Using Geochemistry, Stable Isotopes and Statistical Tools to Estimate the Sources and Transformation of Nitrate in Groundwater in Jinan Spring Catchment, China

Nitrate (NO<sub>3</sub><sup>-</sup>) pollution resulting from anthropogenic activities represents one of the most prevalent environmental issues in karst spring catchments of northern China. In June 2021, a comprehensive study was conducted in the Jinan Spring Catchment (JSC), where 30 groundwater and surface water samples were collected. The sources and spatial distribution of nitrate pollution were systematically investigated through hydrochemical analysis combined with dual-isotope tracing techniques (δ<sup>15</sup>N<sub>NO3</sub> and δ<sup>18</sup>O<sub>NO3</sub>). Analytical results revealed that the predominant anion and cation sequences were HCO<sub>3</sub><sup>-</sup> > SO<sub>4</sub><sup>2-</sup> > Cl<sup>-</sup> > NO<sub>3</sub><sup>-</sup> and Ca<sup>2+</sup> > Na<sup>+</sup> > Mg<sup>2+</sup> > K<sup>+</sup>, respectively, with HCO<sub>3</sub>·SO<sub>4</sub>-Ca identified as the primary hydrochemical type. Notably, the average NO<sub>3</sub><sup>-</sup> concentration in groundwater (46.62 mg/L) significantly exceeded that in surface water (4.96 mg/L). Among the water samples, 11 locations exhibited substantial nitrate pollution, demonstrating an exceedance rate of 42%. Particularly, the NO<sub>3</sub><sup>-</sup>-N concentrations in both the upstream recharge area and downstream drainage area were markedly higher than those in the runoff area. The spatial distribution of NO<sub>3</sub><sup>-</sup> concentrations was primarily influenced by mixing processes, with no significant evidence of denitrification observed. The isotopic compositions ranged from -1.42‱ to 12.79‱ for δ<sup>15</sup>N<sub>NO3</sub> and 0.50‱ to 15.63‱ for δ<sup>18</sup>O<sub>NO3</sub>. Bayesian isotope mixing model (MixSIAR) analysis indicated that domestic sewage and manure constituted the principal nitrate sources, contributing 37.1% and 56.9% to groundwater and surface water, respectively. Secondary sources included soil organic nitrogen, rainfall and fertilizer NH<sub>4</sub><sup>+</sup>, and chemical fertilizers, while atmospheric deposition showed the lowest contribution rate. Additionally, potential mixing of soil organic nitrogen with chemical fertilizer was identified.

Authors

Institutions

Publication Details

Journal
Toxics
Published
2025-05-14
DOI
https://doi.org/10.3390/toxics13050393
Citations
1
Primary Topic
Groundwater and Isotope Geochemistry
Type
article
Field-Weighted Citation Impact
1.34

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Geochemistry, Stable Isotopes and Statistical Tools to Estimate the Sources and Transformation of Nitrate in Groundwater in Jinan Spring Catchment, China

Mingsen Wang, Xuequn Chen, Kairan Wang, Xin Zhang et al.
1 citations
Toxics
Groundwater and Isotope Geochemistry
1.34
article

Using Geochemistry, Stable Isotopes and Statistical Tools to Estimate the Sources and Transformation of Nitrate in Groundwater in Jinan Spring Catchment, China

Mingsen Wang, Xuequn Chen, Kairan Wang, Xin Zhang, Mingyuan Fan, Hongbo Wang, Zhen Wu
article en
1 citations

Abstract

Nitrate (NO<sub>3</sub><sup>-</sup>) pollution resulting from anthropogenic activities represents one of the most prevalent environmental issues in karst spring catchments of northern China. In June 2021, a comprehensive study was conducted in the Jinan Spring Catchment (JSC), where 30 groundwater and surface water samples were collected. The sources and spatial distribution of nitrate pollution were systematically investigated through hydrochemical analysis combined with dual-isotope tracing techniques (δ<sup>15</sup>N<sub>NO3</sub> and δ<sup>18</sup>O<sub>NO3</sub>). Analytical results revealed that the predominant anion and cation sequences were HCO<sub>3</sub><sup>-</sup> > SO<sub>4</sub><sup>2-</sup> > Cl<sup>-</sup> > NO<sub>3</sub><sup>-</sup> and Ca<sup>2+</sup> > Na<sup>+</sup> > Mg<sup>2+</sup> > K<sup>+</sup>, respectively, with HCO<sub>3</sub>·SO<sub>4</sub>-Ca identified as the primary hydrochemical type. Notably, the average NO<sub>3</sub><sup>-</sup> concentration in groundwater (46.62 mg/L) significantly exceeded that in surface water (4.96 mg/L). Among the water samples, 11 locations exhibited substantial nitrate pollution, demonstrating an exceedance rate of 42%. Particularly, the NO<sub>3</sub><sup>-</sup>-N concentrations in both the upstream recharge area and downstream drainage area were markedly higher than those in the runoff area. The spatial distribution of NO<sub>3</sub><sup>-</sup> concentrations was primarily influenced by mixing processes, with no significant evidence of denitrification observed. The isotopic compositions ranged from -1.42‱ to 12.79‱ for δ<sup>15</sup>N<sub>NO3</sub> and 0.50‱ to 15.63‱ for δ<sup>18</sup>O<sub>NO3</sub>. Bayesian isotope mixing model (MixSIAR) analysis indicated that domestic sewage and manure constituted the principal nitrate sources, contributing 37.1% and 56.9% to groundwater and surface water, respectively. Secondary sources included soil organic nitrogen, rainfall and fertilizer NH<sub>4</sub><sup>+</sup>, and chemical fertilizers, while atmospheric deposition showed the lowest contribution rate. Additionally, potential mixing of soil organic nitrogen with chemical fertilizer was identified.

ToxicsVol. 13(5)
Shandong Provincial Water Resources Research Institute (CN), Shandong Jianzhu University (CN)
Natural Science Foundation of Shandong Province, Postdoctoral Innovation Project of Shandong Province
Clean water and sanitation
Openalex Percentile: Top 20%
Groundwater and Isotope Geochemistry
1.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.