A novel regional-scale human health risk assessment model for soil heavy metal(loid) pollution based on empirical Bayesian kriging

Liting Wang; Renzhi Liu; Jing Liu; Yushun Qi; Weihua Zeng; Baoshan Cui

doi:10.1016/j.ecoenv.2023.114953

A novel regional-scale human health risk assessment model for soil heavy metal(loid) pollution based on empirical Bayesian kriging

Ecotoxicol Environ Saf. 2023 Jun 15:258:114953. doi: 10.1016/j.ecoenv.2023.114953. Epub 2023 May 3.

Authors

Liting Wang¹, Renzhi Liu², Jing Liu³, Yushun Qi¹, Weihua Zeng⁴, Baoshan Cui¹

Affiliations

¹ State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China.
² State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China. Electronic address: liurenzhi@bnu.edu.cn.
³ Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of the People's Republic of China, 210019 Nanjing, China.
⁴ State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001 Qinghai, China.

PMID: 37146388
DOI: 10.1016/j.ecoenv.2023.114953

Abstract

Soil heavy metal(loid)s contamination caused by rapid urbanization and industrialization seriously affects human health and hinders the global sustainable development goals (SDGs). Currently, there is a lack of comprehensive human health risk assessment (HHRA) studies for multiple land use types at the regional scale. We propose a practical risk assessment framework that integrates empirical Bayesian kriging (EBK), pollution level analyses, and modified HHRA modeling. The concentrations of copper industry-related metals (Cu, Ni, Cd, As, and Hg) in 332 topsoil samples from the south bank of the Yangtze River in Tongling were investigated. Obvious enrichment of Cu, Cd, As, and Hg was detected, and the average concentration of Cu was 5.24 times higher than the background values. The distribution of heavy metal(loid) pollution was typically high in the south and east, and low in the north and west. The mean errors of interpolation for Cu, Ni, and Hg were 0.84, 1.29, and 0, respectively, and the root mean square errors of interpolation for Cd and As were 1.29 and 0.86, respectively. Non-carcinogenic risks of soil heavy metal(loid)s were assessed as acceptable throughout the studied area. The hazard index decreased in the order As (0.448) > Ni (0.0729) > Cd (0.0136) > Hg (9.04 ×10^-4) > Cu (6.41 ×10^-4). Nevertheless, the carcinogenic risks of Ni, Cd, and As in 70-80% of the administrative units (AUs) were between 10^-6 to 10^-4, considered an unacceptable level. Exposure through the oral ingestion route accounted for 88.0-99.2% of the total three exposure routes. It is worth noting that four AUs were considered to be the priority control units, and Ni and As were identified as the priority control soil heavy metal(loid)s. This case demonstrates the feasibility and scientific validity of the new EBK-HHRA framework, which confirms that EBK can effectively predict the spatial distribution patterns of soil heavy metal(loid)s and that modified HHRA models are conducive to risk integration at the regional scale. The EBK-HHRA approach is generic and provides substantial support for risk source identification and risk management of soil heavy metal(loid)s contamination at the regional scale.

Keywords: Empirical Bayesian kriging; Heavy metal(loid); Human health risk assessment; Land use; Soil pollution.

MeSH terms

Bayes Theorem
Cadmium / analysis
China
Environmental Monitoring
Humans
Mercury* / analysis
Metals, Heavy* / analysis
Risk Assessment
Soil
Soil Pollutants* / analysis
Spatial Analysis

Substances

Soil
Cadmium
Soil Pollutants
Metals, Heavy
Mercury