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首页> 外文期刊>Ecological Modelling >Numerical and field investigation of enhanced in situ denitrification in a shallow-zone well-to-well recirculation system
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Numerical and field investigation of enhanced in situ denitrification in a shallow-zone well-to-well recirculation system

机译：浅层井间再循环系统中增强原位反硝化的数值和现场研究

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摘要

This study investigated efficiency of in situ enhanced biological denitrification of nitrate-contaminated groundwater which employs a well-to-well circulation in a shallow zone where oxygen might give an adverse affect on the denitrification processes. The numerical model developed for the efficiency test included sequential aerobic and nitrate-based respiration, multi-Monod kinetics of reactive components, growth and decay of biomass, and denitrification inhibition associated with the presence of oxygen. Moreover, reaction kinetics for production of toxic intermediates such as nitrite and nitrous oxide were also included in the model. The developed model was applied to the analysis of enhanced in situ denitrification using an injection/extraction well pair. To evaluate the relative remediation effectiveness, comparisons were made between a continuous fumarate injection test (CFIT) system and a pulsed fumarate injection test (PFIT) system, where both systems had the same total fumarate mass injected into the aquifer. The PFIT system was preferable to the CFIT system because of the high possibility of occurrence of clogging in the latter case at the injection well, with no other significant advantages found in either the CFIT or the PFIT system. Accordingly, this developed numerical model is useful to predict and evaluate an in situ bioremediation by denitrification in aquifers.
机译：这项研究调查了硝酸盐污染的地下水的原位增强生物反硝化的效率，该地下水在氧气可能对反硝化过程产生不利影响的浅层区域进行井间循环。为效率测试开发的数值模型包括顺序的有氧和基于硝酸盐的呼吸，反应性组分的多Monod动力学，生物量的生长和衰减以及与氧的存在相关的反硝化抑制作用。此外，该模型还包括生产有毒中间体（如亚硝酸盐和一氧化二氮）的反应动力学。使用注入/提取井对将开发的模型应用于增强原位反硝化作用的分析。为了评估相对修复效果，在富马酸连续注入试验（CFIT）系统和富马酸脉冲注入试验（PFIT）系统之间进行了比较，在这两种系统中，向含水层中注入的富马酸总质量相同。 PFIT系统优于CFIT系统，因为后者在注入井中发生堵塞的可能性很高，而CFIT或PFIT系统都没有其他明显的优势。因此，该开发的数值模型可用于预测和评估含水层中反硝化作用的原位生物修复。

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