Abstract:

Rapid industrialization in China has imposed significant risks to regional ecosystems and public health owing to the persistent release of diverse hazardous pollutants from industries. The intricate interactions between soil and groundwater systems exacerbate cross-media contamination. Existing environmental criteria systems are often inadequate for systematically evaluating pollutant migration process across different media and their associated health risks because they fail to account for the intricate interactions among various environmental factors. To address these shortcomings, this study introduces the Soil and Groundwater Multi-Element Synergistic Environmental Criteria for Human Health (S&G MESEC_-HH), a comprehensive theoretical framework designed to assess the synergistic effects of multiple environmental factors on pollutant behavior and human health. The S&G MESEC_-HH framework integrates four core elements: 1) Pollutant Characteristics, including contaminant types, chemical forms, and physicochemical properties, which critically determine mobility and bioavailability. 2) Hydrogeological Conditions, including soil stratification, groundwater level fluctuations, and flow direction. 3) Soil Physicochemical Properties, such as pH, organic matter content, and particle size distribution. 4) Meteorological Factors, which primarily include temperature and precipitation patterns. This study emphasizes that the characteristics of pollutants play a crucial role in determining their mobility and bioavailability. For instance, heavy metals and organic pollutants exhibit different behaviors in soil and groundwater systems because of their chemical forms and interactions with soil particles. Understanding these characteristics is essential for predicting the behavior of pollutants in the environment and assessing their potential risks to human health. Additionally, the study delineates three principal synergistic mechanisms that dictate pollutant transport and transformation within the soil-groundwater continuum: 1) Chemical Synergy, which involves multiphase partitioning and valence state transformations of contaminants. 2) Physical Synergy, characterized by processes such as advection-diffusion and adsorption-desorption. 3) Biological Synergy, pertains to microbial metabolic activities that can alter the fate of pollutants. These mechanisms underscore the intricacy of pollutant interactions and the necessity of a multifaceted approach to environmental risk assessment. By systematically analyzing these multi-factor coupled mechanisms, the S&G MESEC_-HH framework offers an approach to understand how pollutants migrate and transform in complex environmental settings. This paradigm not only augments the prognostic capabilities regarding contaminant behavior but also affords a comprehensive appraisal of the public health risks associated with exposure to such pollutants and their environmental persistence. The S&G MESEC_-HH framework comprises several critical elements that collectively influence the behavior of pollutants in soil and groundwater systems. These factors are essential for understanding the complex dynamics of contaminant transport and transformations. The key elements identified include: 1) Stratigraphic Heterogeneity, wherein variability in geological strata notably affects pollutant migration; disparities in permeability, adsorption capacity, and ion exchange potential across diverse lithologies govern contaminant mobilization within subsurface matrices. 2) Hydrogeological Parameters, such as hydraulic conductivity, porosity, and dispersivity, are indispensable for characterizing groundwater flow regimes and contaminant transport kinetics. These parameters directly dictate the pollutant migration pathways, residence times, and transformation rates. 3) Groundwater Depth and Fluctuations, since groundwater table depth and temporal variations can modulate soil moisture conditions, redox states, and microbial activity, thereby influencing the mobilization and retention of contaminants, particularly heavy metals. 4) Soil Gas, where VOCs present in soil gas can significantly affect the extent of pollution. The distribution and concentration of VOCs in the gas phase can lead to underestimations of environmental risks if not considered adequately. 5) Non-Aqueous Phase Liquids (NAPLs), whose presence in free, dissolved, or adsorbed phases poses persistent contamination challenges. The density-dependent behavior of both light and dense NAPLs in heterogeneous geological media complicates the prediction of contaminant plumes. 6) Microbial Activity, wherein indigenous microbial communities facilitate the biodegradation of organic pollutants. Their metabolic processes can transform contaminants, thereby affecting their toxicity and mobility. Environmental factors, such as oxygen levels, nutrient availability, temperature, and pH critically influence microbial pathways, thereby affecting contaminant toxicity, persistence, and degradation kinetics. 7) Climatic and Meteorological Factors, including temperature fluctuations and precipitation patterns, govern the physical, chemical, and biological processes that regulate the fate of contaminants. Variations in seasonal temperature may alter the solubility and sorption characteristics of organic pollutants, whereas rainfall can affect soil moisture and leaching. By integrating these elements into the S&G MESEC_-HH framework, this study aims to provide a comprehensive understanding of the multifactorial interactions that govern pollutant behavior, thereby enhancing risk assessment fidelity and informing the development of robust environmental management strategies and resilience metrics. Moreover, this study delves into the ramifications of the S&G MESEC_-HH framework for regulatory and environmental management practices. By providing a theoretical basis for the systematic assessment of health risks in complex polluted environments, this framework can guide policymakers in establishing more effective environmental regulations and remediation strategies in the future. The integration of multi-element interactions into environmental criteria can lead to more accurate risk assessments, ultimately protecting public health and the environment. The S&G MESEC_-HH framework also opens avenues for future research, particularly in terms of risk communication. Furthermore, the framework’s adaptability to incorporate emerging technologies, such as remote sensing and machine learning, facilitates the enhancement of data collection and analysis. These advancements have the potential to improve the precision of predictions regarding pollutant behavior, thereby facilitating the timely identification of contamination events. Consequently, these advancements can help protect public health. Additionally, the implementation of the S&G MESEC_-HH framework is versatile, allowing adaptation to different geographical contexts, thereby ensuring its suitability for diverse environmental conditions and pollutant profiles. This adaptability is imperative for addressing the unique challenges faced by different regions, particularly in areas with varying industrial activities and ecological sensitivities. By adapting the framework to local conditions, it can provide more relevant and actionable insights into the environmental management. In conclusion, this study establishes a foundation for subsequent research endeavors aimed at refining the S&G MESEC_-HH framework and its application in real-world applications. This underscores the necessity for continuous research on the interactions among diverse environmental factors and their collective impact on pollutant behavior and human health. These findings emphasize the significance of interdisciplinary collaboration in addressing the multifaceted challenges posed by soil and groundwater pollution, ultimately contributing to the establishment of effective pollution prevention and remediation strategies.

Key words: Taihu Lake, nonsteroidal anti-inflammatory drugs, bacterial communities, antibiotic resistance genes, intI1

摘要：

非甾体消炎药（Nonsteroidal anti-inflammatory drugs，NSAIDs）在湖泊水环境的残留已受到广泛关注，但其对于湖泊水体中微生物群落及抗生素抗性基因（Antibiotic resistance genes，ARGs）的潜在影响尚未明晰。以太湖西部沿岸区、竺山湾、梅梁湾、贡湖湾和湖心区为研究区域，分析了水体中4种典型NSAIDs的赋存特征，利用相关性分析和共现网络分析探究NSAIDs与细菌群落及ARGs的关系，并通过偏最小二乘路径模型（PLS-PM）定量解析NSAIDs对ARGs影响。 结果表明，酮洛芬和双氯芬酸是太湖水体中浓度最高的NSAIDs，其质量浓度范围分别为29.0-49.5 ng·L⁻¹和2.4-10.4 ng·L⁻¹，且太湖西北部湖区的总NSAIDs浓度高于中东部湖区。不同湖区细菌群落多样性空间差异显著（p<0.05），hgcl clade、Microcystis PCC-7914和Clade Ⅲ_norank是太湖水体中的优势菌属，其相对丰度的空间差异与NSAIDs趋势一致。太湖不同湖区水体中9种ARGs的总丰度为6.70×10¹⁰-1.76×10¹¹ copies·L⁻¹，其中主要ARGs类型为ermB、mphA和sul1，其空间差异也与NSAIDs具有一致性。此外，NSAIDs与太湖水体中ARGs的潜在宿主呈显著正相关（p<0.05）。偏最小二乘路径模型（Partial least squares path model，PLS-PM）分析结果表明，NSAIDs主要通过增加可移动遗传原件（Mobile genetic elements，MGEs）的丰度促进ARGs的富集，也可通过改变细菌群落多样性进而调控ARGs的赋存与传播。该研究为评估NSAIDs在自然水体中的生态风险提供了科学依据。

关键词: 太湖, 非甾体消炎药, 细菌群落, 抗生素抗性基因, intI1