A Summary of Research Progress on Bioavailability Assessment Method of Selenium in Soil and Its Influencing Factors
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摘要:
硒是人体必需的微量元素之一。土壤-植物体系是人体摄入硒的主要途径，但尚缺乏准确评价土壤中硒生物有效性的通用方法，且影响因素也复杂多样, 这些问题制约了富硒土地资源的利用。本文通过追踪近年来国内外研究成果，系统地总结及比较了化学提取法、梯度扩散薄膜法、区域尺度硒生物有效性评价方法的优缺点。传统的化学提取法如单一提取和顺序提取在一定程度上能够表征土壤中生物有效性硒，但提取过程中存在影响因素多和提取不完全等问题。梯度扩散薄膜技术(DGT)能够模拟植物的根系吸收过程，相比顺序提取能更好地表征硒的生物有效性，但由于复杂的自然体系和不同元素结合相的差异，野外原位表征技术上仍存在难度。通过大规模的农作物-根系土样本，建立土壤-农作物硒元素评价模型，模型参数为影响土壤硒有效性的理化指标(如土壤酸碱度、有机质含量、土壤硒总量等)，能较好地预测区域尺度上硒生物有效性。本文还总结了影响植物吸收土壤中硒的因素如地形、土壤类型、硒的存在形态、土壤理化性质、植物种类、土壤老化等，认为地形和土壤类型、硒的存在形态、酸碱度和有机质是影响有效硒的主要因素，植物种类与土壤老化为次要因素。完善DGT等原位分析检测技术、改进元素形态分析方法是未来发展的重要方向。
要点(1) 化学提取法和梯度扩散薄膜技术在表征硒生物有效性上仍存在不足。
(2) 区域尺度土壤硒的生物有效性评价模型预测的成功率较高。
(3) 成土母质及土壤理化性质是影响植物吸收土壤硒的主要因素。
HIGHLIGHTS(1) The chemical extraction method and DGT technology are limited in accessing the bioavailability of soil selenium.
(2) The soil selenium bioavailability assessment models are acceptable at the regional scale prediction.
(3) Soil parent materials and soil physicochemical properties play a significant role in determining the uptake of soil selenium by plants.
Abstract: Selenium (Se) is a trace element that plays a crucial role in human health. It has antioxidant, anti-cancer and anti-viral properties and is essential for a healthy body. The level of Se in the human body is largely dependent on daily dietary intake, which is in turn influenced by the amount of Se that enters the food chain from the soil. The global distribution of Se in soil is uneven, with a large difference in concentrations ranging mainly between 0.01-2.0mg/kg. The average abundance of Se in the Earth's crust is 0.07mg/kg, but in some Se-enriched areas, it can reach up to 1200mg/kg. The chemical behavior of Se in soils is complex and diverse, involving processes such as adsorption-desorption, precipitation-dissolution, oxidation-reduction, methylation-demethylation and complexation reactions, each of which affects the bioavailable Se and is influenced and conditioned by factors such as soil pH, soil organic matter, metal oxides, clay and microorganisms. Roots are the primary site for most plants to absorb Se, which is then transported, metabolized, and accumulated. Plants can directly absorb Se from the soil, including Se that exists in the form of free ions, carbonate-bound Se, and Se adsorbed on the surfaces of clay and humus in soil solutions. However, selenite and selenate can be reduced to solid, insoluble Se(0) and metal-Se precipitates that are not bioavailable in locally anaerobic areas (such as soil aggregates) or used by bacteria as terminal electron acceptors.Previous researchers have conducted a lot of work on chemical extraction methods, but there are still problems, such as insufficient extraction specificity and Se form transformation during the extraction process. Hence, an accurate approach for predicting the amount of soil Se that can be absorbed by plants is essential. However there are no clear paths for the choices of assessment methods and influencing factors of soil Se bioavailability. These problems have restricted the utilization of Se-enriched land resources. Thus, providing a scientific basis for the development and utilization of Se-enriched land resources is the goal here by summarizing the main assessment methods and dominant factors on soil Se bioavailability.Determining the activity of Se in soils comprehensively requires considering the complicated and varied effects of natural conditions on its bioavailability, which can be studied through characterization methods and identification of influencing factors. Therefore, it is of practical importance and a challenge to accurately determine the form of Se in soils and assess its bioavailability. Current methods for characterizing the bioavailability of soil Se include the traditional chemical extraction methods (single extraction and sequential extraction) and the emerging Diffusive Gradients in Thin films (DGT) technique. Chemical extraction is a process that involves separating a specific component or substance from a mixture using a solvent or a chemical reagent. The extraction method depends on the physical and chemical properties of the substance being extracted and the nature of the mixture. The general steps involved in a chemical extraction method are: choosing the appropriate solvent or chemical reagent that can selectively dissolve the desired substance while leaving the unwanted components behind, mixing the mixture and the solvent/reagent together to allow the selective extraction of the desired substance, separating the extracted substance from the mixture using various techniques such as filtration, centrifugation, or evaporation, and purifying and isolating the extracted substance by further chemical or physical methods if necessary. The DGT technique is an effective environmental chemistry method used for identifying elements and compounds in various aqueous environments, including natural waters, sediments, and soils. This technique is particularly useful for detecting bioavailable trace elements, and it can be applied for in-situ detection. The DGT technique involves using a specially-designed passive sampler that comprises a binding gel, a diffusive gel, and a membrane filter. The element or compound of interest passes through the membrane filter and diffusive gel before being assimilated by the binding gel in a rate-controlled manner. Subsequently, the binding gel is analyzed post-deployment, enabling the determination of the time-weighted-average bulk solution concentration of the element or compound via a simple equation.The advantages and limitations of chemical extraction methods, DGT technique and bioavailability assessment models of Se at a regional scale are compared. Traditional chemical extraction procedures such as single extraction or sequential extraction can be used to characterize the bioavailability of Se in the soil, to a certain extent. Still, the extraction process has many limits and incomplete extraction problems. The DGT method can be used to simulate the root uptake process of plants and can better characterize the bioavailability of Se compared to sequential extraction. One of the major advantages of the DGT technique is its ability to provide accurate and reliable results, even at low concentrations. Additionally, this technique is non-destructive and can be used in-situ, making it suitable for real-time monitoring of environmental conditions. However, there are also some limitations associated with the DGT technique. For instance, the binding gel used in this method may not be specific to the target element or compound, leading to the possibility of cross-reactivity with other substances. Additionally, the technique may be influenced by factors such as temperature, pH, and ionic strength, which could affect the accuracy of the results. Using large-scale crop-root soil samples, a soil-crop Se assessment model was developed with parameters of physicochemical indicators (e.g. soil pH, soil organic matter, soil Se, etc.), which can better predict Se bioavailability on a regional scale.Some major and minor influencing factors affecting the uptake of Se in soil by plants are discussed. In short, topography and soil type, Se species, pH and organic matter are the main factors affecting bioavailable Se, with plant species and soil aging as secondary factors.In brief, the main limitations of the characterization methods for the bioavailability of different forms of Se are: a single extraction method can be affected by soil properties, soil/solution ratio, extraction time, the pH value of the extraction agent, and other factors. Sequential extraction methods have problems with incomplete extraction, dilution of the extract, and Se loss during centrifugation and filtration. These traditional methods cannot be used to reflect the dynamic processes of the solid-phase soil-solution-root system. DGT technology is a method that disturbs the equilibrium between soil solution and solid phase, simulating the dynamic process of Se uptake by roots, and has advantages in assessing bioavailability. However, it is still questionable whether it can be used to fully predict the replenishment dynamics of Se in field soil. The main factors affecting the bioavailability of soil Se are: (1) Topographical factors such as altitude, slope, and terrain wetness index, which have some influence on soil Se content; there are large differences in organic matter, iron/aluminum hydroxides, and pH among different soil types, which can be controlled to affect Se migration and bioavailability; (2) Soluble and exchangeable Se are more easily absorbed by plants, and selenate with better mobility is easier to absorb, transport, and metabolize in plants than selenite; (3) Increasing soil pH can generally improve Se bioavailability, but this is not the case in organic-enriched soils. Currently, there is no universally applicable method for evaluating soil Se bioavailability, as it is influenced by many factors such as topography, soil type, and soil physicochemical properties. This makes it difficult to compare and verify different results. Improving in-situ DGT analysis technology and modifying the analysis of Se forms are important technical means for accurately evaluating soil Se bioavailability and are also important directions for future development.
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Keywords:
- selenium /
- soil /
- bioavailability /
- influencing factors /
- chemical speciation /
- assessment method
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原位化学氧化(In-situ Chemical Oxidation，ISCO)是指利用合适的输送技术将氧化剂输送到土壤或含水层中，通过化学氧化作用将污染物转化为低毒或者无毒物质，由于反应高效、性价比高等特点，ISCO修复技术已经在土壤和地下水的有机污染修复中得到了广泛应用[1-3]。氧化剂用量是应用中的一个关键参数，当氧化剂用量不足时，污染场地的修复可能达不到工程的目的要求，易形成残留污染物或反应中间产物，导致场地污染物浓度发生反弹[3-6]；当氧化剂用量过多时，则可能会严重破坏土壤理化性质，降低微生物群落的多样性，增加工程的修复成本[7-12]。因此，ISCO中所使用的氧化剂剂量的准确测定是确定污染场地治理效果的关键，对于最终获得良好的修复效益具有重要的意义[13]。
ISCO工程中所需氧化剂的剂量通常用氧化剂需求量来衡量。经过调研总结，目前针对氧化剂需求量的测算方法可以划分为实验法和化学计量模型法两类[14-15]，实验法又可以分为批实验法、柱实验法、注抽实验法以及基于这三者的反应动力学模型法[7-8, 16]。在不断的发展实践中，实验法中的批实验法得到了较为广泛的探索，尤其是美国材料试验协会(ASTM)提出的相关标准(D7262)有力促进了其标准化的应用。化学计量模型法则直到近年来与Li等[13]和Ranc等[14]提出了新的模型才有了较大的发展。
然而，上述方法的研究依然存在不足：一是相关概念定义不统一，不同文献中术语定义不同；二是缺乏对不同种类的氧化剂需求量的考量，当前氧化剂需求量的测定方法主要针对高锰酸钾氧化剂，对其他种类的氧化剂的探究还相对较少；三是对氧化剂自然分解量的测算研究还略有不足。本文根据国内外研究现状，对氧化剂需求量的组成及定义进行讨论和梳理，在此基础上，对各种氧化剂需求量测算方法的使用特点和应用现状进行了综述，同时对当前方法在不同氧化剂种类条件下的应用、氧化剂自然分解量的测算进行了一定探讨。相关内容有助于人们了解氧化剂需求量测算方法的原理与现状，并为今后开展相关研究提供依据和建议。
1. 氧化剂需求量的组成与定义
当氧化剂被注入到受污染的土壤或含水层之后，氧化剂除了与目标污染物发生反应，同时还与介质中的天然有机质(Natural Organic Matter，NOM)以及Fe2+、Mn2+、S-、S2-等还原性矿物质(Reductive Mineral，RM)发生反应[16-20]，并且伴随着由于氧化剂自身性质而发生的自然分解，如芬顿试剂和臭氧会分解成氧气等[21]。为了更好地表示氧化剂需求量的组成，研究者使用了许多术语，如总氧化剂需求量(Total Oxidant Demand，TOD)[7, 21-24]、土壤氧化剂需求量(Soil Oxidant Demand，SOD)[13, 18, 25-27]、天然氧化剂需求量(Natural Oxidant Demand，NOD)[7-9, 15, 16, 21-24, 28-30]以及氧化剂分解量(Decomposed Oxidant DEO，DEO)[17, 21, 24, 29]等。这些术语具体含义尚不统一，易产生歧义，常常在不同的研究中被混用。例如，由于SOD未明确是否包含土壤中的污染物对氧化剂的需求量，常常与TOD或NOD混用。
本文根据已有术语的定义及使用情况，进一步考虑介质类型和氧化剂消耗的组成，将相关术语关系及定义梳理总结列于表 1。同时明确SOD指的是土壤中的天然有机质和矿物质所消耗的氧化剂剂量，它是NOD的一部分，也可以称为土壤的NOD。
表 1 氧化剂需求量相关术语及定义Table 1. Terms and concepts related to oxidant demand氧化剂需求量相关术语 定义 污染物氧化剂需求量
(Pollutant Oxidant Demand，POD)污染物氧化降解所消耗的氧化剂量 天然氧化剂需求量
(Natural Oxidant Demand，NOD)土壤或含水层介质中的天然有机质和还原性矿物质所消耗的氧化剂量 氧化剂分解量
(Decomposed Oxidant, DEO)氧化剂因本身的性质以及环境条件的影响而自然分解，未能参与到氧化反应过程中的那部分剂量 需要特别指出的是，表 1所列术语的单位统一为g、kg或mol氧化剂，而非前人文献中通常使用的氧化剂需求量单位：g氧化剂/kg介质，因为绝大部分前人的研究中氧化剂的需求量都是针对单位质量介质而言的。如Dangi等[31]通过总结指出，单位质量土壤的高锰酸钾NOD可以达到0.4~50.0g/kg。研究者们还指出，介质中的天然物质可能比污染物对氧化剂的需求更高[32]，它们之间的竞争可能对氧化剂的用量、扩散程度、氧化反应速率以及污染物的去除效率产生显著影响[7, 14, 20, 28, 33-36]。因此，POD和NOD的测算均受到了研究者们的重视，而对于DEO，目前的测算方法对其关注尚且不足。本文在对现有测算方法进行综述的基础上，对DEO的测算进行了一定探讨。
2. 实验法测算氧化剂需求量
实验法是较为经典的氧化剂需求量测算方法，基本原理是：将经过粉碎、干燥及其他方法处理的介质样品与氧化剂在一定体系内混合反应一段时间，通过计算反应前后氧化剂的消耗量进而得到单位介质的氧化剂需求量。其基本的数学表达式为：
$$ \mathrm{NOD}_{\mathrm{t}} / \mathrm{TOD}_{\mathrm{t}}=\frac{\left(C_1-C_2\right) \times V}{m_{\mathrm{s}}} $$ (1) 式中：C1、C2分别表示反应前后氧化剂浓度，单位为g/L；V表示加入的氧化剂溶液体积，单位为L；ms表示介质样品质量，单位为kg；t表示时间，单位为小时(h)或天。需要指出的是，由于并未特别考虑氧化剂的DEO，此处的TOD指的是POD和NOD之和，单位均为：g氧化剂/kg。在该基础上，场地总NOD值或总TOD值则还需乘以污染区域介质的总质量。
根据实验的尺度和维度的逐渐增加，实验法可以分为批实验法、柱实验法和注抽实验法，以及基于上述三种方法，利用动力学模型预测更长时间尺度上的氧化剂需求量的反应动力学模型法。
2.1 批实验法
Haselow等[7]提出利用比色技术(Colorimetric Techniques)来估算单位土壤或含水层的TOD，该方法实质上就是基于上述原理的批实验法(Batch Test)。经过不断发展，ASTM[15]提出了测算单位质量土壤或含水层固体的高锰酸钾天然氧化剂需求量的标准试验方法。王文坦等[37]提出了土壤的化学需氧量的测定方法专利，促进了批实验法在国内外的标准化应用。批实验法具有操作简便、高效、对不同场地介质和不同的氧化剂种类适应性较强等特点，在许多污染修复研究中得到运用[25, 27, 38-39]。
批实验法的结果受到许多因素的影响，包括氧化剂的初始浓度、反应时间、反应的固液比以及反应的混合条件等。前人对批实验中相关影响因素及影响机制进行了大量探究，可以总结得出：更高的氧化剂浓度和更长的反应时间意味着氧化剂与污染物之间更充分的反应，但这也带来了更高的氧化剂消耗[13, 31]；固液比对实验的影响与氧化剂是否充足以及反应时间有关[21, 31]；搅拌混合可以促进氧化剂与土壤含水层介质充分反应[31]，但可能不符合实际的应用情况，因为在实际条件下氧化剂与介质的接触并没有这样充分。为了便于不同研究或修复工程数据的对比，支撑工程的成本核算，根据实验影响条件，批实验中NOD或TOD科学的表达方式应该为特定样品与一定浓度的特定氧化剂，在一定的固液比、温度和混合条件下反应一定时间时的氧化剂的消耗量，并且某一场地某一氧化剂的NOD或TOD应该是一组数据。因此，比较严谨的氧化剂需求量的表述方式为：NOD/TOD(XX浓度YY氧化剂，固液比，反应温度，反应时间，混合条件)。例如，NOD(0.5mol/L KMnO4，1∶5，25℃，48h，充分混合)，表示使用0.5mol/L的高锰酸钾溶液，固液比为1∶5，反应温度为25℃，反应时间为48h，充分混合条件下的天然氧化剂需求量。同理，柱实验和注抽实验测算值的表达也应是如此，只是需要考虑的因素有所差别。
研究者们在利用批实验法测算高锰酸钾的氧化剂需求量时发现，氧化剂的消耗速率在一定时间后会发生显著降低，尔后呈现出较长时间的缓慢消耗，即存在钝化现象和拖尾现象。发生钝化现象的所需时间随着高锰酸钾浓度升高而变短，拖尾现象则可以持续到14天以上[31]。Xu等[40]指出，钝化现象与高锰酸钾氧化剂的特征产物MnO2生成有关。拖尾现象则可能是由于介质中部分反应物与氧化剂反应较慢，或是吸附在介质上的相关还原性物质解吸较慢。钝化现象和拖尾现象的存在延长了实验的时间，使得氧化剂需求量的测算变得困难、复杂。ASTM的标准方法中是以48h处的氧化剂消耗量作为测定值，根据钝化现象和拖尾现象，这具有一定风险[6]，因为此时获得的氧化剂消耗量可能并未达到最高。在不同反应时间条件下，氧化剂的消耗量可能有较大差距。如Dangi等[31]的测试结果表明，在高氧化剂浓度下，48h和14天时所获得的高锰酸钾NOD值相差可以达到前者的37%。如果等待氧化剂与样品反应完全、氧化剂消耗量达到相对稳定，则可能需要耗费较长的时间。考虑到ISCO工程的主要目的是有效地降低污染物的浓度，实验时间不应该是一个固定的时间，而应是污染物浓度在氧化作用下降低到目标值以下所需要的时间。Xu等[41]提出了一种改进的方法用于测定样品的NOD或TOD最大值，即对介质样品进行了进一步的酸化、加热等处理，以促进介质中的物质与高锰酸钾发生更加充分、快速的反应，避免拖尾现象。该方法所得的测算值是介质中的物质完全氧化所需的氧化剂的剂量，ISCO工程可能并不需要完全满足天然物质对氧化剂的需求[22]。因此，上述方法的测算值可能偏大。
批实验法已经得到了较为广泛的研究和实践，但还具有进一步优化的空间。由于具有简便、高效的显著优势，该方法将仍然是最受青睐的氧化剂需求量测算方法。批实验法可以显示出氧化剂需求量与时间的变化关系，而柱实验法在此基础上可以进一步模拟氧化剂在介质中实际运输中的氧化剂消耗。
2.2 柱实验法
柱实验(Column Test)的大致方法是：将场地介质填充到实验柱中，通入一定浓度的氧化剂，观察氧化剂浓度在时间和空间上的双重分布，通过流经实验柱前后氧化剂含量的变化获得NOD或TOD值。氧化剂含量的变化可通过反应前后氧化剂浓度变化获得[42]，也可以通过对穿透曲线的积分来获得[8]。在柱实验中，氧化剂与介质之间的固液比、混合条件将不再是实验所考虑的重要因素。而氧化剂浓度和反应时间的影响机制则与批实验中相同[43]。Xu等[44]研究发现，从柱实验中测得的高锰酸钾NOD值是批试验中7天时所测得的NOD值的0.1~0.5倍，这说明批实验和柱实验法的测算结果可能有较大差异。由于考虑了氧化剂的流动运输，氧化剂与介质之间的接触更加符合实际情况，柱实验被认为更能够反映出氧化剂在场地介质中的实际消耗[8, 44]。
尽管柱实验法的准确性具有一定优势，但该方法并未得到广泛的研究应用，也未形成较为清晰的操作和计算流程。推测造成这一现象的主要原因是柱实验的操作和计算都较为繁琐和复杂。如当介质非均质性较强导致所需测定的样品较多时，工作量和实验成本将显著增加。在这样的背景下，柱实验的下一步发展方向应是形成较为完整的工作流程，同时进一步探究与批实验测算值之间的联系或差异。
2.3 注抽实验法
Mumford等[16]提出使用注抽实验(Push-Pull Test，PPT)来测定含水层介质的NOD。注抽技术起源于石油工业，主要用途是确定介质中的剩余油饱和度、介质水文地质参数[45]，后来被广泛用于地下水的原位修复中，尤其对于场地中非水相液体(NAPL)污染的修复具有重要意义[46]。通过该方法测算氧化剂需求量的主要操作是：通过注入装置将已知含量的氧化剂和示踪剂混合注入到含水层中，在经过一段时间的反应后测定剩余氧化剂的含量，通过反应前后的差值进而估算含水层介质的NOD或TOD[16]。其中，示踪剂用来控制样品的回收率。该方法的基本原理与2.1中所述原理相同，由于在场地尺度上进行，因此也可以称为场地实验或是中试实验[47]。Ko等[48]利用简单的单井注抽试验对ISCO工程场地中TCE的降解率和高锰酸盐的消耗率进行了估算，显示出了较好的适用性。Mathai[46]设计了数值模型“PPT-ISCO”来模拟注抽试验，用于评估天然氧化剂需求量大小和ISCO的有效性，并且探究了注抽实验在NAPL相污染物修复效果调查和氧化剂需求量测算中的应用，推动了注抽实验法的数值模拟应用。
目前，注抽实验法的应用并不广泛。其主要优点在于可以有效地克服实验室条件与实际场地环境条件不同所导致的误差，获得比实验室试验更具代表性的测定值[46]，可以在场地原有的监测井中进行以节约部分成本[16]。但同时，该方法的大规模使用仍面临一些困难：一是其准确性依赖于对与氧化剂发生接触的含水层介质体积和质量的准确估算；二是当场地介质条件或污染物分布较为复杂时，需要进行多次实验；三是该方法适用于含水层介质，对于土壤非饱和带的适用性还有待进一步的验证。尽管如此，注抽实验法对于验证氧化剂需求量的实验室测算结果以及探究NAPL污染源区的氧化剂需求量仍具有重要意义。在进行ISCO设计时，柱实验和注抽实验通常会被用来探究氧化剂的输送以及实际的氧化修复效果，可以在进行这些探究的同时考虑进行氧化剂需求量的测算，进而避免更多的操作和成本消耗，将有利于促进两种方法的发展与应用。
2.4 反应动力学模型法
反应动力学模型法(Reaction Kinetics Model)是指在实验基础上，对反应过程中氧化剂的消耗量进行动力学分析，从而能够在更长的时间尺度上刻画氧化剂的消耗，这对于反应时间较长的高锰酸钾或过硫酸钠氧化具有较大的意义。Mumford等[8]在批、柱实验的基础上提出了t时刻高锰酸钾NOD值与理论NOD最大值之间的关系拟合模型：
$$ \mathrm{NOD}_{\mathrm{t}}=\mathrm{NOD}_{\text {est }} \times(a \ln t+b) $$ (2) 式中: NODest为利用化学计量模型计算的理论最大值，将在化学计量模型法中介绍，a和b为拟合参数。Xu等[40]给出了高锰酸钾反应NOD最大值与7天时测得的NOD值之间的关系模型，式中的NODmax是根据反应动力学图像估算出的最大值：
$$ \mathrm{NOD}_{\max }=1.5 \times \mathrm{NOD}_7+0.7 $$ (3) 上述模型能够帮助人们在不需要进行长时间的实验情况下估算介质的NOD最大值，具有使用简便的优势，但需要考虑适用的氧化剂浓度等条件。ASTM的标准中给出的基于实验室测定的高锰酸钾消耗的一级动力学模型[15]，该模型考虑到了高锰酸钾氧化反应的钝化，并将反应过程划分为快速反应和缓慢反应两个阶段，两个阶段的分界点为反应速率变化的拐点。最终表达式为：
$$ \mathrm{d}\left[\mathrm{KMnO}_4\right] / \mathrm{d} t=-k_{\mathrm{f}} a\left[\mathrm{KMnO}_{4 \mathrm{f}}\right]-k_{\mathrm{s}} b\left[\mathrm{KMnO}_{4 \mathrm{s}}\right] $$ (4) 式中：[KMnO4f]和[KMnO4s]分别为快速反应和缓慢反应阶段的KMnO4浓度；kf和ks分别为快速反应和缓慢反应的阶段一级反应动力学常数；a和b分别表示参与快速反应阶段和缓慢反应阶段的KMnO4的质量占总质量的比例，可以通过测定反应初始KMnO4质量以及拐点处KMnO4的质量来确定。该模型的主要优点是标准化，缺点是使用成本相对较高。
反应动力学模型法目前仅被用来估算介质的NOD。除此之外所面临的主要问题是，现有模型在不同实验条件下的适用性尚不明确，同时缺乏对高锰酸钾之外的氧化剂的研究，这都应是其进一步发展的方向。
综上所述，由于简便、高效的突出特点，批实验法是目前最受关注、应用最为广泛的氧化剂需求量测算方法，但由于主要针对的是高锰酸钾氧化剂，尽快推出针对其他种类氧化剂的标准方法是当前较为迫切的工作。而柱实验法和注抽实验法被认为更能代表氧化剂的实际消耗，进一步探究并量化三种方法测算结果的差异性、推出柱实验法和注抽实验法的标准实施流程将是下一步工作的难点。
3. 化学计量模型法测算氧化剂需求量
化学计量模型法是指通过建立氧化剂需求量与介质中各个组分之间化学计量关系模型来得到理论的氧化剂需求量值。化学计量模型法的初期探索是探究介质中总有机碳与氧化剂需求量之间的关系。如Hendrych等[49]指出，天然介质的高锰酸钾NOD与介质中的有机碳含量在很大范围内呈线性关系，Xu等[40]提出了利用有机碳含量计算NOD的经验模型。在不断发展中，研究者们进一步关注到有机污染物以及介质中的还原性矿物对氧化剂的需求。Ranc等[14]提出了针对介质中多环芳烃污染物的POD的计算模型(原文中用化学计量需求量(Stoichiometric Oxidant Demand，SOD)表示，单位为mol)：
$$ \mathrm{POD}=m \times 10^{-6} \times \sum\limits_{i=1}^n \mathrm{SMR}_i \times \frac{C_i}{M_i} $$ (5) 式中：Ci和Mi分别代表第i种多环芳烃化合物的浓度(mg/kg)和摩尔质量，m指介质质量，SMRi指氧化剂与污染物之间的化学计量摩尔比(Stoichiometric Molar Ratio)，即理论上将1mol目标污染物氧化为二氧化碳所需的氧化剂的摩尔质量，一般通过化学反应方程获得。该模型的显著优势是被证明可以在不同氧化剂种类条件下使用，如Bendouz等[50]利用式(5)计算了芬顿试剂和过硫酸钠降解污泥中多环芳烃污染物的POD。
Li等[13]统筹考虑了天然有机质和其他矿物离子以及有机污染物的氧化剂需求量，提出单位介质的TOD计算模型：
$$ \begin{aligned} \mathrm{TOD}_{\text {est }}= & M \times\left(R_1 \times \sum\limits_{i=1}^n W_i \times \frac{C_i}{M_1}+o p \times R_1 \times \frac{\mathrm{NOC}}{M_1}+\right. \\ & \left.R_2 \times \frac{\mathrm{Fe}}{M_2}+R_3 \times \frac{\mathrm{Mn}}{M_3}+R_4 \times \frac{\mathrm{S}}{M_4}\right) \end{aligned} $$ (6) 式中：M、M1、M2、M3、M4分别代表KMnO4、碳、铁、锰、硫元素的摩尔质量；R1、R2、R3、R4分别代表KMnO4获得的电子数与被氧化原子失去的电子数之比；op为天然有机质的最大氧化率，与KMnO4浓度有关；n为有机污染物种类数；NOC为天然有机碳的含量(g/kg)，TODest表示单位介质理论计算的TOD最大值。Ci和Wi分别代表第i种污染物的浓度(g/kg)和碳的质量分数；Fe、Mn和S分别代表背景土壤中铁、锰和硫的浓度(g/kg)。
通过对式(6)中组分的选择，可以实现对NOD或POD理论值的计算。该模型的提出基于两个基本的假设：一是氧化剂与介质、污染物充分接触；二是有机物、还原性矿物与氧化剂完全反应[13]。在这样的假设下，测算值将不可避免地偏大，因此在计算NOD时可以与式(2)联立来获得更贴合实际的NOD值。
化学计量模型法的测算结果依赖于模型的准确性以及对介质中相关组分含量的准确测定。与实验法相比，化学计量模型法可以有效地避免实验因素对结果的影响，对于不同的场地介质也具有较好的适用性。它作为一种简便、高效、经济的氧化剂需求量测算方法，具有较好的应用前景。但同时，该方法需要进一步探索在其他种类的氧化剂条件下的适用性，并在更多的实际应用中加以论证。
4. 不同种类氧化剂需求量和氧化剂分解量的测算方法现状
无论是实验法还是化学计量模型法，多以高锰酸钾氧化剂作为研究对象，缺乏对芬顿试剂、臭氧以及过硫酸钠等氧化剂需求量的探究。
批实验法已经被应用到过硫酸钠氧化剂需求量的测定中[37, 51]。Liu等[20]利用批实验探究了过硫酸钠降解氯化挥发性有机化合物时与土壤介质的相互作用，发现土壤的过硫酸钠NOD值可以达到16.8~40.2g/kg，占据了TOD的较大比重。Dangi等[32]也利用批实验法进行评估发现，由于在高浓度条件下会发生活化而导致更充分的氧化反应，过硫酸钠NOD值在低浓度和高浓度下的差别明显比其他氧化剂高。因此，未来批实验法研究中需要特别关注不同活化条件下的过硫酸钠氧化剂需求量的测算，而其他实验法以及化学计量模型法的应用则都还有待进一步的发展和实践。
对于芬顿试剂与臭氧等分解性较强的氧化剂，DEO可能成为TOD的重要组成部分。如Baciocchi[36]指出芬顿试剂由于歧化反应产生的DEO可达到TOD的50%以上；高锰酸钾和过硫酸钠等氧化剂尽管分解性不强，但如果场地修复时间较长，则其DEO可能不能轻易忽略。对于过硫酸钠与高锰酸钾的分解量的测算，在实验法测算过程中伴随着氧化剂的自然分解，因此DEO实则已经被考虑在内。而对于芬顿试剂和臭氧，两者的自然分解半衰期一般以小时计，分解速率较高，与物质反应的速率较快，并且分解产生气体或本身是气体，为实验法测算带来了很大挑战。如王文坦等[37]提出的批实验法专利中指出，该专利适用于溶质质量分数在10%以下的芬顿试剂或过氧化氢溶液。而Xu等[52]通过进行批、柱实验指出，由于较大的固体质量与溶液体积比，芬顿试剂柱实验中分解速率常数比在批实验中更高，说明两种方法测得的NOD值可能有较大差异。这意味着将芬顿试剂氧化剂需求量的批实验测定值直接应用到实际中去必须谨慎，需要进一步的探索和验证。除此之外，DEO的刻画难点还在于会受到氧化剂注入速率、注射井设置等项目施工状况的影响。例如，在利用注射井注射氧化剂时，如果注入浓度和注入速率较高，会在注射井附近产生高温区域，可能会造成氧化剂的大量分解[21]。
除了批实验法，柱实验法、注抽实验法的操作均更加复杂，而化学计量模型法则是未考虑氧化剂的自然分解，因此可行性均有待发展验证。考虑到各方法的应用现状，本研究较为推荐利用注抽实验法进行估算，即不苛求进行准确的测算，在缓慢注入氧化剂的同时测定污染物的含量，当含量降至目标值以下时，以此时的氧化剂输入量为测定值，进行场地TOD的估算。该方法可以在进行氧化剂的修复效果的场地中试实验中进行。在实际的ISCO工程应用中，更受关注的可能依然是如何控制芬顿试剂和臭氧的氧化和分解速度。
5. 结语与展望
本文在对氧化剂需求量的组成和定义进行梳理的基础上，对比阐述了不同的氧化剂需求量测算方法的特点和使用现状。研究发现，原位化学氧化(ISCO)中总氧化剂需求量(TOD)由污染物氧化剂需求量(POD)、天然氧化剂需求量(NOD)和氧化剂分解量(DEO)三部分构成，氧化剂需求量的测算方法主要包括实验法和化学计量模型法，实验法中的批实验法的应用最为广泛，而化学计量模型法经过不断的发展，表现出了较大的应用潜力。考虑到实验法中不同时间点获得的氧化剂需求量的差异，提出把污染物浓度在氧化作用下降低到目标限值所需要的时间作为氧化剂需求量的测定时间，同时使用带有测试条件的表达方式从而更精准地提供氧化剂需求量。目前的氧化剂需求量测算方法对高锰酸钾、过硫酸钠等分解性较低的氧化剂表现出较好的适用性，而对于芬顿试剂和臭氧等分解性较强的氧化剂，则由于DEO占据TOD的较大比重，准确测算仍面临困难。
作为容易被忽略的TOD的组成部分，DEO的重要性需要进一步明确，同时探索更准确的测算方法。在实际工程中，注入井数量、注入井间距、氧化剂注入速率等施工参数都会对总的氧化剂需求量产生影响，需要进一步的探究。原位化学氧化修复污染场地是一个复杂的工程，氧化剂需求量的测算仍需一个更为科学的工作流程或指南。
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图 1 土壤-植物系统中硒的生物有效性和相关的化学反应(据Dinh等[15]修改)
Figure 1. The bioavailability and associated chemical reactions of selenium in soil-plant systems (The grey-blue parts on the left side presents, from top to bottom, the root soil, the soil solution and the soil solid phase; the blue arrow on the right side indicates the increase in bioavailability of selenium from bottom to top).Modified from Dinh, et al[15].
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图 4 有机酸对土壤硒生物有效性的影响示意图
Figure 4. The impact of organic acids on soil selenium bioavailability.
表 1 土壤硒生物有效性评价研究案例
Table 1 Cases of soil selenium bioavailability assessment
评估方法 土壤类型 地区 作物 影响硒生物有效性因素 参考文献 单一提取法 草甸黏壤土 英国 - 可溶性硒、交换性硒为主要的有效硒组分 [24] 黄褐色土 湖北省恩施市 马铃薯 硒酸盐比亚硒酸盐更能提高块茎硒的生物有效性，但膨大期叶面施用亚硒酸盐适合富硒马铃薯的生产 [43] 水田土，旱地土 湖北省恩施市 水稻 水稻植株的硒含量与有机结合态硒呈显著相关，有机质是影响水稻硒生物有效性的主要因素 [44] 黄土, 砂壤土 陕西省永寿县 玉米 土壤和叶面施加硒均能可靠有效地提高玉米籽粒中硒的含量 [45] 变性土，铁铝土 云南省滇池东岸 - 土壤中的总硒含量对生物有效性硒影响最大，其次是铁/铝氧化物，pH增加时铁/铝氧化物对硒的吸附降低 [46] 富硒土壤，风化石煤 湖北省恩施市渔塘坝 - 弱结合的腐植酸结合态硒在有机结合态硒中占主导地位，且结合越弱越容易转化成生物有效性硒，是生物有效性硒的潜在来源 [47] 泥炭土、壤土，泥炭/壤土混合土 挪威东南部 小麦 有机质含量较低的土壤，硒有效性随pH的增加而增加；有机质含量较高的泥炭土，硒有效性随pH的增加而降低 [48] 顺序提取法 水稻土，旱地土 陕西省紫阳县闹热村 水稻，玉米 旱地中铁锰氧化结合态硒占主导地位，有机结合态释放硒会提高硒的生物有效性 [25] 黄土 陕西省 小白菜 硒酸盐比亚硒酸盐处理的土壤有更高的生物有效性 [32] 黄土，壤土 西北农林科技大学试验田 小麦 亚硒酸盐处理，交换性硒浓度增加；硒酸盐处理，可溶性硒浓度增加；铁锰氧化结合态硒、有机结合态硒浓度均降低；硒生物有效性增加 [33] 大骨节病病区的天然土壤 西藏高原松潘县 青稞 硒的生物有效性与海拔高度呈负相关 [49] 栗钙土，黑土 内蒙古和黑龙江 小白菜 老化使可溶性硒和交换性硒随时间延长而含量降低，硒生物有效性降低 [50] DGT技术 天然富硒土壤 湖北省恩施市 水稻 DGT测定的硒主要来源于可溶性和可交换态硒，可溶性和交换性硒浓度与土壤pH呈显著正相关 [36] 天然富硒土壤 陕西省紫阳县 玉米 残余态硒和铁锰氧化物结合态硒占据优势，交换性硒和碳酸盐结合态硒占比<5%，生物有效性很低 [39] 农场表层土 西北农林科技大学农场 紫甘蓝，西兰花，芥菜，小麦 紫甘蓝和西兰花吸收土壤中最有效的可溶性硒的能力优于芥菜和小麦，DGT适用于表征硒酸盐处理的土壤硒生物有效性 [40] 栗钙土，黑土 内蒙古和黑龙江 小白菜 小白菜根中硒浓度与CDGT-Se呈极显著相关，硒酸盐处理的土壤老化速率低于亚硒酸盐处理的土壤，老化使硒生物有效性均降低 [51] 水培溶液 - 油菜，小麦 油菜对硒的积累速度大约是小麦的三倍 [52] 黄棕壤、砂姜黑土、褐土、海滨土、黑土和潮土 安徽、江苏、辽宁、天津、黑龙江、河北 小白菜 生物有效性：褐土>潮土, 黑土>海滨土, 砂姜黑土>黄棕壤, 土壤类型是影响有效硒的主要因素 [53] 
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