Implementing Spatial Mapping and Monte Carlo Simulation for Probabilistic Risk Modeling of Heavy Metals Contamination in Urban Soils

Due to rapid and significant urbanization around the world, the land surface of urbanized areas has changed significantly through intensive construction via excavation and underground space development, and the natural state of environmental media such as soil has also altered through the emission of enormous amounts of diverse pollutants. Urban soil conditions, including heavy metal levels (esp., Cu, Zn, As, and Pb), have a significant impact on environmental assessments, so a better understanding of the source, distribution, and contamination of heavy metals is important for managing ecological and human health risks. The purpose of this study is to evaluate heavy metal (Cu, As, Pb, Zn) analysis data from 2,957 locations in Seoul, South Korea, representing the world’s fastest-growing metropolitan area. Statistical methods such as the additive log-ratio transformation-expectation maximization (EM) algorithm were used to process left-censored data below the limits of detection. We then used variogram analysis and ordinary kriging to interpolate the distribution of heavy metal concentrations to a 100m grid. The results showed an overall spatial distribution: more elevated levels of Cu, Pb, and Zn preferentially in the southwest of Seoul, and higher levels of As in the northeast. These patterns primarily imply spatial control of heavy metal enrichment mainly by land use activities in Seoul and warrant further investigation into specific sources of heavy metal pollution. Therefore, Monte Carlo simulation was utilized for risk assessment to provide comprehensive evaluations to incorporate uncertainties. As a result, a probabilistic risk mapping was prepared by running 1,000 randomized simulations per location. Then, the resulting risk maps were then combined with spatial data for vulnerable populations (i.e., infant and elderly populations) to assess potential health impacts. This study on the comprehensive spatial analysis of heavy metals in urban soils can provide key information on the characteristics, distribution, and exposure risk of multiple metals to develop targeted risk reduction strategies in metropolitan areas.

<Acknowledgements> This study was supported by the Korea Environment Industry & Technology Institute (KEITI) through the project ‘Integrated environmental forensic approaches to trace source and pathways of subsurface contaminants (2021002440003)’, funded by Korea Ministry of Environment (MOE), the Institute for Korea Spent Nuclear Fuel (iKSNF) and the BK Plus project in Korea.