Appraisal of environmental, ecological and carcinogenic risk due to heavy metals in a sewage and solid waste contaminated area

ABSTRACT

Unsystematic use of city waste, sludge and sewage water in agricultural fields elevated the heavy metal load in soil warranting critical introspection. The present study aims to delineate heavy metals in polluted soils of peri-urban Kolkata, determine pollution and ecological risk, assess the heavy metal uptake and human dietary risk in commonly cultivated crops. Total 36 sampling points were selected and paired sampling of soil and crops were done. Significant available heavy metal (mg kg-1) in surface soil like Cd (0.72-3.76), Pb (28.59-87.29), Ni (3.11-8.73), and Cr (2.23-8.43) and in crops as Cd (0.55-2.73), Pb (2.82-29.85), Ni (2.45-8.27) and Cr (0.80-6.85) was observed. Use of machine learning revealed soil pH and organic carbon as the influencing factors of heavy metal contamination. Moderate to considerable environmental and ecological risk was observed. Substantial carcinogenic risk was observed as Cd (1.13x10-3 to 3.77x10-4), Pb (2.75x10-4 to 3.47x10-5), Ni (1.15x10-3 to 1.73x10-4), and Cr (2.78x10-4 to 1.18x10-4), for almost all crops, with a general trend of spinach > cabbage > radish > red amaranthus > bottle gourd > maize. The results can serve as the baseline information to enforce policy decisions for solving this conundrum of managing waste and saving human lives.        

KEYWORDS:

• Toxic heavy metals
• paired soil-crop sampling
• machine learning
• spatial mapping
• target cancer risk
• pollution indices

Highlights

• Long-term deposits of sewage and solid waste result in heavy metal (HM) contamination.

• Elevated soil HM bio-accumulates in crops and ramifies through the food chain.

• Machine learning reveals soil pH and organic carbon as major soil HM determinants.

• High environmental, ecological and carcinogenic risk exists for soil–plant HM load.

• The baseline information can ensure policy decisions for solving HM problem.

Acknowledgments

The authors acknowledge the help and cooperation of the farming communities, laboratory technical staffs, and local residents of Dhapa landfill areas for proper execution of the research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author’s contributions

Shreya Das: Methodology, Investigation, Formal analysis, Kriging Interpolation, Spatial distribution map preparation, writing – original draft; Sudip Sengupta: Methodology, Analysis, Data curation, Statistical analyses and modeling, Software, Writing – review and editing, Visualization; Prasanta Kumar Patra: Conceptualization, Project administration, Writing-review and editing; Pravat Utpal Acharjee: Methodology, Data curation, Validation, Editing; Susanta Kumar Pal: Supervision, Writing-review and editing.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15320383.2022.2112651