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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Water</journal-id>
<journal-title>Frontiers in Water</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Water</abbrev-journal-title>
<issn pub-type="epub">2624-9375</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta>
<article-id pub-id-type="doi">10.3389/frwa.2025.1499448</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Water</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Combining microcosm biodegradation and reactive transport modeling to explore the feasibility of ATES-bioremediation approaches</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Wienkenjohann</surname> <given-names>Henning</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Bin Hudari</surname> <given-names>Mohammad Sufian</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>Mosthaf</surname> <given-names>Klaus</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Vogt</surname> <given-names>Carsten</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Nijenhuis</surname> <given-names>Ivonne</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Rolle</surname> <given-names>Massimo</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Department of Environmental and Resource Engineering, Technical University of Denmark</institution>, <addr-line>Kongens Lyngby</addr-line>, <country>Denmark</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Isotope Biogeochemistry, Helmholtz Centre for Environmental Research - UFZ</institution>, <addr-line>Leipzig</addr-line>, <country>Germany</country></aff>
<aff id="aff3"><sup>3</sup><institution>Institute of Applied Geosciences, Department of Materials and Geosciences, Technical University of Darmstadt</institution>, <addr-line>Darmstadt</addr-line>, <country>Germany</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Giuseppe Oliveto, University of Basilicata, Italy</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Zhuobiao Ni, South China Agricultural University, China</p>
<p>Matthijs Bonte, MB-Water, Netherlands</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Massimo Rolle, <email>massimo.rolle@tu-darmstadt.de</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>19</day>
<month>02</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>7</volume>
<elocation-id>1499448</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>09</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>31</day>
<month>01</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Wienkenjohann, Bin Hudari, Mosthaf, Vogt, Nijenhuis and Rolle.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Wienkenjohann, Bin Hudari, Mosthaf, Vogt, Nijenhuis and Rolle</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>This study presents a process-based model analysis of non-isothermal biodegradation of chlorinated ethenes in batch microcosm setups and field-scale remediation, combining Aquifer Thermal Energy Storage with <italic>in situ</italic> bioremediation (ATES-ISB). The features of the proposed modeling framework include: (i) kinetic multi-phase mass transfer and temperature-dependent biodegradation in batch systems, and (ii) multi-dimensional non-isothermal fluid flow, heat transport, and contaminant transport in a physically and chemically heterogeneous aquifer combined with temperature-dependent microbial kinetics. The model was used to analyze an experimental microcosm dataset of temperature-dependent reductive dehalogenation of chlorinated ethenes, from which maximum specific degradation rates were derived. A scenario modeling investigation is presented, considering an ATES-ISB intervention in an aquifer contaminated with trichloroethene, where heated groundwater is injected and lactate is delivered to stimulate <italic>in situ</italic> microbial activity and contaminant transformation. Four scenario parameters were varied to identify the optimal conditions for efficient bioremediation. High lactate concentrations and temperatures at 20&#x00B0;C and 30&#x00B0;C led to more complete transformation of chlorinated ethenes in the considered heterogeneous aquifer system. Furthermore, the pumping rate and the natural groundwater flow velocity were found to control the delivery of heated water and solutes, including lactate, in the aquifer. The outcomes of the scenario simulations performed in this study are useful for designing non-isothermal bioremediation interventions in groundwater systems polluted with organic contaminants.</p>
</abstract>
<kwd-group>
<kwd>microcosms</kwd>
<kwd>aquifer thermal energy storage</kwd>
<kwd>bioremediation</kwd>
<kwd>chlorinated ethenes</kwd>
<kwd>reactive transport modeling</kwd>
<kwd>scenario simulations</kwd>
</kwd-group>
<counts>
<fig-count count="11"/>
<table-count count="1"/>
<equation-count count="19"/>
<ref-count count="72"/>
<page-count count="17"/>
<word-count count="10610"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Water and Built Environment</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>Organic compounds, such as trichloroethene (TCE) and its transformation products cis<italic>-</italic>1,2-dichloroethene (cis-DCE) and vinyl chloride (VC), are widespread contaminants in groundwater systems due to their intense use in industrial activities (<xref ref-type="bibr" rid="ref33">McCarty, 2010</xref>). A large number of groundwater contaminated sites occur in industrial and urban areas and pose a risk to humans and environmental systems (<xref ref-type="bibr" rid="ref53">Rosenberg et al., 2023</xref>). Concurrently, heating and cooling demand is highest in urban and industrial areas (<xref ref-type="bibr" rid="ref11">Epting et al., 2013</xref>). To balance out demand and supply, industrial waste heat or waste heat derived from the cooling of buildings can be stored in porous aquifer systems (<xref ref-type="bibr" rid="ref60">Ueckert and Baumann, 2019</xref>). Aquifer Thermal Energy Storage (ATES) makes use of the subsurface to store heat energy. ATES setups are open-loop systems, in which cold groundwater is abstracted, heated, and reinjected into the porous aquifer. The flow direction is reversed in winter times, so that warm groundwater can be extracted and used for residential heating (<xref ref-type="bibr" rid="ref28">Kumar et al., 2024</xref>). Pilot-scale experiments of ATES systems have shown energy recovery rates of around 66&#x2013;89% (<xref ref-type="bibr" rid="ref35">Molz et al., 1981</xref>; <xref ref-type="bibr" rid="ref19">Heldt et al., 2024</xref>).</p>
<p>Remediation of chlorinated ethenes in heterogeneous groundwater systems is challenging due to the physico-chemical properties of these compounds, such as their high mobility and limited degradability (<xref ref-type="bibr" rid="ref45">Pankow and Cherry, 1996</xref>). In the last decades<italic>, in situ</italic> bioremediation (ISB) has become one of the primary techniques to clean up sites contaminated with chlorinated ethenes since it results in contaminant transformation and effective mass removal (<xref ref-type="bibr" rid="ref30">Major et al., 2002</xref>; <xref ref-type="bibr" rid="ref20">Hood et al., 2008</xref>; <xref ref-type="bibr" rid="ref56">Scheutz et al., 2008</xref>). Under favorable biogeochemical conditions, i.e., in anoxic aquifers, chlorinated ethenes can be dehalogenated by specialized indigenous bacteria, i.e., organohalide-respiring bacteria (OHRB) (<xref ref-type="bibr" rid="ref42">Nijenhuis et al., 2007</xref>, <xref ref-type="bibr" rid="ref43">2013</xref>; <xref ref-type="bibr" rid="ref44">Ottosen et al., 2021</xref>). Biostimulation of polluted aquifer systems can overcome the lack of available electron donor, and, concurrently, improve redox conditions in the groundwater system (<xref ref-type="bibr" rid="ref66">Yamazaki et al., 2020</xref>). Bioaugmentation might be necessary in cases where no OHRB are present in the subsurface (<xref ref-type="bibr" rid="ref58">Stroo et al., 2010</xref>). The temperature in the groundwater system is an important parameter determining the growth of indigenous and bioaugmented bacteria consortia in polluted aquifers (<xref ref-type="bibr" rid="ref14">Friis et al., 2007a</xref>; <xref ref-type="bibr" rid="ref70">Zeman et al., 2014</xref>). Former studies reported optimal microbial growth rates of OHRB, which are capable of biotransforming chlorinated ethenes, at a temperature range of 22&#x2013;38&#x00B0;C (<xref ref-type="bibr" rid="ref15">Friis et al., 2007b</xref>; <xref ref-type="bibr" rid="ref12">Fletcher et al., 2011</xref>; <xref ref-type="bibr" rid="ref32">Marcet et al., 2018</xref>). This is about the same temperature range at which low-temperature ATES systems are typically operated. Therefore, several studies have investigated the potential synergies of underground thermal energy storage systems with <italic>in situ</italic> bioremediation. This includes experimental laboratory studies (<xref ref-type="bibr" rid="ref41">Ni et al., 2015</xref>, <xref ref-type="bibr" rid="ref40">2018</xref>), pilot-scale studies (<xref ref-type="bibr" rid="ref39">N&#x011B;me&#x010D;ek et al., 2018</xref>; <xref ref-type="bibr" rid="ref64">Wienkenjohann et al., 2024</xref>), and field-scale simulations (<xref ref-type="bibr" rid="ref72">Zuurbier et al., 2013</xref>; <xref ref-type="bibr" rid="ref46">Popp et al., 2015</xref>; <xref ref-type="bibr" rid="ref5">Beyer et al., 2016</xref>; <xref ref-type="bibr" rid="ref34">Meng et al., 2021</xref>; <xref ref-type="bibr" rid="ref52">Roohidehkordi and Krol, 2021</xref>).</p>
<p>One important challenge during bioremediation interventions is to determine the rate of the naturally occurring biodegradation caused by indigenous bacteria in the contaminated aquifer system and to evaluate the effect of biostimulation. In this regards, microcosm studies have shown to be a versatile and useful tool (<xref ref-type="bibr" rid="ref2">Allen-King et al., 1995</xref>; <xref ref-type="bibr" rid="ref31">Malaguerra et al., 2011</xref>; <xref ref-type="bibr" rid="ref55">Scheutz et al., 2014</xref>; <xref ref-type="bibr" rid="ref68">Yu et al., 2018</xref>). Microcosm experiments can be used to assess the natural degradation potential at a contaminated site (<xref ref-type="bibr" rid="ref21">Hunkeler et al., 1999</xref>), to demonstrate the effect of biostimulation during reductive dehalogenation (<xref ref-type="bibr" rid="ref68">Yu et al., 2018</xref>), to understand the effect of bioaugmentation (<xref ref-type="bibr" rid="ref16">Friis et al., 2007c</xref>), and to understand the competition within different microbial communities (<xref ref-type="bibr" rid="ref38">Murray et al., 2020</xref>). However, only a few studies have used microcosms to investigate the effect of temperature on the biotransformation rate of chlorinated ethenes (<xref ref-type="bibr" rid="ref13">Friis et al., 2005</xref>; <xref ref-type="bibr" rid="ref6">Bin Hudari et al., 2025</xref>).</p>
<p>The combination of ATES and ISB induces a complex interplay between physical and biogeochemical processes (<xref ref-type="bibr" rid="ref64">Wienkenjohann et al., 2024</xref>). These processes are temperature-dependent and govern the mobility and fate of pollutants, such as chlorinated ethenes, in subsurface porous media. Fluid flow is affected by heat transport, which also impacts solute transport, mixing and biogeochemical reactions in aquifer systems. To account for these challenging multi-physics phenomena, numerical simulators are needed, to effectively incorporate the coupled, physical and biogeochemical processes that occur during ATES-ISB. In addition, such numerical models allow the simulation of field-scale remediation interventions considering different scenarios (<xref ref-type="bibr" rid="ref46">Popp et al., 2015</xref>; <xref ref-type="bibr" rid="ref5">Beyer et al., 2016</xref>). Therefore, scenario simulations are a useful approach to test various flow, heat transfer and solute transport conditions and different operational procedures, which, ultimately, could lead to an optimal set of conditions and parameters for ATES-ISB interventions.</p>
<p>In this study, we present a batch multi-phase kinetic mass-transfer model and a field-scale model with scenario simulations to describe non-isothermal reactive transport and biodegradation of chlorinated ethenes. Temperature-dependent maximum specific degradation rates are derived from the model-based analysis of microcosm setups and used as input for reactive transport simulations of a modeled ATES-ISB intervention in a physically and chemically heterogeneous aquifer, which is contaminated with chlorinated ethenes. Field-scale scenario modeling in the considered groundwater system was performed to assess the biodegradation potential considering four operational constraints: (i) the natural groundwater flow velocity, (ii) the pumping rate of the injection/abstraction system, (iii) the injection temperature, and (iv) the injected concentration of lactate as substrate to stimulate microbial growth and biological reductive dehalogenation. Finally, we also discuss the optimal parameter set for field-scale ATES-ISB at sites contaminated with chlorinated ethenes.</p>
</sec>
<sec id="sec2">
<label>2</label>
<title>Laboratory and field-scale setups</title>
<p>A conceptual, multi-scale representation of the microcosms and a field-scale system is shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. In the multi-phase microcosms, mass transfer of contaminants can occur between the sediment, water, and gas phase and microbial reductive dechlorination is carried out by indigenous dehalogenators (i.e., <italic>Dehalococcoides</italic> spp., <italic>Dhc</italic>) (<xref ref-type="fig" rid="fig1">Figure 1a</xref>). The reactive field-scale setup includes active pumping with injection of warm groundwater, its recirculation, and biostimulation of the system with lactate (<xref ref-type="fig" rid="fig1">Figures 1b</xref>,<xref ref-type="fig" rid="fig1">c</xref>). Four key parameters (one site parameter and three operational parameters) are varied to assess the overall biotransformation potential in different modeling scenarios (<xref ref-type="fig" rid="fig1">Figure 1d</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Schematic representation of the multi-scale approach incorporating microcosm biodegradation and field-scale reactive transport modeling. Incubation of biostimulated microcosms at four different temperatures and batch multi-phase modeling <bold>(a)</bold>. Field-scale scenario modeling approach combining Aquifer Thermal Energy Storage with <italic>in situ</italic> bioremediation (ATES-ISB) in a two-dimensional aquifer system <bold>(b,c)</bold>. Scenario parameters considered in field-scale simulations <bold>(d)</bold>.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g001.tif"/>
</fig>
<sec id="sec3">
<label>2.1</label>
<title>Description of microcosm dataset</title>
<p>The dataset used in this study was obtained from microcosm experiments performed in a three-phase system comprising aquifer sediments, an aqueous phase, and a gas phase. <xref ref-type="bibr" rid="ref6">Bin Hudari et al. (2025)</xref> provide a detailed description of the experimental procedures and materials. Briefly, 20&#x202F;g of aquifer sediments polluted with TCE from a contaminated site in Ferrara, Northern Italy, were prepared in 125&#x202F;mL serum bottles each filled with 50&#x202F;mL of aqueous mineral salts medium in an anoxic chamber. The bottles were fitted with Teflon-lined caps and crimped tightly. The microcosms were amended with 3&#x202F;mM of lactate as substrate at day 0 and were incubated for 105&#x202F;days at 10&#x00B0;C, 20&#x00B0;C, 30&#x00B0;C, and 40&#x00B0;C. The systems held at 20&#x00B0;C and 30&#x00B0;C were spiked with 100&#x202F;&#x03BC;M of TCE at day 3, 35, 56, and 70 and chlorinated ethene concentrations were measured in the headspace to investigate the effect of temperature on the biodegradation potential of the indigenous bacterial consortium (<xref ref-type="fig" rid="fig1">Figure 1a</xref>).</p>
</sec>
<sec id="sec4">
<label>2.2</label>
<title>Geometry and design of field-scale simulations</title>
<p>In order to explore the feasibility of ATES-bioremediation approaches, a field-scale reactive transport model was employed (<xref ref-type="fig" rid="fig1">Figures 1b</xref>,<xref ref-type="fig" rid="fig1">c</xref>. The proposed model used the biodegradation kinetics determined in the microcosm system. We assumed an aquifer with a thickness of 6&#x202F;m and a width and length of 400 meters. A contaminant source was placed in the center of the aquifer. The source consisted of TCE, present as aqueous phase and free, non-aqueous phase liquid (NAPL) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>). Two wells were located in the center of the aquifer to represent a recirculation system, operated as in ATES-ISB systems (<xref ref-type="bibr" rid="ref64">Wienkenjohann et al., 2024</xref>). The eastern well was used for the abstraction of groundwater, whereas the western well was used to inject the heated groundwater back into the subsurface (<xref ref-type="fig" rid="fig1">Figure 1b</xref>). The model included indigenous <italic>Dhc</italic> bacteria, capable of transforming TCE to the non-toxic end product ethene. These OHRB were present, bound to the sediments, in the entire solution domain. Dissolved organic carbon and lactate were considered as substrate providing carbon sources and electron donors. Lactate was injected via the injection well into the system, whereas DOC was present at a pristine background concentration from the start of the simulation. The chemical species were advectively transported by the natural groundwater flow and active pumping. The physics of the fluid flow, solute transport, and biogeochemical reactions were coupled. The temperature dependence and non-isothermal properties of these processes were considered to accurately describe transport and biotransformation of the organic contaminants in the contaminated aquifer.</p>
</sec>
<sec id="sec5">
<label>2.3</label>
<title>Modeling approach</title>
<sec id="sec6">
<label>2.3.1</label>
<title>Modeling of batch microcosms</title>
<sec id="sec7">
<label>2.3.1.1</label>
<title>Multi-phase kinetic mass transfer</title>
<p>The vertical, black arrows in <xref ref-type="fig" rid="fig1">Figure 1</xref> represent the mass transfer of the chlorinated ethenes between the distinct phases (sediment, water, and gas). In the model, reductive dehalogenation by <italic>Dhc</italic> is considered only for chlorinated ethenes dissolved in the aqueous phase. The change in concentration of each relevant species in each phase is described by a set of ordinary differential equations (<xref ref-type="disp-formula" rid="EQ1">Equations 1</xref>&#x2013;<xref ref-type="disp-formula" rid="EQ3">3</xref>) (<xref ref-type="bibr" rid="ref1">Aeppli et al., 2009</xref>; <xref ref-type="bibr" rid="ref25">Jin et al., 2013</xref>; <xref ref-type="bibr" rid="ref37">Murray et al., 2019</xref>):</p>
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<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mfrac>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mi mathvariant="italic">deg</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<disp-formula id="EQ2">
<label>(2)</label>
<mml:math id="M2">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mfrac>
</mml:math>
</disp-formula>
<disp-formula id="EQ3">
<label>(3)</label>
<mml:math id="M3">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:msub>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:msub>
</mml:mfrac>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M4">
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo stretchy="true">/</mml:mo>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:math>
</inline-formula> [mol&#x202F;L<sup>&#x2212;1</sup> s<sup>&#x2212;1</sup>] is the change in concentration for the species <inline-formula>
<mml:math id="M5">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula> in phase <inline-formula>
<mml:math id="M6">
<mml:mi>x</mml:mi>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math id="M7">
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> [L] is the volume of phase <inline-formula>
<mml:math id="M8">
<mml:mi>x</mml:mi>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math id="M9">
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo stretchy="true">/</mml:mo>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:math>
</inline-formula> [mol&#x202F;s<sup>&#x2212;1</sup>] represents the total, species-specific change in moles between the phases, and <inline-formula>
<mml:math id="M10">
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mi mathvariant="italic">deg</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the biodegradation rate. The gas and sediment phases do not share an interface, therefore <inline-formula>
<mml:math id="M11">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo stretchy="true">/</mml:mo>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> is equal to zero. The initial concentration of TCE is highest in the aqueous phase. Thus, movement from the aqueous phase is defined as positive. The transfer of mass across the two relevant phase interfaces <inline-formula>
<mml:math id="M12">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo stretchy="true">/</mml:mo>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M13">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo stretchy="true">/</mml:mo>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula>, can be described by <xref ref-type="disp-formula" rid="EQ4">Equations 4</xref>, <xref ref-type="disp-formula" rid="EQ5">5</xref> (<xref ref-type="bibr" rid="ref1">Aeppli et al., 2009</xref>; <xref ref-type="bibr" rid="ref37">Murray et al., 2019</xref>):</p>
<disp-formula id="EQ4">
<label>(4)</label>
<mml:math id="M14">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mfrac>
</mml:mfenced>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi mathvariant="italic">gas</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msubsup>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mi mathvariant="italic">eq</mml:mi>
</mml:msubsup>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mfenced>
</mml:math>
</disp-formula>
<disp-formula id="EQ5">
<label>(5)</label>
<mml:math id="M15">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mfrac>
</mml:mfenced>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msubsup>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mi mathvariant="italic">eq</mml:mi>
</mml:msubsup>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mfenced>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M16">
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [mol&#x202F;m<sup>&#x2212;3</sup>] and <inline-formula>
<mml:math id="M17">
<mml:msubsup>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mi mathvariant="italic">eq</mml:mi>
</mml:msubsup>
</mml:math>
</inline-formula> [mol&#x202F;m<sup>&#x2212;3</sup>] are the concentration and equilibrium concentration of species <inline-formula>
<mml:math id="M18">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula> in the <inline-formula>
<mml:math id="M19">
<mml:mi>x</mml:mi>
</mml:math>
</inline-formula>-th phase, respectively, <inline-formula>
<mml:math id="M20">
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">gas</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [cm&#x202F;s<sup>&#x2212;1</sup>] and <inline-formula>
<mml:math id="M21">
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>d</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [cm&#x202F;s<sup>&#x2212;1</sup>] are the species-specific mass transfer coefficients, while <inline-formula>
<mml:math id="M22">
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>x</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [cm<sup>2</sup>] is the cross-sectional area of the respective phase interface. More information on the model parameters and temperature-dependent mass transfer processes, including volatilization and sorption, is provided in the <xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>.</p>
</sec>
<sec id="sec8">
<label>2.3.1.2</label>
<title>Temperature-dependent biodegradation and microbial dynamics</title>
<p>The temperature-dependent biodegradation and the dynamics of indigenous microorganisms were simulated as such that TCE was sequentially biotransformed to cis-DCE, VC, and ethene under anoxic conditions with dissolved organic carbon and lactate as electron donors&#x2019; source. Organohalide-respiring bacteria were assumed as a <italic>Dehalococcoides</italic> containing bacterial consortium, which was attached to the sediment, and is capable of carrying out the complete transformation sequence from TCE to ethene.</p>
<p>For both the modeling of the microcosms and the field-scale scenario simulations, double-Monod kinetics including competitive inhibition of dissolved chlorinated ethenes were used to implement temperature-dependent biotransformation reactions, occurring in the aqueous phase (<xref ref-type="bibr" rid="ref69">Yu and Semprini, 2004</xref>; <xref ref-type="bibr" rid="ref37">Murray et al., 2019</xref>):</p>
<disp-formula id="EQ6">
<label>(6)</label>
<mml:math id="M23">
<mml:mtable columnalign="left">
<mml:mtr>
<mml:mtd>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mi mathvariant="italic">deg</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">max</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mstyle displaystyle="true">
<mml:mo stretchy="true">&#x2211;</mml:mo>
</mml:mstyle>
<mml:mrow>
<mml:mi>j</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>n</mml:mi>
</mml:msubsup>
<mml:mfrac>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">in</mml:mi>
<mml:msub>
<mml:mi>h</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:mfrac>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M24">
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> is the molar concentration of the <inline-formula>
<mml:math id="M25">
<mml:mi>n</mml:mi>
</mml:math>
</inline-formula>-th electron donor (ED), <inline-formula>
<mml:math id="M26">
<mml:msub>
<mml:mi>&#x03BA;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">max</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mi>k</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
</mml:math>
</inline-formula> [s<sup>&#x2212;1</sup>] represents the maximum specific degradation rate at temperature <inline-formula>
<mml:math id="M27">
<mml:mi>T</mml:mi>
</mml:math>
</inline-formula> of the <inline-formula>
<mml:math id="M28">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>-th electron acceptor (EA) (i.e., the chlorinated ethenes), <inline-formula>
<mml:math id="M29">
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> is the molar concentration of the indigenous <italic>Dhc</italic> bacteria, <inline-formula>
<mml:math id="M30">
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula>[mol&#x202F;m<sup>&#x2212;3</sup>] represents the half-saturation constant of the <inline-formula>
<mml:math id="M31">
<mml:mi>n</mml:mi>
</mml:math>
</inline-formula>-th ED, and <inline-formula>
<mml:math id="M32">
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [mol&#x202F;m<sup>&#x2212;3</sup>] is the half-saturation constant of the <inline-formula>
<mml:math id="M33">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>-th EA. The inhibition constant of <inline-formula>
<mml:math id="M34">
<mml:msub>
<mml:mi>K</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">in</mml:mi>
<mml:msub>
<mml:mi>h</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [mol&#x202F;m<sup>&#x2212;3</sup>] of the <inline-formula>
<mml:math id="M35">
<mml:mi>j</mml:mi>
</mml:math>
</inline-formula>-th EA is considering all the other electron acceptors, except the <inline-formula>
<mml:math id="M36">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>&#x2013;th EA.</p>
<p>Growth and decay of biomass are described as:</p>
<disp-formula id="EQ7">
<label>(7)</label>
<mml:math id="M37">
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="normal">Y</mml:mi>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>A</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</disp-formula>
<p>in which the bacterial yield <inline-formula>
<mml:math id="M38">
<mml:mi>Y</mml:mi>
</mml:math>
</inline-formula> was implemented with a value of 0.02 [mol<sub>X</sub> mol<sub>EA</sub><sup>&#x2212;1</sup>] (<xref ref-type="bibr" rid="ref31">Malaguerra et al., 2011</xref>), and <inline-formula>
<mml:math id="M39">
<mml:msub>
<mml:mi>b</mml:mi>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>h</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [s<sup>&#x2212;1</sup>] is the biomass decay coefficient (<xref ref-type="bibr" rid="ref10">Cupples et al., 2004</xref>).</p>
</sec>
</sec>
<sec id="sec9">
<label>2.3.2</label>
<title>Field-scale simulations</title>
<sec id="sec10">
<label>2.3.2.1</label>
<title>Non-isothermal flow and heat transport</title>
<p>Field-scale non-isothermal fluid flow in a saturated porous aquifer can be described by the following governing equation (<xref ref-type="disp-formula" rid="EQ8">Equation 8</xref>) (<xref ref-type="bibr" rid="ref4">Bear and Bachmat, 1990</xref>):</p>
<disp-formula id="EQ8">
<label>(8)</label>
<mml:math id="M40">
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mo>&#x2207;</mml:mo>
<mml:mo>&#x00B7;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mfrac>
<mml:mi>k</mml:mi>
<mml:mrow>
<mml:mi>&#x03B7;</mml:mi>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
</mml:mrow>
</mml:mfrac>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mo>&#x2207;</mml:mo>
<mml:mi>p</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mi>g</mml:mi>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
</mml:mfenced>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>F</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<p>in which <inline-formula>
<mml:math id="M41">
<mml:mi>n</mml:mi>
</mml:math>
</inline-formula> is the porosity [&#x2212;], <inline-formula>
<mml:math id="M42">
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the water density [kg&#x202F;m<sup>&#x2212;3</sup>], <inline-formula>
<mml:math id="M43">
<mml:mi>t</mml:mi>
</mml:math>
</inline-formula> is time [s], <inline-formula>
<mml:math id="M44">
<mml:mi>k</mml:mi>
</mml:math>
</inline-formula> stands for the intrinsic permeability tensor [m<sup>2</sup>], <inline-formula>
<mml:math id="M45">
<mml:mi>&#x03B7;</mml:mi>
</mml:math>
</inline-formula> is the dynamic viscosity of water [kg&#x202F;m<sup>&#x2212;1 s-1</sup>], <inline-formula>
<mml:math id="M46">
<mml:mi>p</mml:mi>
</mml:math>
</inline-formula> is the water pressure [kg&#x202F;m<sup>&#x2212;1</sup> s<sup>&#x2212;2</sup>], <inline-formula>
<mml:math id="M47">
<mml:mi>g</mml:mi>
</mml:math>
</inline-formula> is the vector of gravitational acceleration [m&#x202F;s<sup>&#x2212;2</sup>], and <inline-formula>
<mml:math id="M48">
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>F</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is a source/sink term [kg&#x202F;m<sup>&#x2212;3</sup> s<sup>&#x2212;1</sup>].</p>
<p>The temperature dependence of water density, water viscosity, specific isobaric heat capacity of water, and the thermal conductivity of water were implemented using the IF97 formulation (<xref ref-type="bibr" rid="ref62">Wagner et al., 2000</xref>; <xref ref-type="bibr" rid="ref22">IAPWS, 2007</xref>), resulting in temperature-induced changes in the hydraulic conductivity tensor <inline-formula>
<mml:math id="M49">
<mml:mi>K</mml:mi>
</mml:math>
</inline-formula>, whereas the intrinsic permeability <inline-formula>
<mml:math id="M50">
<mml:mi>k</mml:mi>
</mml:math>
</inline-formula> is a specific property of the solid matrix of the porous medium.</p>
<p>The heat convection-conduction (<xref ref-type="disp-formula" rid="EQ9">Equation 9</xref>) (e.g. <xref ref-type="bibr" rid="ref4">Bear and Bachmat, 1990</xref>; <xref ref-type="bibr" rid="ref57">Sprocati et al., 2023</xref>) was used to describe non-isothermal heat transport in the field-scale groundwater system:</p>
<disp-formula id="EQ9">
<label>(9)</label>
<mml:math id="M51">
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>&#x03C1;</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:msub>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mo>&#x2207;</mml:mo>
<mml:mo>&#x00B7;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:mi>&#x03C1;</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
<mml:mi>v</mml:mi>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:mo>+</mml:mo>
<mml:mo>&#x2207;</mml:mo>
<mml:mo>&#x00B7;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>H</mml:mi>
</mml:msub>
<mml:mo>&#x2207;</mml:mo>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>H</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M52">
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> [J&#x202F;kg<sup>&#x2212;1</sup> K] is the specific heat capacity of the porous medium, <inline-formula>
<mml:math id="M53">
<mml:mi>v</mml:mi>
</mml:math>
</inline-formula> is the seepage velocity vector, <inline-formula>
<mml:math id="M54">
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>H</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the heat dispersion tensor, and <inline-formula>
<mml:math id="M55">
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>H</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is a term for the source/sink of heat. The effective volumetric heat capacity <inline-formula>
<mml:math id="M56">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>&#x03C1;</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> of the porous medium (<xref ref-type="disp-formula" rid="EQ10">Equation 10</xref>), with the subscripts <inline-formula>
<mml:math id="M57">
<mml:mi>l</mml:mi>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M58">
<mml:mi>s</mml:mi>
</mml:math>
</inline-formula> indicating the liquid phase and the solid matrix, respectively, can be written as:</p>
<disp-formula id="EQ10">
<label>(10)</label>
<mml:math id="M59">
<mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>&#x03C1;</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>n</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</disp-formula>
<p>The tensor for the dispersion of heat in the porous media is shown in <xref ref-type="disp-formula" rid="EQ11">Equation 11</xref>:</p>
<disp-formula id="EQ11">
<label>(11)</label>
<mml:math id="M60">
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>H</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">cond</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">disp</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</disp-formula>
<p>where the effective thermal conductivity tensor <inline-formula>
<mml:math id="M61">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">cond</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [W&#x202F;m<sup>&#x2212;1</sup> K<sup>&#x2212;1</sup>] (<xref ref-type="disp-formula" rid="EQ12">Equation 12</xref>) can be approximated from the porosity and the thermal conductivity of the fluid (<inline-formula>
<mml:math id="M62">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
</mml:math>
</inline-formula>) and the solid phase (<inline-formula>
<mml:math id="M63">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
</mml:math>
</inline-formula>) (<xref ref-type="bibr" rid="ref71">Zimmerman, 1989</xref>):</p>
<disp-formula id="EQ12">
<label>(12)</label>
<mml:math id="M64">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">cond</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>&#x03B4;</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>n</mml:mi>
</mml:mrow>
</mml:mfenced>
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>&#x03B4;</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</disp-formula>
<p>in which <inline-formula>
<mml:math id="M65">
<mml:msub>
<mml:mi>&#x03B4;</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mfenced open="[" close="]">
<mml:mo>&#x2212;</mml:mo>
</mml:mfenced>
</mml:math>
</inline-formula> is the Kronecker delta. The effective thermal dispersion tensor <inline-formula>
<mml:math id="M66">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">disp</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> reads as (<xref ref-type="disp-formula" rid="EQ13">Equation 13</xref>):</p>
<disp-formula id="EQ13">
<label>(13)</label>
<mml:math id="M67">
<mml:msub>
<mml:mi>&#x03BB;</mml:mi>
<mml:mrow>
<mml:mi mathvariant="italic">disp</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="italic">eff</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>l</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mi>&#x03B3;</mml:mi>
<mml:mi>T</mml:mi>
</mml:msub>
<mml:mo stretchy="true">|</mml:mo>
<mml:mi>v</mml:mi>
<mml:mo stretchy="true">|</mml:mo>
<mml:msub>
<mml:mi>&#x03B4;</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mi>&#x03B3;</mml:mi>
<mml:mi>L</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>&#x03B3;</mml:mi>
<mml:mi>T</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>&#x03BD;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>&#x03BD;</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mfenced open="|" close="|">
<mml:mi>v</mml:mi>
</mml:mfenced>
</mml:mfrac>
</mml:mrow>
</mml:mfenced>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M68">
<mml:msub>
<mml:mi>&#x03B3;</mml:mi>
<mml:mi>L</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M69">
<mml:msub>
<mml:mi>&#x03B3;</mml:mi>
<mml:mi>T</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> [m] are, respectively, the longitudinal and transverse thermal dispersivities, and <inline-formula>
<mml:math id="M70">
<mml:msub>
<mml:mi>v</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M71">
<mml:msub>
<mml:mi>v</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> [m&#x202F;s<sup>&#x2212;1</sup>] are the components of the seepage velocity in <inline-formula>
<mml:math id="M72">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M73">
<mml:mi>j</mml:mi>
</mml:math>
</inline-formula> directions, respectively.</p>
</sec>
<sec id="sec11">
<label>2.3.2.2</label>
<title>Reactive transport</title>
<p>Reactive solute transport at field scale is described by the advection-dispersion-reaction equation (<xref ref-type="bibr" rid="ref4">Bear and Bachmat, 1990</xref>) as shown in <xref ref-type="disp-formula" rid="EQ14">Equation 14</xref>:</p>
<disp-formula id="EQ14">
<label>(14)</label>
<mml:math id="M74">
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mo>&#x2207;</mml:mo>
<mml:mo>&#x00B7;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:mi>v</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mo>+</mml:mo>
<mml:mo>&#x2207;</mml:mo>
<mml:mo>&#x00B7;</mml:mo>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>&#x2207;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mi mathvariant="italic">deg</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M75">
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the retardation factor of the transported species <inline-formula>
<mml:math id="M76">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math id="M77">
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the molar concentration of the species <inline-formula>
<mml:math id="M78">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>, and <inline-formula>
<mml:math id="M79">
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the local hydrodynamic dispersion tensor with the components <inline-formula>
<mml:math id="M80">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>L</mml:mi>
</mml:msubsup>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M81">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>T</mml:mi>
</mml:msubsup>
</mml:math>
</inline-formula> in longitudinal and transverse direction, respectively. The local longitudinal dispersion coefficient (<xref ref-type="disp-formula" rid="EQ15">Equation 15</xref>) (<xref ref-type="bibr" rid="ref18">Guedes de Carvalho and Delgado, 2005</xref>; <xref ref-type="bibr" rid="ref36">Muniruzzaman and Rolle, 2017</xref>) and the local transverse dispersion coefficient (<xref ref-type="disp-formula" rid="EQ16">Equation 16</xref>) (<xref ref-type="bibr" rid="ref9">Chiogna et al., 2010</xref>; <xref ref-type="bibr" rid="ref49">Rolle et al., 2012</xref>) were implemented as follows:</p>
<disp-formula id="EQ15">
<label>(15)</label>
<mml:math id="M82">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>L</mml:mi>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>P</mml:mi>
</mml:msubsup>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mn>2</mml:mn>
</mml:mfrac>
<mml:mo stretchy="true">|</mml:mo>
<mml:mi>v</mml:mi>
<mml:mo stretchy="true">|</mml:mo>
<mml:mi>d</mml:mi>
</mml:math>
</disp-formula>
<disp-formula id="EQ16">
<label>(16)</label>
<mml:math id="M83">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>T</mml:mi>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>P</mml:mi>
</mml:msubsup>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msubsup>
<mml:msup>
<mml:mfenced open="(" close=")">
<mml:mfrac>
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:msubsup>
<mml:mi>e</mml:mi>
<mml:mi>i</mml:mi>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:msub>
<mml:mi>e</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mn>2</mml:mn>
<mml:mo>+</mml:mo>
<mml:mn>4</mml:mn>
<mml:msup>
<mml:mi>&#x03B4;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfrac>
</mml:mfenced>
<mml:mi>&#x03B2;</mml:mi>
</mml:msup>
</mml:math>
</disp-formula>
<p>in which <inline-formula>
<mml:math id="M84">
<mml:mi>d</mml:mi>
</mml:math>
</inline-formula> [m] is the spatially-varying grain size diameter of the aquifer material, <inline-formula>
<mml:math id="M85">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>P</mml:mi>
</mml:msubsup>
<mml:mo>&#x2248;</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msubsup>
<mml:mi>n</mml:mi>
</mml:math>
</inline-formula> [m<sup>2</sup> s<sup>&#x2212;1</sup>] is the pore diffusion coefficient, <inline-formula>
<mml:math id="M86">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msubsup>
</mml:math>
</inline-formula> is the aqueous diffusion coefficient [m<sup>2</sup> s<sup>&#x2212;1</sup>], <inline-formula>
<mml:math id="M87">
<mml:mi>P</mml:mi>
<mml:mi>e</mml:mi>
<mml:mo>=</mml:mo>
<mml:mo stretchy="true">|</mml:mo>
<mml:mi>v</mml:mi>
<mml:mo stretchy="true">|</mml:mo>
<mml:mi>d</mml:mi>
<mml:mo stretchy="true">/</mml:mo>
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msubsup>
</mml:math>
</inline-formula> is the dimensionless grain P&#x00E9;clet number, <inline-formula>
<mml:math id="M88">
<mml:mi>&#x03B4;</mml:mi>
</mml:math>
</inline-formula> [&#x2212;] is the ratio between the length of a pore channel and its hydraulic radius, and <inline-formula>
<mml:math id="M89">
<mml:mi>&#x03B2;</mml:mi>
</mml:math>
</inline-formula> [&#x2212;] is an empirical parameter accounting for the effects of incomplete mixing in the pores. We consider values of <inline-formula>
<mml:math id="M90">
<mml:mi>&#x03B4;</mml:mi>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math id="M91">
<mml:mi>&#x03B2;</mml:mi>
</mml:math>
</inline-formula> (5.37 and 0.5, respectively) as reported in <xref ref-type="bibr" rid="ref67">Ye et al. (2015)</xref>.</p>
<p>In this paper, hydraulic aquifer characteristics of the well-studied Borden aquifer (Ontario, Canada) were used (<xref ref-type="bibr" rid="ref59">Sudicky, 1986</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>) to create a heterogeneous hydraulic conductivity field (<xref ref-type="bibr" rid="ref63">Wienkenjohann et al., 2023</xref>) (more information is provided in the <xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>). The heterogeneity of the hydrogeological subsurface impacts field-scale contaminant transport. In order to accurately simulate the transport of contaminants in the subsurface, a spatially variable description of the porosity, grain size, and fraction of organic carbon was implemented using the same procedure as described in detail in <xref ref-type="bibr" rid="ref64">Wienkenjohann et al. (2024)</xref>. Probability density functions of the spatial random fields are shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S3</xref>.</p>
<p>The aqueous diffusion coefficients are compound-specific and different for the distinct chlorinated ethenes (<xref ref-type="bibr" rid="ref48">Rolle et al., 2013</xref>; <xref ref-type="bibr" rid="ref26">Jin et al., 2014</xref>). Their value and temperature dependence (<xref ref-type="disp-formula" rid="EQ17">Equation 17</xref>) was calculated according to <xref ref-type="bibr" rid="ref65">Worch (1993)</xref>:</p>
<disp-formula id="EQ17">
<label>(17)</label>
<mml:math id="M92">
<mml:msubsup>
<mml:mi>D</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mi>q</mml:mi>
</mml:mrow>
</mml:msubsup>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mo>=</mml:mo>
<mml:mn>3.595</mml:mn>
<mml:mo>&#x00D7;</mml:mo>
<mml:msup>
<mml:mn>10</mml:mn>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>14</mml:mn>
</mml:mrow>
</mml:msup>
<mml:mfrac>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>&#x03B7;</mml:mi>
<mml:msubsup>
<mml:mi>M</mml:mi>
<mml:mi>i</mml:mi>
<mml:mn>0.53</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:mfrac>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math id="M93">
<mml:msub>
<mml:mi>M</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> [g&#x202F;mol<sup>&#x2212;1</sup>] is the molecular mass of the <inline-formula>
<mml:math id="M94">
<mml:mi>i</mml:mi>
</mml:math>
</inline-formula>-th species. The increase of aqueous diffusion coefficients with increasing temperature for the chlorinated ethenes considered in this study is shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1B</xref>.</p>
<p>Temperature-dependent sorption of chlorinated ethenes to the sediment was implemented by linear equilibrium sorption (<xref ref-type="disp-formula" rid="EQ18">Equation 18</xref>). The resulting temperature-dependent retardation factor reads as:</p>
<disp-formula id="EQ18">
<label>(18)</label>
<mml:math id="M95">
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>b</mml:mi>
</mml:msub>
<mml:mi>n</mml:mi>
</mml:mfrac>
<mml:msubsup>
<mml:mi>K</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
</mml:msubsup>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
</mml:math>
</disp-formula>
<p>in which <inline-formula>
<mml:math id="M96">
<mml:msub>
<mml:mi>&#x03C1;</mml:mi>
<mml:mi>b</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the bulk density of the sediment, and <inline-formula>
<mml:math id="M97">
<mml:msubsup>
<mml:mi>K</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
</mml:msubsup>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mo>=</mml:mo>
<mml:msubsup>
<mml:mi>K</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>O</mml:mi>
<mml:mi>C</mml:mi>
</mml:mrow>
</mml:msubsup>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mspace width="thickmathspace"/>
<mml:msub>
<mml:mi>f</mml:mi>
<mml:mrow>
<mml:mi>O</mml:mi>
<mml:mi>C</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> is the sorption distribution coefficient, with <inline-formula>
<mml:math id="M98">
<mml:msubsup>
<mml:mi>K</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>O</mml:mi>
<mml:mi>C</mml:mi>
</mml:mrow>
</mml:msubsup>
</mml:math>
</inline-formula>(T) [L&#x202F;kg<sup>&#x2212;1</sup>] being the temperature-dependent species-specific soil organic carbon-water partition coefficient as shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1D</xref>, and <inline-formula>
<mml:math id="M99">
<mml:msub>
<mml:mi>f</mml:mi>
<mml:mrow>
<mml:mi>O</mml:mi>
<mml:mi>C</mml:mi>
</mml:mrow>
</mml:msub>
</mml:math>
</inline-formula> [&#x2212;] the spatially varying fraction of organic carbon in the sediment (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S3D</xref>).</p>
<p>The proposed field-scale model also accounts for temperature-dependent kinetic mass transfer between the free TCE phase (non-aqueous phase liquid (NAPL)), and the aqueous TCE phase. The NAPL phase dissolves and progressively releases TCE in the groundwater. The aqueous solubility is dependent on temperature and was implemented following an empirical model proposed by <xref ref-type="bibr" rid="ref27">Koproch et al. (2019)</xref> (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1A</xref>). The linear driving force expression, with temperature-dependent aqueous solubility, can be used to describe inter-phase mass transfer (<xref ref-type="disp-formula" rid="EQ19">Equation 19</xref>) (<xref ref-type="bibr" rid="ref47">Powers et al., 1994</xref>):</p>
<disp-formula id="EQ19">
<label>(19)</label>
<mml:math id="M100">
<mml:mfrac>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>d</mml:mi>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>&#x03C9;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mrow>
<mml:msub>
<mml:mi>S</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
<mml:mfenced open="(" close=")">
<mml:mi>T</mml:mi>
</mml:mfenced>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfenced>
</mml:math>
</disp-formula>
<p>in which <inline-formula>
<mml:math id="M101">
<mml:msub>
<mml:mi>&#x03C9;</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the mass-transfer rate as reported in <xref ref-type="bibr" rid="ref23">Illy et al. (2022)</xref>, <inline-formula>
<mml:math id="M102">
<mml:msub>
<mml:mi>S</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the temperature-dependent aqueous solubility (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1A</xref>), and <inline-formula>
<mml:math id="M103">
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is the species-specific aqueous concentration. In this study, only TCE has been included as NAPL in the model.</p>
<p>The reactive term <inline-formula>
<mml:math id="M104">
<mml:msub>
<mml:mi>r</mml:mi>
<mml:mi mathvariant="italic">deg</mml:mi>
</mml:msub>
</mml:math>
</inline-formula> is expressed with a double-Monod kinetics (<xref ref-type="disp-formula" rid="EQ6">Equation 6</xref>) representing a mixing-controlled reaction between the electron donors and electron acceptors in the aquifer system (<xref ref-type="bibr" rid="ref51">Rolle and Le Borgne, 2019</xref>; <xref ref-type="bibr" rid="ref61">Valocchi et al., 2019</xref>). The dynamics of the indigenous reductive dehalogenators in the simulated aquifer system was described as in <xref ref-type="disp-formula" rid="EQ7">Equation 7</xref>, since it was assumed that the bacteria are attached to the solid matrix of the aquifer and, thus, do not undergo transport processes (<xref ref-type="bibr" rid="ref3">Bauer et al., 2009</xref>; <xref ref-type="bibr" rid="ref17">Griebler and Lueders, 2009</xref>).</p>
</sec>
<sec id="sec12">
<label>2.3.2.3</label>
<title>Model implementation</title>
<p>The field-scale model domain is split into two solution domains. One large 400&#x202F;m&#x202F;&#x00D7;&#x202F;400&#x202F;m domain for solving the fluid flow and heat transport, and a smaller 200&#x202F;m&#x202F;&#x00D7;&#x202F;200&#x202F;m domain for solving the reactive solute transport (overview in <xref ref-type="fig" rid="fig1">Figure 1</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>). Two wells were positioned 30&#x202F;m apart in the center of the domain. The western well is the injection well and the eastern well is the abstraction well. No-flow boundary conditions were assigned to the top and bottom sides of the fluid flow domain. Fixed head boundary conditions were imposed at the western and eastern side of the domain. The injection and abstraction wells were implemented as point source/sink. Physical and chemical heterogeneity was implemented using spatial random fields based on aquifer characteristics as shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S3</xref>. We assumed an initial groundwater temperature of 10&#x00B0;C in the entire field-scale domain and set fixed temperature boundary conditions at the upstream and downstream sides of the domain, with no-flux boundary conditions at the top and bottom of the domain. A fixed temperature was assigned to the injection well, representing the re-injection of heated groundwater into the aquifer.</p>
<p>The reactive solute transport was solved in a smaller domain with finer spatial discretization and a very fine mesh around the wells, where high pressure and concentration gradients could be expected. We assigned no-flux boundary conditions to all sides of the solute transport domain, except to the eastern, downstream boundary and to the abstraction well, where outflow boundary conditions were set. <xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref> shows the initial distribution of TCE in the aqueous phase and in the free NAPL phase. All chemical species were recirculated in the ATES-ISB system by evaluating the species concentration at the abstraction well and re-injecting them at the injection well using a specified flux condition. Furthermore, we added a term for the addition of lactate at the injection well. The initial DOC concentration was set to 0.125&#x202F;mM in the entire solute transport domain. Immobile <italic>Dhc</italic> bacteria were assumed present in the model domain from the beginning of the simulation. Detailed information on the model parameters is provided in the <xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>.</p>
<p>The entire model domain was spatially discretized by a mesh with 2.13&#x202F;&#x00D7;&#x202F;10<sup>4</sup> triangular elements. The mesh was refined where strong gradients were expected. The governing equations were solved with the finite-element simulation tool COMSOL Multiphysics&#x00AE; v6.1.</p>
</sec>
</sec>
</sec>
<sec id="sec13">
<label>2.4</label>
<title>Scenario simulations</title>
<p>Scenario simulations were used to explore the feasibility of ATES-ISB interventions in an aquifer contaminated with chlorinated ethenes. We used four key scenario parameters: (i) the groundwater flow velocity under natural gradient conditions, (ii) the pumping rate of the injection/extraction ATES system, (iii) the temperature of the injected groundwater, and (iv) the concentration of the injected lactate. We used the same fields of permeability, porosity, grain diameter, and fraction of organic carbon in all scenarios to ensure comparable results. The scenarios were simulated for 360&#x202F;days. <xref ref-type="table" rid="tab1">Table 1</xref> shows an overview of the sixteen scenarios that were explored in this work with the proposed numerical modeling approach described above.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Overview of ATES-ISB scenario simulations.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Scenario</th>
<th align="center" valign="top">Natural groundwater flow velocity [m/year]</th>
<th align="center" valign="top">Pumping rate [m<sup>3</sup>/h]</th>
<th align="center" valign="top">Temperature of injected groundwater [&#x00B0;C]</th>
<th align="center" valign="top">Concentration of injected lactate [mM]</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">S0</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S1a</td>
<td align="center" valign="middle">40</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S1b</td>
<td align="center" valign="middle">80</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S2a</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">5</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S2b</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S3a</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S3b</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">20</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S3c</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">40</td>
<td align="center" valign="middle">0.2</td>
</tr>
<tr>
<td align="left" valign="middle">S4a</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">S4b</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">15</td>
<td align="center" valign="middle">30</td>
<td align="center" valign="middle">0.02</td>
</tr>
<tr>
<td align="left" valign="middle">S5a</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">5</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">S5b</td>
<td align="center" valign="middle">40</td>
<td align="center" valign="middle">5</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">S5c</td>
<td align="center" valign="middle">80</td>
<td align="center" valign="middle">5</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">S6a</td>
<td align="center" valign="middle">8</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">20</td>
<td align="center" valign="middle">0.02</td>
</tr>
<tr>
<td align="left" valign="middle">S6b</td>
<td align="center" valign="middle">40</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">20</td>
<td align="center" valign="middle">0.02</td>
</tr>
<tr>
<td align="left" valign="middle">S6c</td>
<td align="center" valign="middle">80</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">20</td>
<td align="center" valign="middle">0.02</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Scenario S0 was used as a base case with optimal parameter values. The scenarios S1, S2, S3, and S4 explored the effect of different natural groundwater flow velocity, pumping rate, temperature of injected groundwater, and concentration of injected lactate on the overall biotransformation potential of the chlorinated ethenes in the contaminated aquifer. Scenarios S5 and S6 assessed in detail the effect of the natural groundwater velocity considering different combinations of operational parameter sets. The results of all scenarios were compared by means of total masses of each chlorinated ethene species integrated over the entire solution domain of the reactive solute transport problem (200&#x202F;m&#x202F;&#x00D7;&#x202F;200&#x202F;m). The set of scenarios S1 to S4, including the base case S0, are shown in the main manuscript, whereas the results of the scenario sets S5 and S6 are reported in the <xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>.</p>
</sec>
</sec>
<sec sec-type="results" id="sec14">
<label>3</label>
<title>Results and discussion</title>
<sec id="sec15">
<label>3.1</label>
<title>Simulation of temperature-dependent biodegradation in the microcosms</title>
<p>Chlorinated ethenes were biotransformed via sequential reductive dehalogenation in the microcosms. <xref ref-type="fig" rid="fig2">Figure 2</xref> shows the experimental data from the microcosm studies (<xref ref-type="bibr" rid="ref6">Bin Hudari et al., 2025</xref>), alongside with the outcome of the multi-phase biodegradation model for the four different temperatures investigated in this work. Experimental data show incomplete reductive dehalogenation of TCE to ethene for microcosms at 10&#x00B0;C and 40&#x00B0;C, whereas complete dehalogenation was observed for the experiments at 20&#x00B0;C and 30&#x00B0;C. TCE concentrations decrease more rapidly at 20&#x00B0;C and 30&#x00B0;C compared to experiments conducted at 10&#x00B0;C, where transformation products, such as cis-DCE and VC accumulate. Experimental data at the highest temperature, i.e., 40&#x00B0;C, show stable values of TCE concentration, indicating the lack of significant microbial reductive dehalogenation in these conditions. Considering the complexity of the setups with two fluid phases and a solid natural sediment, the kinetic interphase mass transfer between the phases, the temperature dependence, and the dynamic operational conditions (i.e., multiple spiking TCE spiking events for microcosms operated at 20&#x00B0;C and 30&#x00B0;C), the developed numerical model allows capturing most of the patterns and trends shown by the experimental observations. However, some trends were more difficult to capture, such as TCE concentrations observed in the microcosms held at 10&#x00B0;C. TCE is not entirely transformed to ethene in the first ~70&#x202F;days of the microcosm experiments carried out at 10&#x00B0;C. This resulted in slow degradation in the first ~70&#x202F;days and more complete degradation in the last period of the microcosms operated at 10&#x00B0;C. In addition, the gradual decrease of measured ethene in the microcosms held at 30&#x00B0;C might indicate further mass transfer or transformation of ethene. The accumulation of VC from day 65 onwards might indicate slower transformation rates of VC to ethene. The spiking events add new TCE mass to the systems operated at 20&#x00B0;C and 30&#x00B0;C, which is readily biotransformed under these optimal temperature conditions. The model indicates most complete reductive dehalogenation at 20&#x00B0;C and 30&#x00B0;C, where TCE is rapidly transformed to cis-DCE and VC, and these daughter compounds are further dehalogenated to ethene. The simulated slow dehalogenation kinetics at 10&#x00B0;C and the absence of biotransformation at 40&#x00B0;C are in line with the experimental observations collected from these respective microcosms.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Observed markers; dataset obtained from <xref ref-type="bibr" rid="ref6">Bin Hudari et al. (2025)</xref> and simulated (lines) normalized aqueous concentrations of chlorinated ethenes from batch microcosm setups at four different temperatures, <bold>(a)</bold> 10&#x00B0;C, <bold>(b)</bold> 20&#x00B0;C, <bold>(c)</bold> 30&#x00B0;C, and <bold>(d)</bold> 40&#x00B0;C. Additional TCE was spiked to microcosms operated at 20&#x00B0;C and 30&#x00B0;C after 3, 35, 56, and 70&#x202F;days (arrows at top of panels <bold>b,c</bold>).</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g002.tif"/>
</fig>
<p>In this study, the three maximum specific degradation rates of the chlorinated ethenes were adjusted to obtain a good fit between experimental data and simulation results. The fitted maximum specific degradation rates for each chlorinated ethene at each temperature (10&#x00B0;C, 20&#x00B0;C, 30&#x00B0;C, and 40&#x00B0;C), as derived from the simulation of the microcosms, are shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>. The data show a clear temperature dependence with optimum temperatures for microbial dehalogenation at 29&#x00B0;C, 26&#x00B0;C, and 25&#x00B0;C for TCE, cis-DCE, and VC, respectively, as derived by fitting an empirical model (<xref ref-type="bibr" rid="ref54">Rosso et al., 1995</xref>; <xref ref-type="bibr" rid="ref46">Popp et al., 2015</xref>). The difference in optimal temperatures is in line with previous studies investigating the effect of temperature on microbial reductive dehalogenation of chlorinated ethenes (<xref ref-type="bibr" rid="ref15">Friis et al., 2007b</xref>).</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Temperature dependence of maximum specific dehalogenation rates of <italic>Dhc</italic> for trichloroethene (TCE) <bold>(a)</bold>, cis-1,2-dichloroethene (cis-DCE) <bold>(b)</bold>, and vinyl chloride (VC) <bold>(c)</bold>. Values derived from multi-phase modeling of experimental microcosms (<xref ref-type="fig" rid="fig2">Figure 2</xref>) (markers), and fitted with the empirical model by <xref ref-type="bibr" rid="ref54">Rosso et al. (1995)</xref> (lines).</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g003.tif"/>
</fig>
<p>The temperature dependence of the maximum specific degradation rates, as shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>, is a key input for the field-scale simulations of ATES-ISB scenarios and thus links the multi-phase microcosm studies to the field-scale modeling of non-isothermal remediation interventions.</p>
</sec>
<sec id="sec16">
<label>3.2</label>
<title>Field-scale scenario simulations</title>
<p>Transient field-scale simulations, considering active pumping, heat transport, and reactive solute transport were conducted for a set of 16 scenarios with combinations of different parameters (<xref ref-type="table" rid="tab1">Table 1</xref>).</p>
<sec id="sec17">
<label>3.2.1</label>
<title>Non-isothermal flow and heat transport</title>
<p>The groundwater flow field was changed by using natural groundwater velocities from 8&#x202F;m/year to 80&#x202F;m/year. Additionally, three different pumping rates were simulated in the ATES-ISB system. <xref ref-type="fig" rid="fig4">Figure 4</xref> shows that the pumping induces a dipole flow field in the vicinity of the injection and extraction wells. The capture zone has the largest extent at low natural groundwater flow velocities (<xref ref-type="fig" rid="fig4">Figures 4a</xref>&#x2013;<xref ref-type="fig" rid="fig4">c</xref>). These velocity variations, and irregular streamlines outside the capture zone, are caused by the physical heterogeneity in the simulated aquifer system. The zones of influence of the well-doublet system decrease in size at higher natural groundwater flow velocities. Nonetheless, even at 80&#x202F;m/year and a pumping rate of 5 m<sup>3</sup>/h, a dipole flow field is observed based on the simulated streamlines and velocity distribution. The size of the capture zone has important implications for the ATES-ISB application, since it impacts the subsurface contaminated zone that can be treated and where active delivery of amendments and reactants to stimulate microbial activities can occur.</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Simulated field-scale surface maps (isothermal conditions) of the groundwater flow velocity (log<sub>10</sub> (<inline-formula>
<mml:math id="M105">
<mml:mi>v</mml:mi>
</mml:math>
</inline-formula> [m&#x202F;s<sup>&#x2212;1</sup>])) with computed streamlines at three different natural groundwater flow velocities of <bold>(a&#x2013;c)</bold> 8, <bold>(d&#x2013;f)</bold> 40, and <bold>(g&#x2013;i)</bold> 80 m/year (rows), and considering three different pumping rates, <bold>(a,d,g)</bold> 5, <bold>(b,e,h)</bold> 10, and <bold>(c,f,i)</bold> 15 m<sup>3</sup>/h (columns). The natural groundwater flow direction is from left to right. Red and blue dots indicate the injection and extraction wells, respectively.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g004.tif"/>
</fig>
<p>The fluid flow is directly affecting the transport of heat in the simulated aquifer system. <xref ref-type="fig" rid="fig5">Figure 5</xref> shows simulated surface maps of the temperature distribution at four times, at the beginning of the simulation (10&#x202F;days), after 120&#x202F;days, 240&#x202F;days, and at the end of the simulation (360&#x202F;days). The distribution of heat in the subsurface is evaluated at the three different natural groundwater flow velocities (i.e., 8, 40, and 80&#x202F;m/year) considered in this study. <xref ref-type="fig" rid="fig5">Figures 5a</xref>&#x2013;<xref ref-type="fig" rid="fig5">d</xref> indicate that the heat plume, which originates from the injection well, is not influenced much by the natural groundwater flow at low flow velocities. Contrarily, at higher natural groundwater flow velocities, the heat plume is significantly smaller and spreads in the flow direction. Furthermore, the impact of groundwater flow on heat transport has important feedback also on the reactive contaminant transport, since the temperature distribution directly affects the transport parameters and the kinetics of biotransformation reactions.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Simulated field-scale surface maps of temperature at three different natural groundwater flow velocities (scenarios S0 <bold>(a&#x2013;d)</bold>, S1a <bold>(e&#x2013;h)</bold>, and S1b <bold>(i&#x2013;l)</bold>) at 10, 120, 240, and 360 days. The pumping rate is constant at 15 m<sup>3</sup>/hour. Red and blue dots indicate the injection and extraction wells, respectively.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g005.tif"/>
</fig>
</sec>
<sec id="sec18">
<label>3.2.2</label>
<title>Reactive transport model</title>
<p>The fluid and heat transport model laid the basis for the reactive transport model, which simulated the temperature-dependent biotransformation of chlorinated ethenes considering an ATES-ISB approach. Lactate, which serves as electron donor in this study, is delivered via active pumping into the contaminated aquifer. <xref ref-type="fig" rid="fig6">Figure 6</xref> shows an example of the simulated spreading of lactate at the three natural groundwater velocities investigated in this study. Similarly to the transport of heat in the aquifer, the fluid flow significantly affects the distribution of lactate in the aquifer. The lactate spreads according to the induced dipole flow field at low flow velocities (<xref ref-type="fig" rid="fig5">Figures 5a</xref>&#x2013;<xref ref-type="fig" rid="fig5">d</xref>), whereas a lactate plume is forming downgradient of the abstraction well at higher flow velocities (<xref ref-type="fig" rid="fig5">Figures 5i</xref>&#x2013;<xref ref-type="fig" rid="fig5">l</xref>). Concurrently, the lactate plume is more spread at 8&#x202F;m/year, with smooth concentration gradients in both longitudinal and transverse direction, compared to 40&#x202F;m/year and especially 80&#x202F;m/year flow velocity. In particular, at the highest natural groundwater flow velocity of 80&#x202F;m/year, the concentration gradients are steep and sharply defined zones of lactate-rich and lactate-poor areas are present in the aquifer. Under these flow conditions, some lactate bypasses the extraction well and is transported advectively downstream towards the outflow boundary of the domain, though not reaching it at the end of the simulation time (360&#x202F;days). The area of high lactate concentrations is smaller at high flow velocity, as evident from the surface maps at the last time step (<xref ref-type="fig" rid="fig6">Figures 6d</xref>,<xref ref-type="fig" rid="fig6">h</xref>,<xref ref-type="fig" rid="fig6">i</xref>).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Simulated field-scale surface maps of lactate at three different natural groundwater flow velocities (scenarios S0 <bold>(a&#x2013;d)</bold>, S1a <bold>(e&#x2013;h)</bold>, and S1b <bold>(i&#x2013;l)</bold>) at 10, 120, 240, and 360 days. Red and blue dots indicate the injection and extraction wells, respectively.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g006.tif"/>
</fig>
<p>The reactive transport of the chlorinated ethenes was simulated in the solute transport domain, including the sequential dehalogenation of TCE to ethene and the non-isothermal kinetics observed in the microcosm experiments. <xref ref-type="fig" rid="fig7">Figure 7</xref> shows the simulated surface maps of chlorinated ethene concentrations after 360&#x202F;days at the four simulated injection temperatures (10&#x00B0;C, 20&#x00B0;C, 30&#x00B0;C, and 40&#x00B0;C). In <xref ref-type="fig" rid="fig7">Figure 7</xref>, the injection of groundwater with a temperature of 10&#x00B0;C can be considered the isothermal case, since the pristine groundwater temperature in the entire model domain is also 10&#x00B0;C. The degradation efficiency at 10&#x00B0;C is very low; only small amounts of TCE are transformed to cis-DCE and VC, with no ethene formed in the domain after 360&#x202F;days (<xref ref-type="fig" rid="fig7">Figures 7a</xref>&#x2013;<xref ref-type="fig" rid="fig7">d</xref>). The dehalogenation process is incomplete because the maximum specific degradation rate is low at a groundwater temperature of 10&#x00B0;C.</p>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>Simulated surface maps of chlorinated ethene concentrations at four different groundwater injection temperatures (rows) (scenarios S3a <bold>(a&#x2013;d)</bold>, S3b <bold>(e&#x2013;h)</bold>, S0 <bold>(i&#x2013;l)</bold>, and S3c <bold>(m&#x2013;p)</bold>) at the end of the simulations at 360 days. Red and blue dots indicate the injection and extraction wells, respectively.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g007.tif"/>
</fig>
<p>On the contrary, the injection of 20&#x00B0;C and 30&#x00B0;C warm groundwater into the contaminated aquifer results in non-isothermal transport phenomena leading to enhanced biotransformation and almost complete dechlorination from TCE to ethene (<xref ref-type="fig" rid="fig7">Figures 7e</xref>&#x2013;<xref ref-type="fig" rid="fig7">l</xref>). The produced ethene might undergo transport and mass transfer processes (e.g., from the water to the gaseous phase, particularly in the shallow portion of the aquifer close to the unsaturated zone), but it could also be further biotransformed by indigenous microorganisms present in the aquifer. These visual results are supported by the evaluation of the total masses of the chlorinated ethenes in the domain, where the scenarios at 20&#x00B0;C and 30&#x00B0;C show the best bioremediation efficiency. The injection of groundwater with a temperature of 40&#x00B0;C results in a more efficient dehalogenation compared to the scenario at 10&#x00B0;C, but the transformation from TCE to ethene is incomplete. Note that contrary to the batch experiments, where no biotransformation of TCE was observed at 40&#x00B0;C, the injection of warm groundwater at 40&#x00B0;C into the multi-dimensional domain leads to zones of optimal thermal conditions for microbial growth and contaminant dehalogenation at the fringes of the heat plume. Over the simulated time, the heat plume spreads into the aquifer. The highly bioreactive zones at the fringes of the heat plume expand, finally resulting in the spatial distribution of contaminants as shown in <xref ref-type="fig" rid="fig7">Figures 7m</xref>&#x2013;<xref ref-type="fig" rid="fig7">p</xref>. In contrast, the biological dehalogenation at 10&#x00B0;C (scenario S3a) is a scenario considering isothermal conditions, resulting in uniform, low degradation rates across the entire domain. The complex interplay between heat transport and microbial dehalogenation governs the mobility and fate of the contaminants in the multi-dimensional aquifer systems considered in this study.</p>
<fig position="float" id="fig8">
<label>Figure 8</label>
<caption>
<p>Effect of different natural groundwater flow velocities on bioremediation efficiency. Simulated contaminant mass of chlorinated ethenes (<bold>(a)</bold> TCE; <bold>(b)</bold> cis-DCE; <bold>(c)</bold> VC; <bold>(d)</bold> ethene) for scenarios S0, S1a, and S1b.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g008.tif"/>
</fig>
</sec>
<sec id="sec19">
<label>3.2.3</label>
<title>Effect of scenario parameters on contaminant mass</title>
<p>The total masses of the chlorinated ethenes were evaluated in the entire solute transport domain, allowing a quantitative interpretation of the efficiency of bioremediation for the different scenarios listed in <xref ref-type="table" rid="tab1">Table 1</xref>. First, the effect of the natural groundwater flow velocity on the overall bioremediation efficiency is analyzed. The flow velocity influences the total dehalogenation efficiency of cis-DCE and VC, with less pronounced effects for ethene (<xref ref-type="fig" rid="fig8">Figure 8</xref>). This faster biotransformation might be caused by increased mixing at higher groundwater flow velocities (<xref ref-type="bibr" rid="ref50">Rolle and Kitanidis, 2014</xref>). In the <xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref> we provide more information on the effect of the natural groundwater flow velocity on the efficiency of the ATES-ISB system (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S4</xref>).</p>
<fig position="float" id="fig9">
<label>Figure 9</label>
<caption>
<p>Effect of different pumping rates on bioremediation efficiency. Simulated contaminant mass of chlorinated ethenes (<bold>(a)</bold> TCE; <bold>(b)</bold> cis-DCE; <bold>(c)</bold> VC; <bold>(d)</bold> ethene) for scenarios S2a, S2b, and S0.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g009.tif"/>
</fig>
<p>Secondly, we investigated the effect of the pumping rate of the injection/extraction system on the overall biotransformation efficiency. <xref ref-type="fig" rid="fig9">Figure 9</xref> illustrates that a high pumping rate of 15 m<sup>3</sup>/h is preferable at the beginning of the ATES-ISB intervention. However, after 150 to 200&#x202F;days, the efficiency of scenarios considering lower pumping rates is comparable to scenarios with a higher pumping rate for most of the chlorinated ethenes investigated in this study. The pumping rate is strongly coupled to the natural groundwater flow velocity as shown in <xref ref-type="fig" rid="fig4">Figure 4</xref>. Furthermore, in this work, the pumping rate highly affects the amount of lactate injected into the aquifer system, which might explain the more efficient mass destruction of chlorinated ethenes at higher pumping rates because in fact more lactate is delivered into the contaminated aquifer (e.g., <xref ref-type="fig" rid="fig9">Figure 9a</xref>).</p>
<fig position="float" id="fig10">
<label>Figure 10</label>
<caption>
<p>Effect of different injection temperatures on bioremediation efficiency. Simulated contaminant mass of chlorinated ethenes (<bold>(a)</bold> TCE; <bold>(b)</bold> cis-DCE; <bold>(c)</bold> VC; <bold>(d)</bold> ethene) for scenarios S3a, S3b, S0 and S3c (also depicted in <xref ref-type="fig" rid="fig7">Figure 7</xref>).</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g010.tif"/>
</fig>
<p>Thirdly, the temperature of the injected groundwater was varied, and the total contaminant masses were evaluated. <xref ref-type="fig" rid="fig10">Figure 10</xref> shows the results of different injection temperatures and is linked to <xref ref-type="fig" rid="fig7">Figure 7</xref>, which shows surface maps of the identical scenarios. The isothermal scenario at 10&#x00B0;C shows slow biotransformation kinetics with incomplete transformation of TCE to ethene. In contrast, almost complete dehalogenation to the non-toxic end product ethene is observed considering an injection temperature of 20&#x00B0;C and 30&#x00B0;C. However, both scenarios show that VC is not completely transformed to ethene. The injection of 40&#x00B0;C warm groundwater leads to an improved mass destruction of TCE compared to the isothermal scenario (10&#x00B0;C), but to an accumulation of cis-DCE and VC up to 150&#x202F;days, and 200&#x202F;days, respectively (<xref ref-type="fig" rid="fig10">Figures 10b</xref>,<xref ref-type="fig" rid="fig10">c</xref>). This phenomenon is caused by the successive spreading of the injected 40&#x00B0;C heat plume into the aquifer, which results in bioreactive zones at the fringes of the expanding heat plume, where optimal conditions for microbial reductive dehalogenation are present. This dynamic system results, however, in incomplete biotransformation of TCE to ethene. Vinyl chloride concentrations in scenario S3c show, for example, the highest concentrations among all scenarios assessed in <xref ref-type="fig" rid="fig10">Figure 10</xref> at the end of the simulation after 360&#x202F;days (red solid line in <xref ref-type="fig" rid="fig10">Figure 10</xref>). In conclusion, the results show that the injected groundwater temperature strongly affects the dehalogenation efficiency in the considered ATES-ISB system.</p>
<p>Lastly, the impact of different lactate concentrations on the bioremediation efficiency of ATES-ISB interventions was investigated. <xref ref-type="fig" rid="fig11">Figure 11</xref> shows the total masses of chlorinated ethenes over time considering three concentrations (0.002&#x202F;mM, 0.02&#x202F;mM, and 0.2&#x202F;mM) of lactate injected into the simulated, polluted aquifer. Higher lactate concentrations are associated with faster and more complete contaminant mass destruction for all contaminants (TCE, cis-DCE, VC), and more efficient production of non-toxic ethene. The apparent effect of the added electron donor source suggests that lactate is limiting the extent of microbial reductive dechlorination in the ATES-ISB system considered in this study. The efficient delivery of lactate (or other suitable carbon sources) in the contaminated aquifer seems to be particularly important for the overall bioremediation efficiency of the simulated remediation system.</p>
<fig position="float" id="fig11">
<label>Figure 11</label>
<caption>
<p>Effect of different injected lactate concentrations on bioremediation efficiency. Simulated contaminant mass of chlorinated ethenes (<bold>(a)</bold> TCE; <bold>(b)</bold> cis-DCE; <bold>(c)</bold> VC; <bold>(d)</bold> ethene) for scenarios S4a, S4b, and S0.</p>
</caption>
<graphic xlink:href="frwa-07-1499448-g011.tif"/>
</fig>
</sec>
</sec>
</sec>
<sec sec-type="conclusions" id="sec20">
<label>4</label>
<title>Conclusions</title>
<p>In this study, we presented a process-based modeling framework for the interpretation and analysis of temperature-dependent biotransformation of chlorinated ethenes. The proposed model is capable of simulating biodegradation in batch microcosms, as well as field-scale reactive transport of Aquifer Thermal Energy Storage combined with <italic>in situ</italic> bioremediation (ATES-ISB), which is a promising remediation technique to foster more sustainable and efficient groundwater clean-up. The modeling framework described in this study accounts for: (i) multi-phase mass transfer limitations and temperature-dependent microbial reductive dehalogenation in batch systems, and (ii) multi-dimensional non-isothermal fluid flow, heat transport, and reactive solute transport in physically and chemically heterogeneous groundwater systems in combination with temperature-dependent microbial growth kinetics and contaminant dehalogenation.</p>
<p>Experimental microcosm studies of temperature-dependent microbial reductive dechlorination of chlorinated ethenes were interpreted using the modeling approach proposed in this work. Maximum specific transformation rates were derived, which served as input for scenario simulations of an ATES-ISB system in a sandy heterogeneous aquifer contaminated with TCE. The scenario simulations, considering one site parameter (the natural groundwater flow velocity) and three operational parameters (the pumping rate of the injection/extraction system, the temperature of injected groundwater, and the concentration of the injected lactate) were carried out to identify optimal conditions for efficient ATES-ISB interventions in polluted subsurface porous media. The scenario simulations highlight the importance of the injection temperature and the concentration of the injected lactate for complete dehalogenation of chlorinated ethenes in the considered heterogeneous aquifer system. The natural groundwater flow velocity, i.e., the groundwater velocity without active pumping, as well as the pumping rate of the ATES-ISB system were found to be of lower significance for efficient remediation of the aquifer considered in this study. The natural groundwater flow velocity and pumping rate are, nonetheless, important since they control the delivery of the injected heated water and solutes in the aquifer. Future investigation should address more explicitly the interplay between non-isothermal biodegradation and groundwater chemistry to explore the interactions between the beneficial effects of ATES-related higher temperatures for <italic>in situ</italic> chlorinated compounds biotransformation with concurrent effects of increased temperature in shallow aquifers. The latter include the potential release of dissolved organic carbon (<xref ref-type="bibr" rid="ref8">Brons et al., 1991</xref>; <xref ref-type="bibr" rid="ref24">Jesu&#x00DF;ek et al., 2013</xref>), which could provide electron donor and substrate to sustain reductive dehalogenation, as well as of metals and metalloids that could impact bacteria activity and groundwater quality (<xref ref-type="bibr" rid="ref7">Bonte et al., 2013</xref>; <xref ref-type="bibr" rid="ref29">L&#x00FC;ders et al., 2020</xref>).</p>
<p>This scenario modeling study explored the feasibility of ATES-ISB approaches by combining non-isothermal microcosm reductive dehalogenation and field-scale reactive transport modeling. The interplay of temperature-dependent physical, chemical, and biological processes controls the bioremediation efficiency of such ATES-ISB interventions. The modeling framework described in this work is helpful for the identification of controlling mechanisms and optimal parameters in complex subsurface remediation systems, such as ATES-ISB. Furthermore, the developed modeling approach can be used for planning, designing, and guiding remediation setups for non-isothermal bioremediation interventions.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec21">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="sec22">
<title>Author contributions</title>
<p>HW: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing &#x2013; original draft. MB: Conceptualization, Data curation, Investigation, Writing &#x2013; review &#x0026; editing. KM: Conceptualization, Methodology, Supervision, Writing &#x2013; review &#x0026; editing. CV: Conceptualization, Writing &#x2013; review &#x0026; editing. IN: Conceptualization, Resources, Writing &#x2013; review &#x0026; editing. MR: Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec23">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Independent Research Fund Denmark (project BiodegrATES, grant DFF 0136-00205B).</p>
</sec>
<sec sec-type="COI-statement" id="sec24">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The reviewer ZN is currently organizing a Research Topic with the author IN.</p>
</sec>
<sec sec-type="disclaimer" id="sec25">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec26">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/frwa.2025.1499448/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/frwa.2025.1499448/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.pdf" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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