Evaluating human health risk assessment tools for contaminated soil: a comparative review

TL;DR

This paper reviews 12 human health risk assessment tools for contaminated soil, highlighting their differences and suggesting improvements for better EU-wide management.

Contribution

The study provides a comparative analysis of HHRA tools and proposes future enhancements for harmonization and functionality.

Findings

There is a lack of harmonization among HHRA tools across different countries.

Future improvements include integrating AI/ML and GIS-based visualizations.

Updating contaminant lists to include emerging pollutants like PFAS is recommended.

Abstract

At the European Union level, approximately 60–70% of soil is in unhealthy or degraded conditions. One of the soil threats is the legacy of industrial pollution, as historic industrial pollutants discharged into the ground continue to pose risks to both the environment and human health. As part of the legislative measures adopted in the late 90 s, Human Health Risk Assessment (HHRA) was introduced as a standardized method for evaluating risks associated with contaminated sites. To support the quantification of these risks, various software tool models were developed. This study reviews 12 HHRA tools for contaminated sites developed across different countries. First, an overview of national legislative frameworks concerning contaminated sites, with a particular focus on the use of HHRA as a decision-making tool, is provided. Subsequently, the study compares and discusses the methodologies adopted by each tool, the exposure pathways and receptors considered, the integrated contaminant databases, and additional features provided by the models. The comparison highlights the diversity of functionalities offered by the different tools, reflecting a lack of harmonization among national regulations regarding contaminated site management. Beyond the need for a harmonized approach at the EU level, potential future developments include the design of more user-friendly interfaces capable of expanding exposure scenarios, updating contaminant lists (including emerging pollutants such as PFAS), integrating uncertainty analysis, incorporating Geographic Information System (GIS)-based visualizations, and integrating artificial intelligence (AI)/machine learning (ML).

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