Transportability of exogenous microbial community correlates with interwell connectivity in deep aquifers

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Yuran Zhang, Anne E. Dekas, Adam J. Hawkins, John Carlo Primo, Oxana Gorbatenko, Tianming Huang, Zhonghe Pang, Roland N. Horne
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引用次数: 0

Abstract

Subsurface resource engineering operations often utilize continuous injection of externally-sourced water into geological reservoirs for formation pressure maintenance, resource recovery or energy/waste storage. Such injected water generally contains naturally occurring microbes. Little is known, however, about how the injectate microbes transport through geological media as a community, how such transportability is affected by injector-producer connectivity, and whether such knowledge can be utilized for flowpath characterization. In this study, we analyzed daily-to-weekly timeseries microbial community data from the injected- and produced-fluids of a ten-month flow test at a deep, well-characterized engineered aquifer. We found that the injectate microbial community was distinct from the indigenous community at the amplicon sequence variant (ASV) level, and that the transportability of injectate community towards a given producer, quantified by an “nASV-Overlap” metric we propose, had strong and significant positive correlation with known injector-producer connectivities at our site. This suggests that the better the connectivity, the higher the probability for more injectate species to flow through the interwell region and arrive at a producer. Because interwell connectivity is an important yet usually unknown parameter in subsurface resource engineering, such correlation in turn points to nASV-Overlap as a useful indicator of interwell connectivity for aquifer characterization and long-term monitoring. Based on our findings, an nASV-Overlap-based microbial tracing approach was developed for characterizing and monitoring the relative connectivities across multiple producers with a given injector. A side-by-side comparison between the new nASV-Overlap approach and traditional artificial tracer methods is presented, and their respective strengths and limitations are discussed.

Abstract Image

深层含水层中外源微生物群落的可转运性与井间连通性相关
地下资源工程作业通常利用外部水源连续注入地质储层,以维持地层压力、资源回收或能源/废物储存。这种注入水通常含有天然存在的微生物。然而,对于被注入的微生物如何作为一个群落在地质介质中运输,这种可运输性如何受到注入器-采油器连通性的影响,以及这些知识是否可以用于流道表征,我们知之甚少。在这项研究中,我们分析了每日至每周的时间序列微生物群落数据,这些数据来自于在一个特征良好的深层工程含水层进行的为期10个月的流动测试中的注入液和产出液。我们发现,注射微生物群落在扩增子序列变异(ASV)水平上与本地群落不同,并且注射微生物群落对给定生产者的可转运性(通过我们提出的“nasv重叠”度量来量化)与已知的注射者-生产者连通性具有强而显著的正相关。这表明,连通性越好,更多的注入物种流过井间区域并到达生产井的可能性就越大。由于井间连通性是地下资源工程中一个重要但通常未知的参数,这种相关性反过来又指向nasv重叠,作为表征含水层特征和长期监测的有用指标。基于我们的研究结果,我们开发了一种基于nasv重叠的微生物追踪方法,用于表征和监测给定注入器下多个生产商的相对连通性。将新的nasv -重叠方法与传统的人工示踪方法进行了比较,并讨论了它们各自的优点和局限性。
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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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