Journal Article

Identification of groundwater nitrate sources in an urban aquifer (Alborz Province, Iran) using a multi-parameter approach

Ostadhashemi, Zohreh, Zaryab, Abdulhalim, Minet, Eddy, Knoeller, Kay, Musavi, Seyedeh Fatemeh, Alijani, Farshad

2024

Overview

High concentrations of NO 3 ̄ in water resources are detrimental to both human health and aquatic ecosystems. Identification of NO 3 ̄ sources and biogeochemical processes is a crucial step in managing and controlling NO 3 ̄ pollution. In this study, land use, hydrochemical data, dual stable isotopic ratios and Bayesian Stable Isotope Mixing Models (BSIMM) were integrated to identify NO 3 ̄ sources and estimate their proportional contributions to the contamination of the Karaj Urban Aquifer (Iran). Elevated NO 3 ̄ concentrations indicated a severe NO 3 ̄ pollution, with 39 and 52% of groundwater (GW) samples displaying the concentrations of NO 3 ̄ in exceedance of the World Health Organization (WHO) standard of 50 mg NO 3 ̄ L −1 in the rainy and dry seasons, respectively. Dual stable isotopes inferred that urban sewage is the main NO 3 ̄ source in the Karaj Plain. The diagram of NO 3 ̄/Cl‾ versus Cl‾ confirmed that municipal sewage is the major source of NO 3 ̄. Results also showed that biogeochemical nitrogen dynamics are mainly influenced by nitrification, while denitrification is minimal. The BSIMM model suggested that NO 3 ̄ originated predominantly from urban sewage (78.2%), followed by soil organic nitrogen (12.2%), and chemical fertilizer (9.5%) in the dry season. In the wet season, the relative contributions of urban sewage, soil nitrogen and chemical fertilizer were 87.5, 6.7, and 5.5%, respectively. The sensitivity analysis for the BSIMM modeling indicates that the isotopic signatures of sewage had the major impact on the overall GW NO 3 ̄ source apportionment. The findings provide important insights for local authorities to support effective and sustainable GW resources management in the Karaj Urban Aquifer. It also demonstrates that employing Bayesian models combined with multi-parameters can improve the accuracy of NO 3 ̄ source identification.

• Publisher: Springer Netherlands,Springer Nature B.V
• Subject: Agrochemicals / Aquatic ecosystems / Aquifers / Bayes Theorem / Bayesian analysis / Bayesian theory / Biogeochemistry / Chemical fertilizers / Contamination / Denitrification / Dry season / Earth and Environmental Science / Ecosystem / Environment / Environmental Chemistry / Environmental Health / Fertilizers / Geochemistry / Groundwater / human health / Humans / hydrochemistry / Iran / Isotope ratios / Isotopes / Land pollution / Land use / Mathematical models / mineral fertilizers / Municipal wastes / Municipal wastewater / Nitrates / Nitrification / Nitrogen / Organic nitrogen / Original Paper / Parameter identification / pollution / Pollution control / Probability theory / Public Health / Rainy season / Resource management / Seasons / Sensitivity analysis / Sewage / Soil / Soil chemistry / Soil contamination / soil organic nitrogen / Soil Science & Conservation / Soils / Stable isotopes / Terrestrial Pollution / Urban areas / Water resources / Wet season / World Health Organization