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有机化学品泄漏而造成的地下水和土壤污染一直是广受公众关注的问题,而随着我国双碳战略的发布,生物修复作为一种低成本、低碳绿色的污染场地修复技术逐渐受到科学界和工程界的青睐[1]。微生物在自然界中广泛存在,有的菌种可以利用有机污染物作为自身代谢的碳源和能源来降解污染物,例如使用Dehalococcoides菌可将PCE还原脱氯为乙烯[2],从土壤中分离出的芽孢杆菌Bacillus salmalaya 139SI能降解石油烃[3]。但是本地微生物的数量和活性取决于复杂地下环境,可能难以对污染物进行有效的降解[4]。此时,可以通过添加生物降解所需的营养物质来提高降解效率,即生物刺激,而生物强化方法是通过引入针对特定污染物的外源微生物来提高总体修复率。当从外部向场地添加微生物或营养物质时,场地中微生物和溶质传输效率是决定生物修复效果的关键所在。
现有污染场地生物降解数学模型主要关注有机污染物和附着在土壤上微生物之间的生物反应,并假定微生物固定不动且数量无限[5]。但是,污染含水层中大量微生物活跃在水相中并进行移动[6],尤其是当注入外源微生物时。因此,研究微生物在地下土壤环境中水相和固相中的运移对准确评估生物降解至关重要。微生物通常可以被视作一种生物胶体,同时具备胶体和生物性质[7],近十年来国内外学者通过实验[8-9]和现场试验[10-11]等方法研究了多孔介质中微生物迁移规律。同时,由于地下环境中微生物运移机制复杂,不同的微生物运移数学模型会针对具体研究问题进行假设和简化[12]。其中,细菌类型、温度、土层特性、pH值、含氧量、营养物质和有机物类型等重要因素都会影响微生物的运移。
污染地层内往往存在一些天然裂隙和人工裂隙[13],是微生物的优先运移通道,但也会使得微生物和溶质的运移变得更加复杂。目前,关于微生物在裂隙通道运移的研究较少,且主要集中在岩石裂隙的石油开采方面[14],部分适用于微生物采油的结论可能不适用于生物强化修复方法。目前尚未有文献研究生物修复技术体系下的微生物沿裂隙-基质运移。因此,本研究采用多场耦合仿真软件COMSOL建立了裂隙-基质介质中微生物和溶质反应性输运模型,揭示生物强化技术中微生物运移及降解机制。模型耦合了裂隙-基质介质内微生物的重要物理化学和生物现象,并考虑了注入微生物、电子受体和残留污染物之间的相互联系。最后,研究了微生物注入速度、微生物在基质内扩散系数和动力学吸附/解吸速率系数等对微生物修复效果的影响规律。
含裂隙污染场地中微生物运移及降解修复规律
Study on microbial transport and biodegradation in fracture contaminated sites
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摘要: 原位生物修复作为一种低成本、绿色的污染场地修复技术受到了极大的关注。大多数生物修复研究集中增强土著微生物自身的降解能力的生物刺激技术上,对引入外源微生物的生物强化技术研究有限。而污染场地内天然和人工裂隙等优势渗流会影响注入微生物的运移及其降解反应。通过提出一个数学模型来模拟裂隙含水层中微生物和相关溶质迁移以及污染物降解过程。该模型考虑了对流、扩散、吸附、生长、死亡和微生物代谢反应等过程,并耦合了微生物、电子受体和基质底物三者之间的相互联系,并与试验结果验证良好。模拟结果分析表明,保持微生物与污染物之间的充分接触并提供充足的养分是提高生物修复效率的关键。由于生物降解消耗加速了基质内污染物向裂缝周边区域的反向扩散,生物修复的实际影响范围比微生物运移范围要大。同时,裂隙外基质的扩散系数对生物修复效果的影响最大,其次是微生物吸附系数和注入速度。该数学模型是评估含裂隙地层生物强化策略有效性的重要工具,有助于设计和优化相应的生物修复方法。Abstract: In-situ bioremediation, as a low-cost and environmentally friendly technique for the remediation of contaminated sites, has garnered significant attention. Current research on bioremediation techniques largely focuses on biostimulation techniques that enhance the inherent degradation capabilities of indigenous microorganisms. Limited research exists on bioaugmentation techniques involving the introduction of exogenous microorganisms. While dominant seepage such as natural and artificial fissures within a contaminated site can affect the transport of injected microorganisms and their degradation reactions. A mathematical model was proposed to stimulate the migration of microorganisms, solutes, and contaminant degradation processes within fractured aquifers. The model accounts for processes including advection, diffusion, adsorption, growth, death, and microbial metabolic reactions. It further integrates the interrelationships among microorganisms, electron acceptors, and substrate, and in good agreement with experimental results. The results show that sustaining optimal contact between microorganisms and contaminants, while providing ample nutrients, constitutes a critical factor in enhancing bioremediation efficiency. Due to biodegradation accelerating the reverse diffusion of contaminants within the matrix to the region surrounding the fracture, the impact scope of bioremediation extending beyond microbial transport zones. Simultaneously, the diffusion coefficient of the extracellular matrix in fractures exhibits the most significant influence on bioremediation efficacy, followed by microbial adsorption coefficients and injection rates. The mathematical model presented herein stands as a vital tool for assessing the effectiveness of bioaugmentation strategies within fractured geological formations, thereby aiding the design and optimization of pertinent bioremediation approaches.
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Key words:
- contaminant /
- microorganisms /
- fractures /
- transport /
- biodegradation /
- numerical simulation
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表 1 数值模拟参数
Table 1. Parameters used for numerical simulation
参数 解释 2B = 2 cm 裂隙宽度 L = 1 m 裂隙长度 2H = 1 m 裂隙间距 θ = 0.25 基质孔隙率 Cm0 = Cn0 = Co0 = 1 mg·L−1 注入微生物、溶解氧和初始污染物浓度 Dm = Dn = Do = 10−6 m2·s−1 微生物、溶解氧和污染物扩散系数 ka = 1.73 d−1 微生物吸附系数[18] kr = 0.17 d−1 微生物解吸系数[18] μmax = 2 微生物最大生长系数[19] kd = 0.1 d−1 微生物衰亡系数[20] Kc = 2 mg·L−1 污染物半饱和系数[19] Yc = 0.40 污染物利用系数[19] Ko = 1 mg·L−1 溶解氧半饱和系数[19] Yo = 0.50 溶解氧利用系数[19] σmax = 0.02 微生物最大附着系数 -
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