waste slag.

Keywords

• <i>Oryza sativa</i>
• vermicomposted steel waste slag
• field application
• health risk evaluation
• SOBOL analysis