Effect and genesis of soil nitrogen loading and hydrogeological conditions on the distribution of shallow groundwater nitrogen pollution in the North China Plain

The new region demarcation framework for implementing the joint prevention and control of groundwater pollution: A case study in western of Bohai Bay, China

The joint groundwater pollution prevention and control (GPPC) strategy has been extensively implemented to address the coastal region groundwater pollution challenges in China. However, regional groundwater pollution control and treatment efficiency cannot achieve the expected results due to the lack of regional priority control orders and accurate restoration levels. Thus, this study developed a new region demarcation framework method for delineating GPPC zones, in tandem with a comprehensive pollution index method, the DRASTIC model, source apportionment. To validate the new methodological framework, a case study of groundwater pollution in Qinhuangdao, the western of Bohai Bay, China, was implemented to calculate pollution prevention and control zoning. In total, 340 groundwater samples from shallow aquifers with 9 target pollutants (NO3-, NO2-, NH4+, As, Cd, Cr, Cu, Pb, and Ni) were selected as the dataset for GPPC regionalization. The results showed that GPPC zoning further clarified the direction of groundwater pollution protection and management in Qinhuangdao. Compared to the traditional method, the new GPPC zoning better reflects groundwater mobility characteristics and pollution transport and enrichment patterns in terms of groundwater functional integrity and delineation. This new regional demarcation framework method contributes to providing support for the fine division of groundwater pollution zoning and precise pollution control for groundwater resource management in China.

Anthropogenic impacts and quantitative sources of nitrate in a rural-urban canal using a combined PMF, δ15N/δ18O-NO3-, and MixSIAR approach

Nitrate (NO3-) pollution in irrigation canals is of great concern because it threatens canal water use; however, little is known about it at present. Herein, a combination of positive matrix factorization (PMF), isotope tracers, and Mixing Stable Isotope Analysis in R (MixSIAR) was developed to identify anthropogenic impacts and quantitative sources of NO3- in a rural-urban canal in China. The NO3- concentration (0.99-1.93 mg/L) of canal water increased along the flow direction and was higher than the internationally recognized eutrophication risk value in autumn and spring. The inputs of the Fuhe River, NH4+ fertilizer, soil nitrogen, manure & sewage, and rainfall were the main driving factors of canal water NO3- based on principal component analysis and PMF, which was supported by evidence from δ15N/δ18O-NO3-. According to the chemical and isotopic analyses, nitrogen transformation was weak, highlighting the potential of δ15N/δ18O-NO3- to trace NO3- sources in canal water. The MixSIAR and PMF results with a <15% divergence emphasized the predominance of the Fuhe River (contributing >50%) and anthropogenic impacts (NH4+ fertilizer plus manure & sewage, >37%) on NO3- in the entire canal, reflecting the effectiveness of the model analysis. According to the MixSIAR model, (1) higher NO3- concentration in canal water was caused by the general enhancement of human activities in spring and (2) NO3- source contributions were associated with land-use patterns. The high contributions of NH4+ fertilizer and manure & sewage showed inverse spatial variations, suggesting the necessity of reducing excessive fertilizer use in the agricultural area and controlling blind wastewater release in the urban area. These findings provide valuable insights into NO3- dynamics and fate for sustainable management of canal water resources. Nevertheless, long-term chemical and isotopic monitoring with alternative modeling should be strengthened for the accurate evaluation of canal NO3- pollution in future studies.

Revealing the drivers and genesis of NO3-N pollution classification in shallow groundwater of the Shaying River Basin by explainable machine learning and pathway analysis method

Nitrate (NO3-N), as one of the ubiquitous contaminants in groundwater worldwide, has posed a serious threat to public health and the ecological environment. Despite extensive research on its genesis, little is known about the differences in the genesis of NO3-N pollution across different concentrations. Herein, a study of NO3-N pollution concentration classification was conducted using the Shaying River Basin as a typical area, followed by examining the genesis differences across different pollution classifications. Results demonstrated that three classifications (0-9.98 mg/L, 10.14-27.44 mg/L, and 28.34-136.30 mg/L) were effectively identified for NO3-N pollution using Jenks natural breaks method. Random forest exhibited superior performance in describing NO3-N pollution and was thereby affirmed as the optimal explanatory method. With this method coupling SEMs, the genesis of different NO3-N pollution classifications was proven to be significantly different. Specifically, strongly reducing conditions represented by Mn2+, Eh, and NO2-N played a dominant role in causing residual NO3-N at low levels. Manure and sewage (represented by Cl-) leaching into groundwater through precipitation is mainly responsible for NO3-N in the 10-30 mg/L classification, with a cumulative contribution rate exceeding 80 %. NO3-N concentrations >30 mg/L are primarily caused by the anthropogenic loads stemming from manure, sewage, and agricultural fertilization (represented by Cl- and K+) infiltrating under precipitation in vulnerable hydrogeological conditions. Pathway analysis based on standardized effect and significance further confirmed the rationality and reliability of the above results. The findings will provide more accurate information for policymakers in groundwater resource management to implement effective strategies to mitigate NO3-N pollution.

Revealing discrepancies and drivers in the impact of lomefloxacin on groundwater denitrification throughout microbial community growth and succession

The coexistence of antibiotics and nitrates has raised great concern about antibiotic's impact on denitrification. However, conflicting results in these studies are very puzzling, possibly due to differences in microbial succession stages. This study investigated the effects of the high-priority urgent antibiotic, lomefloxacin (LOM), on groundwater denitrification throughout microbial growth and succession. The results demonstrated that LOM's impact on denitrification varied significantly across three successional stages, with the most pronounced effects exhibited in the initial stage (53.8% promotion at 100 ng/L-LOM, 84.6% inhibition at 100 μg/L-LOM), followed by the decline stage (13.3-18.2% inhibition), while no effect in the stable stage. Hence, a distinct pattern encompassing susceptibility, insusceptibility, and sub-susceptibility in LOM's impact on denitrification was discovered. Microbial metabolism and environment variation drove the pattern, with bacterial numbers and antibiotic resistance as primary influencers (22.5% and 15.3%, p < 0.01), followed by carbon metabolism and microbial community (5.0% and 3.68%, p < 0.01). The structural equation model confirmed results reliability. Bacterial numbers and resistance influenced susceptibility by regulating compensation and bacteriostasis, while carbon metabolism and microbial community impacted energy, electron transfer, and gene composition. These findings provide valuable insights into the complex interplay between antibiotics and denitrification patterns in groundwater.

Nitrogen removal performance of aerobic denitrifying bacteria enhanced by an iron-anode pulsed electric field

Pulsed electric field (PEF) technology has attracted considerable attention because it can efficiently treat pollutants that are difficult to degrade. In this study, a PEF system using iron as the electrode was constructed to investigate the effect of PEF-Fe on the growth and metabolism of aerobic denitrifying bacteria and the effectiveness of wastewater nitrogen removal. The chemical oxygen demand, NO3--N and nitrate removal rates were 98.93%, 97.60% and 24.40 mg·L-1·h-1, respectively, under optimal conditions. As confirmed in this study, PEF-Fe could improve the key enzyme activities of W207-14. Scanning electron microscopy revealed that the surface of PEF-Fe-treated W207-14 was intact and smooth without any irreversible deformation. Flow cytometry combined with fluorescence staining analysis also confirmed reversible electroporation on the cell membrane surface of PEF-Fe-treated W207-14. Differentially expressed gene enrichment analysis showed that PEF-Fe activated the transmembrane transport function of ATP-binding cassette transporte (ABC) transport proteins and enhanced the cell membrane permeability of aerobic denitrifying bacteria. The significant differential expression of iron-sulphur cluster proteins facilitated the regulation of electron transport and maintenance of the dynamic balance of iron ions within the PEF-Fe system.