Pollution Mechanisms and Source Apportionment of Typical Pollutants in Aquatic Environments: Current Insights and Future Directions

1. Introduction

As a critical component of the Earth’s ecosystem, aquatic environments are under sustained pressure from multiple pollution sources, including industrial and agricultural activities, urban runoff, wastewater treatment plant effluent, and atmospheric deposition [1]. The residues, transport, and transformation of typical pollutants (e.g., heavy metals, persistent organic pollutants, microplastics, nutrients (N, P), and dissolved organic matter (DOM)) in water bodies have posed potential threats to aquatic ecological safety and human health [2,3,4]. Although substantial efforts have been made over the past decades to prevent and control water pollution, significant knowledge gaps remain regarding the whole-process mechanisms of pollutant “source–pathway–sink”, particularly the urgent need for breakthroughs in precise source apportionment under complex pollution scenarios.

Accurate source apportionment of pollutants is the logical starting point for “targeted remediation” and “risk prevention and control” of aquatic environments. Traditional source identification methods often rely on single chemical signatures or statistical models, which struggle to address multi-source superposition, non-stationary emissions, and interactions among coexisting pollutants. In recent years, the rapid development of emerging approaches—such as multivariate statistical techniques, the Positive Matrix Factorization (PMF) model, stable isotope analysis, high-resolution mass spectrometry fingerprinting, and machine learning—has provided unprecedented tools for resolving pollution sources and transformation pathways from the molecular to the watershed scale [5,6,7,8]. However, how to standardize these advanced methods, reduce their cost, and apply them effectively in routine regulatory frameworks remains a core challenge.

This Special Issue focuses on the theme “Pollution Mechanisms and Source Apportionment of Typical Pollutants in Aquatic Environments”. It brings together a collection of original research articles and reviews. The contributions cover, for example, the sources and transport of DOM in surface water and groundwater, source apportionment of groundwater pollution based on the PMF model in a rapidly urbanized region; and the spatiotemporal distribution and removal efficiency of microplastics in wastewater treatment plants. These findings not only deepen our mechanistic understanding of the environmental behavior of pollutants but also demonstrate the applicability of multi-technique integrated source apportionment paradigms in real-world scenarios.

Looking forward, establishing an interdisciplinary framework that is “mechanism-driven, data-enabled, and regulation-oriented” will be key to solving complex water pollution challenges. This Special Issue aims to provide a platform for colleagues in water environment science, analytical chemistry, ecotoxicology, and environmental engineering to exchange recent advances and to inspire original explorations on early pollution warning, source control, and ecological restoration. We believe that the papers presented here will offer strong scientific support for source-level pollution reduction and aquatic ecosystem health protection and will also contribute to the development of more precise and forward-looking water quality management policies.

2. Main Contribution of This Special Issue

After a rigorous peer-review process, eleven papers have been selected for publication in this Special Issue. The contributions and implications of them are discussed below.

Wang et al. (Contribution 1) investigate the dynamic characteristics of dissolved organic matter (DOM) in surface water and groundwater within an intensive greenhouse agriculture catchment in northern China. The authors employed an integrated approach combining EEM-PARAFAC, two-dimensional correlation spectroscopy (2D-COS), self-organizing map (SOM) analysis, hydrochemical measurements, and stable water isotopes (δ¹⁸O and δD). The study found that irrigation pumping drives surface–groundwater mixing, with microbial degradation of organic fertilizers and domestic wastewater being important DOM sources. 2D-COS revealed that terrestrial humic substances preferentially change parallel to the river direction, while microbial humic substances are more sensitive vertically. SOM analysis validated the relationships among DOM components and their correlations with inorganic ions. The findings suggest that combining DOM parameters with geochemical indicators and multi-technique analyses can effectively elucidate DOM sources and migration pathways, providing scientific support for sustainable water resource management in greenhouse agricultural systems.

Wang et al. (Contribution 2) investigate the pollution mechanisms and driving factors of groundwater quality in typical industrial areas, taking Zibo City, Shandong Province, as the study area. The authors collected phreatic and karst confined groundwater samples during both dry and flood seasons and employed Piper diagrams, Gibbs plots, ion ratios, and principal component analysis (PCA). The results show that pore phreatic water exhibits higher exceedance rates of Na⁺, Cl⁻, and NO₃⁻ than karst-confined water. The main hydrochemical type is HCO₃·SO₄·Ca, but pore water shifts to HCO₃·SO₄·Cl·Ca in the dry season. Groundwater quality is primarily controlled by water–rock interactions and industrial activities, with seasonal and aquifer-specific differences. The findings highlight the need for customized strategies to mitigate groundwater quality decline in industrial regions.

Wang et al. (Contribution 3) investigate the spatial distribution and sources of sulfate (SO₄²⁻) in groundwater of the Hutuo River alluvial fan, a typical overexploited region in northern China. The authors employed hydrochemical analysis, multivariate statistics (PCA), and geostatistical techniques. The results show that sulfate concentrations are significantly higher in the river valley plain (175 mg/L) and upper alluvial fan (169 mg/L) than in the central fan (77.3 mg/L). Groundwater depth is identified as a critical factor controlling sulfate distribution (p < 0.001). The main sources of sulfate include industrial wastewater, domestic sewage, evaporite dissolution, and sulfide mineral oxidation, with overexploitation accelerating water–rock interactions. The study provides a spatially explicit framework for sulfate pollution control in overexploited aquifers.

Woods (Contribution 4) investigates why U.S. state regulators allow some facilities to discharge more water pollution than similar facilities elsewhere. The author analyzes effluent limits for biochemical oxygen demand (BOD) and total suspended solids (TSS) in National Pollutant Discharge Elimination System (NPDES) permits, using GIS, demographic data, and state political variables. The results show that facilities discharging into interstate rivers receive significantly higher (more lenient) discharge limits, supporting the environmental free-riding hypothesis. Higher poverty rates are associated with less stringent BOD limits, raising environmental justice concerns. More liberal state governments (for BOD) and stronger environmental interest groups (for TSS) lead to tighter permits. These findings indicate that subnational political factors and free-riding incentives shape water quality stringency permits.

Chen et al. (Contribution 5) investigate the spatiotemporal distribution and removal efficiency of microplastics (MPs) in a wastewater treatment plant (WWTP) in Zhengzhou, China. The authors collected influent, process effluent, final effluent, and sludge samples across summer, autumn, and winter, using density separation, H₂O₂ digestion, and Raman spectroscopy. Results show total MP removal efficiencies of 86% (summer), 81% (autumn), and 73% (winter), with fragments and granules dominating (>80%). Polypropylene (PP, 42.6%) and polyethylene terephthalate (PET, 31.8%) are the main polymers. Secondary treatment removed more MPs than tertiary treatment, and residual sludge retained substantial MP loads (14.2–29.1 n/g). The study highlights that WWTPs remain a significant source of MPs to the environment, urging improved management strategies.

Sun et al. (Contribution 6) investigate river hydrograph separation in a hilly catchment with diverse land uses in Southwest China. The authors propose a novel multi-tracer approach combining the ratio of two conservative fluorescent DOM components (C1/C2), ion ratios (Ca²⁺/NO₃⁻, Ca²⁺/K⁺, and Mg²⁺/NO₃⁻), and oxygen-18 (δ¹⁸O), using the MixSIAR model. For a rain event with the longest preceding dry period, a set of four tracers successfully distinguished up to eight water sources at the catchment outlet and five sources in a nested agricultural–forestry drainage area. Drier antecedent soil moisture favored more qualified tracers. The study provides a useful tool for prioritizing water source areas for pollution protection in complex landscapes.

Wang et al. (Contribution 7) investigate natural background levels (NBLs) and contamination mechanisms of shallow groundwater in an overexploited region of Xingtai City, North China Plain. Sixty groundwater samples were analyzed using Piper diagrams, cumulative-probability statistics, contamination indices, and principal component analysis (PCA). The dominant hydrochemical types are HCO₃·Na and SO₄·Cl·Na. NBLs for Na⁺, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻, and NO₃⁻ are 32.3, 34.1, 17.8, 46.2, 66.4, and 0.886 mg/L, with corresponding thresholds of 116, 54.6, 33.9, 248, 258, and 44.7 mg/L. Based on thresholds, 56.7% of sites are anthropogenically contaminated. PCA reveals that groundwater over-extraction, industrial activities, water–rock interaction, agricultural fertilization, and domestic sewage are key contamination drivers. The study provides a scientific basis for pollution control in overexploited aquifers.

Wang et al. (Contribution 8) investigate groundwater pollution sources in Shenzhen, a highly urbanized Chinese city. The authors integrated multivariate statistics, the Positive Matrix Factorization (PMF) model, and GIS spatial interpolation. Results show that groundwater is weakly acidic to neutral, with high exceedance rates for pH, NH₄⁺, COD, Mn, and Fe (up to 67.1%). The dominant hydrochemical type is HCO₃·Ca·Na, controlled primarily by silicate weathering. The PMF model identified three pollution sources: domestic/industrial wastewater (43.9%), water–rock interaction (37.0%), and agricultural fertilizers (19.1%). Urban groundwater quality is mainly affected by wastewater discharge, while agricultural areas suffer from excessive fertilizer use. The study provides a scientific basis for groundwater protection in rapidly urbanizing regions.

Yang et al. (Contribution 9) investigate water quality characteristics and solute sources of the Jinqian River, an agricultural tributary of the Danjiangkou Reservoir source area for China’s South-to-North Water Diversion Project. The authors collected river water across dry, normal, and flood seasons, using hydrochemical analysis and multivariate statistics. Results show slightly alkaline pH (7.55–8.30), with total nitrogen exceeding Class III surface water standards in all seasons, indicating significant human impact. Ionic sources are Cl⁻ and Na⁺ from halite dissolution; Ca²⁺, Mg²⁺, and HCO₃⁻ from carbonate-silicate weathering; and SO₄²⁻ from evaporite dissolution. Principal component analysis identifies four controlling factors: agricultural fertilizers, halite weathering, evaporite dissolution, and domestic sewage. The study provides a quantitative basis for managing nutrients and salts in agricultural rivers.

Liu et al. (Contribution 10) investigate groundwater hydrochemical evolution and pollution sources in the Datong River Basin, an arid region of northwestern China. Thirty-seven groundwater samples were analyzed using hydrochemical methods and the Positive Matrix Factorization (PMF) model. The dominant water type is HCO₃-Ca(Mg), controlled by silicate and carbonate weathering. The water quality index classifies 70.3% of samples as excellent. PMF resolves three sources: natural weathering (19.2%, enriched in Mn, Na⁺, Cl⁻), a mixed source (67.5%, domestic sewage + agriculture + rock weathering), and industrial wastewater (13.3%, dominated by Fe). The mixed source contributes most major ions and COD, while the industrial source accounts for 75.7% of Fe. The study provides a basis for groundwater management in arid basins.

Wu et al. (Contribution 11) investigate microbial driving mechanisms of phosphorus cycling in the Chishui River, southwestern China. Water quality parameters and metagenomic analysis were conducted on samples collected in summer and autumn. Results show higher total phosphorus and soluble reactive phosphorus in summer, while manganese peaks in autumn and correlates positively with SRP, suggesting sediment release. Functional genes for phosphorus cycling differ significantly between seasons: summer enriches high-affinity phosphate transporter (pstB), inorganic phosphate dissolution (pqqC), and polyphosphate decomposition (ppx); autumn enriches phosphonate (phn) and glycerophosphate (ugpQ) genes. Proteobacteria dominate the microbial community. Environmental factors (Fe, DO, DOC, and pH) jointly regulate functional gene composition. The study highlights microbial regulation of phosphorus biogeochemistry in river ecosystems.

3. Conclusions

The papers in this Special Issue highlight key advances in understanding pollution mechanisms and source apportionment in aquatic environments. First, water quality is shaped by the interplay of natural processes and human activities. Intensive greenhouse agriculture drives surface–groundwater mixing and alters dissolved organic matter (Contribution 1). Rock weathering and industrial activities control groundwater quality in industrial areas (Contribution 2); over-exploitation accelerates sulfate release (Contribution 3); and in arid catchments, natural weathering dominates, but sewage, fertilizers, and industry add significant pollution (Contribution 10).

Second, advanced analytical tools enable robust source identification. Combining EEM-PARAFAC, 2D-COS, SOM, and stable isotopes unravels DOM transformation pathways (Contribution 1). A Bayesian mixing model using DOM fluorescence ratios, ion ratios, and δ¹⁸O distinguishes up to eight water sources in hilly catchments (Contribution 6). Metagenomic sequencing reveals seasonal shifts in phosphorus-cycling genes (e.g., pstB and phn) and their environmental drivers (Contribution 11).

Third, long-term monitoring captures temporal variability critical for adaptive management. Seasonal monitoring of a wastewater treatment plant shows microplastic removal peaks in summer (86%) and is lowest in winter (73%), with sludge retaining substantial loads (Contribution 5). In an agricultural river, total nitrogen exceeds standards year-round, with solute dynamics following dilution, flushing, and reservoir-modulated patterns (Contribution 9).

Other important findings include political and regulatory factors: U.S. interstate river discharges receive more lenient permits (free-riding); higher poverty correlates with higher BOD limits (environmental justice); and liberal governments enforce stricter permits (Contribution 4). Determining natural background levels and thresholds in over-exploited aquifers shows 56.7% of sites are anthropogenically contaminated (Contribution 7). PMF quantification in urbanized Shenzhen attributes pollution to domestic/industrial wastewater (43.9%), water–rock interaction (37.0%), and fertilizers (19.1%) (Contribution 8). Collectively, these studies demonstrate that an integrated understanding of natural processes, human pressures, seasonal dynamics, and advanced methodologies is essential for effective water quality management and pollution control.