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

High concentrations of NO3̄ in water resources are detrimental to both human health and aquatic ecosystems. Identification of NO3̄ sources and biogeochemical processes is a crucial step in managing and controlling NO3̄ pollution. In this study, land use, hydrochemical data, dual stable isotopic ratios and Bayesian Stable Isotope Mixing Models (BSIMM) were integrated to identify NO3̄ sources and estimate their proportional contributions to the contamination of the Karaj Urban Aquifer (Iran). Elevated NO3̄ concentrations indicated a severe NO3̄ pollution, with 39 and 52% of groundwater (GW) samples displaying the concentrations of NO3̄ in exceedance of the World Health Organization (WHO) standard of 50 mg NO3̄ L-1 in the rainy and dry seasons, respectively. Dual stable isotopes inferred that urban sewage is the main NO3̄ source in the Karaj Plain. The diagram of NO3̄/Cl‾ versus Cl‾ confirmed that municipal sewage is the major source of NO3̄. Results also showed that biogeochemical nitrogen dynamics are mainly influenced by nitrification, while denitrification is minimal. The BSIMM model suggested that NO3̄ 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 NO3̄ 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 NO3̄ source identification.

Determining nitrate pollution sources in the Kabul Plain aquifer (Afghanistan) using stable isotopes and Bayesian stable isotope mixing model.

The Kabul urban aquifer (Afghanistan), which is the main source of drinking water for Kabul city's inhabitants, is highly vulnerable to anthropogenic pollution. In this study, the geochemistry of major ions (including reactive nitrogen species such as NO3-, NO2-, and NH4+) and stable isotope ratios (δ15N-NO3-, δ18O-NO3-, δ18O-H2O, and δ2H-H2O) of surface and groundwater samples from the Kabul Plain were analyzed over two sampling periods (dry and wet seasons). A Bayesian stable isotope mixing model (BSIMM) was also employed to trace potential nitrate sources, transformation processes, and proportional contributions of nitrate sources in the Kabul aquifer. The plotting of δ15N-NO3- against δ18O-NO3̄ (δ15N-NO3- and δ18O-NO3- values ranged from +4.8 to +25.4‰ and from -11.7 to +18.6‰, respectively) suggests that NO3- primarily originated from the nitrification of sewage rather than artificial fertilizer. The plotting of δ15N-NO3- versus NO3-/Cl- ratios also supported the assumption that sewage is the dominant nitrate source. The results indicate that denitrification did not influence the NO3- isotopic composition in the Kabul aquifer. The BSIMM model suggests that nitrate in the dry season originated mainly from sewage (~81%), followed by soil organic N (10.5%), and chemical fertilizer (8.5%). In the wet season, sewage (~87.5%), soil organic N (6.7%), and chemical fertilizer (5.8%) were the main sources of NO3- in the Kabul aquifer. Effective land management measures should be taken to improve the sewage collection system in the Kabul Plain.

Simplifying and improving the extraction of nitrate from freshwater for stable isotope analyses.

Determining the isotopic composition of nitrate (NO(3)(-)) in water can prove useful to identify NO(3)(-) sources and to understand its dynamics in aquatic systems. Among the procedures available, the 'ion-exchange resin method' involves extracting NO(3)(-) from freshwater and converting it into solid silver nitrate (AgNO(3)), which is then analysed for (15)N/(14)N and (18)O/(16)O ratios. This study describes a simplified methodology where water was not pre-treated to remove dissolved organic carbon (DOC) or barium cations (added to precipitate O-bearing contaminants), which suited samples with high NO(3)(-) (≥ 00 µM or 25 mg L(-1) NO(3)(-)) and low DOC (typically < 17 µM of C or 5 mg L(-1) C) levels. % N analysis revealed that a few AgNO(3) samples were of low purity (compared with expected % N of 8.2), highlighting the necessity to introduce quality control/quality assurance procedures for silver nitrate prepared from field water samples. Recommendations are then made to monitor % N together with % O (expected at 28.6, i.e. 3.5 fold % N) in AgNO(3) in order to better assess the type and gravity of the contamination as well as to identify potentially unreliable data.

Carbohydrate-deficient transferrin isoforms measured by capillary zone electrophoresis for detection of alcohol abuse.

BACKGROUND: Measurements of carbohydrate-deficient transferrin (CDT) are used as markers of alcohol abuse. We developed a capillary zone electrophoresis (CZE) method aimed at improving accuracy of CDT testing. METHODS: We studied 111 alcohol abusers with Alcohol Use Disorders Identification Test scores >11 and 50 teetotalers. CZE was performed with a P/ACE 5500, fused-silica capillaries, and a CEofix CDT reagent set. After iron saturation, sera were loaded by low-pressure injection, separated at 28 kV, and monitored at 214 nm. We identified the transferrin isoforms by migration times, treatment with 100 U/L neuraminidase, and immunosubtraction with anti-human transferrin and anti-C-reactive protein antibodies. We compared CZE results with current biological markers of alcohol abuse, including the %CDT turbidimetric immunoassay. RESULTS: Migration times of the isoforms were identical in both populations. Asialotransferrin was missing in teetotalers but present in 92% of alcohol abusers. Disialotransferrin was higher in those who consumed excessive amounts of alcohol, whereas mean trisialotransferrin concentration was not affected by alcohol abuse. At cutoffs to maximize sensitivity and specificity, these values were 0.92 and 1 [mean ROC area (MRa), 0.96; 95% confidence interval (CI), 0.93-0.99] for asialotransferrin; 0.84 and 0.94 for the sum of asialo- + disialotransferrin (MRa, 0.94; 95% CI, 0.91-0.98); 0.79 and 0.94 for disialotransferrin (MRa, 0.89; 95% CI, 0.84-0.94); 0.62 and 0.53 for trisialotransferrin (MRa, 0.58; 95% CI, 0.49-0.68); 0.79 and 0.82 for a 3% %CDT; and 0.83 and 0.69 for a 2.6% cutoff (MRa, 0.87; 95% CI, 0.81-0.92). Current markers lack sensitivity (<0.65). Transferrins were not significantly correlated with serum enzymes and mean erythrocyte volume. CONCLUSIONS: CZE-isolated desialylated transferrin isoforms allowed differentiation between chronic alcohol abusers and teetotalers.