Aging behaviors intensify the impacts of microplastics on nitrate bioreduction-driven nitrogen cycling in freshwater sediments

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-07-01 Epub Date: 2025-03-05 DOI:10.1016/j.watres.2025.123448
Yuecheng She , Liying Wu , Xin Qi , Siyu Sun , Zhengkui Li
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Abstract

Microplastics (MPs) inevitably undergo aging processes in natural environments; however, how aging behaviors influence the interactions between MPs exposures and nitrate bioreduction in freshwater sediments remains poorly understood. Here, we explored the distinct impacts of virgin and aged MPs (polystyrene (PS) and polylactic acid (PLA)) on nitrate bioreduction processes in lake sediments through a long-term microcosm experiment utilizing the 15N isotope tracing technique and molecular analysis. Compared to virgin MPs, aged PLA significantly increased the rates of denitrification, anaerobic ammonium oxidation (anammox), and dissimilatory nitrate reduction to ammonium (DNRA) (p < 0.05), facilitating sediment nitrogen loss, while aged PS only significantly improved the rates of DNRA by 272–297 % and contributed to nitrogen retention in sediments. Metagenomic sequencing demonstrated that a more significant enrichment of functional genes responsible for nitrate bioreduction pathways occurred with aged MPs exposures than with virgin MPs. By combining analyses of MPs aging traits and the key drivers of nitrate bioreduction, we revealed that aging behaviors directly regulated sediment nutrient status (e.g., DOC/NOx ratio) and microbiological properties (from genes to bacteria), thereby further determining the activity of nitrate bioreduction. This work provides new insights into the impacts of aged MPs on sediment nitrate reduction and highlights the role of MPs aging in future assessments of long-term MPs pollution in freshwater ecosystems.

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老化行为加剧了微塑料对淡水沉积物中硝酸盐生物还原驱动的氮循环的影响
微塑料(MPs)在自然环境中不可避免地经历老化过程;然而,衰老行为如何影响淡水沉积物中MPs暴露与硝酸盐生物还原之间的相互作用仍然知之甚少。本研究利用15N同位素示踪技术和分子分析,通过长期的微观实验,探讨了未加工和老化的MPs(聚苯乙烯(PS)和聚乳酸(PLA))对湖泊沉积物中硝酸盐生物还原过程的不同影响。与未处理的MPs相比,老化PLA显著提高了反硝化、厌氧氨氧化(anammox)和异化硝态氮还原(DNRA)速率(p<0.05),促进了沉积物氮的损失,而老化PS仅显著提高了DNRA速率(27.7% ~ 297%),并有助于沉积物中的氮潴留。宏基因组测序表明,与未暴露的MPs相比,衰老MPs暴露中负责硝酸盐生物还原途径的功能基因的富集更为显著。通过对MPs老化特性和硝酸盐生物还原关键驱动因素的分析,我们发现老化行为直接调节沉积物营养状态(如DOC/NOx -比率)和微生物特性(从基因到细菌),从而进一步决定硝酸盐生物还原活性。这项工作为老年MPs对沉积物硝酸盐减少的影响提供了新的见解,并强调了MPs老化在淡水生态系统中长期MPs污染的未来评估中的作用。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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