Groundwater geochemistry, quality, and pollution of the largest lake basin in the Middle East: Comparison of PMF and PCA-MLR receptor models and application of the source-oriented HHRA approach

Hamed Haghnazar; Karen H Johannesson; Ricardo González-Pinzón; Mojtaba Pourakbar; Ehsan Aghayani; Akbar Rajabi; Ahmad Asl Hashemi

doi:10.1016/j.chemosphere.2021.132489

Groundwater geochemistry, quality, and pollution of the largest lake basin in the Middle East: Comparison of PMF and PCA-MLR receptor models and application of the source-oriented HHRA approach

Chemosphere. 2022 Feb;288(Pt 1):132489. doi: 10.1016/j.chemosphere.2021.132489. Epub 2021 Oct 6.

Authors

Hamed Haghnazar¹, Karen H Johannesson², Ricardo González-Pinzón³, Mojtaba Pourakbar⁴, Ehsan Aghayani⁵, Akbar Rajabi⁶, Ahmad Asl Hashemi⁷

Affiliations

¹ Department of Watershed Sciences, Utah State University, UT, 84322, USA.
² School for the Environment, University of Massachusetts Boston, Boston, MA, 02125, USA.
³ Department of Civil, Construction & Environmental Engineering, University of New Mexico, Albuquerque, NM, 87131, USA.
⁴ Department of Environmental Health Engineering, Maragheh University of Medical Sciences, Maragheh, Iran.
⁵ Department of Environmental Health Engineering, Abadan University of Medical Sciences, Abadan, Iran.
⁶ Department of Environmental Health Engineering, Faculty of Health, Tabriz University of Medical Science, Tabriz, Iran.
⁷ Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. Electronic address: aaslhashemi@yahoo.com.

PMID: 34626652
DOI: 10.1016/j.chemosphere.2021.132489

Abstract

We evaluated groundwater quality, pollution, and its effects on human health in the eastern part of the Lake Urmia basin, the largest lake in the Middle East. Although groundwater quality is suitable for drinking and irrigation purposes, an index-based approach quantifying heavy metal pollution revealed that most sampling sites exhibited moderate to high pollution levels in the northern and southern regions. The positive matrix factorization (PMF) and principal component analysis-multi linear regression (PCA-MLR) receptor models suggest that the main contributors to the observed groundwater pollution, expressed as percentages by model, were: lake water infiltration and dissolution of minerals and fertilizers (46% and 63%), infiltration of leachates from solid wastes (29% and 15%), mixing with industrial-municipal wastewaters (18% and 13%), and vehicular emissions (7% and 9%). The PMF model indicated better correlations between observed and predicted concentrations (R² = 0.96) than the PCA-MLR (R² = 0.89). Our results from the human health risk assessments (HHRA) highlight non-carcinogenic and carcinogenic risks for Pb and Cr, respectively. Also, the PMF-based assessment of human health risk indicated that wastewaters and solid waste leachates are responsible for the cancer risk from Cr for children.

Keywords: Groundwater quality; Heavy metals; Human health risks; Hydrogeochemistry; PMF.

MeSH terms

Environmental Monitoring
Groundwater*
Humans
Lakes*
Linear Models
Principal Component Analysis
Risk Assessment