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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长期饮用高砷、高氟水会引发人体慢性中毒，对皮肤与神经系统造成损害，导致神经性中毒、皮肤病、贫血等多种疾病，严重者会导致癌症，威胁人体健康[1-4]。国际癌症研究机构(IARC)已将As列为一类致癌物质[5-6]。世界卫生组织(WHO)将饮用水中As与F离子允许上限分别规定为10μg/L和1.5mg/L，中国饮用水标准中也将两者浓度上限分别规定为10μg/L和1mg/L。因此，结合饮用水标准与地下水质量标准，通常将As浓度>10μg/L和F浓度>1mg/L作为高砷与高氟的界限[7]。As、F浓度过高的地下水广泛分布于孟加拉国、印度、美国等全球各地[5, 8-9]。孟加拉国与印度饮用水中As浓度最高超过2mg/L，美国肯塔基州部分地下水F浓度超过50mg/L[10-11]。在中国高砷与高氟地下水分布于大同盆地、河套平原、松嫩平原等多地[12-14]。据统计，河套盆地与大同盆地地下水中As浓度最高超过1mg/L，F离子浓度超过5mg/L，松嫩平原地下水As浓度最高也超过300μg/L[15-17]，这些地区地下水中As与F浓度都远超饮用水限值。地下水的As与F超标问题已成为影响地下水利用的重要因素，所以针对地下水中As与F的来源与演化引起了学者们的广泛关注和研究。
张怀胜等[18]对河北衡水高氟水研究表明，水中氟离子主要受萤石溶解与离子交换作用的影响，而天津武清高氟地下水中具有低钠高钙的水化学特征[19]。黄冠星等[20]研究表明珠江三角洲高砷地下水来源受到原生与人为灌溉的共同影响。地下水中氟离子主要来源于含氟原生沉积地层，并通过蒸发浓缩等水化学作用其浓度升高[21]。Guo等[22]和曹文庚等[23]发现河套平原地下水受到黄河改道的影响，高砷主要来源于有机物作用下铁氧化物的还原溶解作用。而王喜宽等[24]和赵锁志等[25]分析了河套地区地下水中高氟是气候因素、地质因素和人类活动共同影响导致。韩双宝等[26]认为黄河流域中As、F、碘等原生组分超标是部分地区地下水饮水安全的主要威胁，且在河南新乡地区零星分布着高砷地下水。通过前人研究可以看出，地下水中As、F等离子浓度升高是受到当地气象条件、水文地质条件与人为活动等多方面因素共同影响[27-29]。在很多地区，地下水会同时出现高砷与高氟并存的结果，但两者赋存机制之间的关系仍需进一步研究。
黄河下游典型灌区(河南)为河南重要的农业产地，该地区的农业灌溉重要水源之一为浅层地下水，同时地下水还用于当地养殖与村民家庭用水。前期已有研究发现，该地区浅层地下水整体水质较差，虽然随着地下水位的下降，浅层地下水逐渐发生淡化[30-31]，但是As、F等离子超标问题较为严重，如新乡市延津县氟水受害人口占全县总人口的33.25%，而在封丘县高砷村暴露人口中病人以皮肤色素脱失伴随色素沉着。这表明高砷、高氟地下水已经对当地用水安全和人体健康造成潜在风险[32-33]。由于黄河下游典型灌区(河南)同时受到山前冲积与黄河冲积双重影响，且该地区人类活动影响较多，地下水中As、F在该地区的分布及演化特征会受到多重环境的影响，As、F两种元素在该地区的富集机制仍无明确结论。
本文基于2010年与2020年对黄河下游典型灌区(河南)进行的两次地下水质调查，分析了2020年地下水中As、F的整体分布情况，通过两次水质数据分析工作区浅层地下水中As、F离子整体浓度与空间分布上的变化情况，揭示研究区内地下水中As、F离子在近十年间的演化特征，探究近十年间导致As、F变化过程的形成机理。研究成果拟为该地区后续的地下水合理利用提供科学依据。
1. 研究区概况
黄河下游典型灌区(河南)位于河南省东部，行政区包括新乡市、鹤壁市、安阳市与濮阳市。该地区西靠太行山，南边以黄河作为边界，北侧和东侧则分别与河北与鲁西平原相连。地区地势总体由西南向东北倾斜。黄河下游典型灌区(河南)为历史上黄河决口、改道最频繁的地区之一，地表仍可见河道变迁的历史遗迹，整体普遍分布为平地与洼地，黄河故道上有沙丘、沙地地貌分布。
研究区属暖温带半湿润、半干旱气候，多年平均气温介于13~15℃之间，降水量600~800mm，且多集中于夏季的七月份至九月份。研究区总的气候特征为冬季寒冷降雪偏少，春季干旱风沙较多，夏热雨水多且丰沛，秋季日照时间较长。研究区内河流以黄河干流及其支流沁河、天然文岩渠、金堤河、洛河、伊河、涧河、廛河、金水河为主。该地区地下水主要赋存于第四系多层交互的砂与粉土的孔隙含水层中。地下水系统在该地区可划分为山前倾斜平原含水层系统与黄河冲积平原含水层系统。
黄河下游典型灌区(河南)总体径流方向与地势变化基本一致，由西南向东北方向，由西部山前的补给源区向东部径流，由南部黄河补给源区向东北方向径流。该灌区(河南)自20世纪80年代以来，由于需水量快速增加，而补给量相对减少，工农业大量开采利用地下水，使得人工开采地下水成为主要的排泄方式，向下游区的径流排泄位居其次。
工作区2010年调查数据表明，高砷地下水主要分布在新乡北部与中西部大部分地区，濮阳市也偶有高砷地下水出现。As平均浓度为9.9μg/L，As最大浓度地下水位置位于新乡市延津县胙城乡，浓度达到190μg/L。高氟地下水主要分布在黄河沿线和濮阳市，最大浓度为4.94mg/L，位于濮阳市濮阳县八公桥镇。
2. 实验部分
在2010年项目组对研究区内地下水进行采样，共计327组，并于2020年10~11月在原水井位置327组上进行复采并添加3组共计330组。后续为了对比演化特征和形成机制，只选取两期对应的327组样品进行对比分析。本次研究中所有样品均来自于机民井与压水井，井深均不超过100米，从含水层划分上均定义为浅层含水层地下水。
采集水样均通过0.45μm的滤膜在现场进行过滤，采样时现场测定水温、pH值、氧化还原电位值(Eh)、电导率、溶解氧(DO)等。对于微量元素(Fe、Mn、As、PO43-、Al、Zn)分析的水样通过50%的硝酸酸化进行保护。样品在野外取样后置于0~4℃保温箱中保存，转移到室内后置于冰柜冷藏保存。
2010年和2020年两期水质数据分别由中国地质科学院水文地质环境地质研究所与河南自然环境监测院进行测试。实验结果中阳离子(K+、Ca2+、Na+、Mg2+)采用电感耦合等离子体发射光谱仪(iCAP6300型，美国ThermoFisher公司)进行测定；锰元素采用电感耦合等离子体发射光谱仪(Optima 8000型，美国PerkinElmer公司)测定；阴离子(Cl-、I-)采用离子色谱仪(CIC-D160型，美国ThermoFisher公司)测定；As元素采用原子荧光光谱仪(AFS-3100型，北京海光仪器有限公司)测定；阴离子(F-、NO3-、SO42-)采用离子色谱仪(ICS-1500型，美国Dionex公司)测定；铵根采用紫外分光光度计(UV-2550型，日本岛津公司)测定；碱度采用酸碱滴定法测定。
在地下水样品测试中，采用加5%的重复样品进行质量控制，所有重复样品的误差小于5%。
3. 结果与讨论
3.1 2010—2020年研究区地下水化学特征
通过2020年主要阴阳离子类型在数量的分布看出，研究区阳离子水化学类型是Na++Ca2++Mg2+、Na++Mg2+、Na+等以钠离子为主的类型(图 1a)，只有在新乡北部与安阳交界的冲洪积平原洼地处，阳离子以Ca2++Mg2+为主。而研究区内阴离子水化学类型普遍以HCO3-、HCO3-+Cl-等类型为主，重碳酸盐都是主要阴离子(图 1b)。
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图 1 2020年研究区水化学阴阳离子类型分布统计a—阳离子类型；b—阴离子类型。Figure 1. Distribution statistics of water chemical anion and anion types in the study area in 2020 (a—cationic type; b—anion type)研究区主要阴阳离子浓度(K+、Ca2+、Na+、Mg2+、HCO3-、Cl-、SO42-)分布列于表 1。研究区内浅层地下水溶解性总固体(TDS)平均值均超过1g/L，说明典型灌区内浅层地下水属于微咸水。根据近十年间主要阴阳离子浓度的变化情况(表 1)，除了K+平均浓度略有增加，其余离子与TDS浓度最大值与平均值都出现降低，这表明研究区内浅层地下水在近十年有所淡化。
表 1 2010年和2020年研究区主要离子浓度分布Table 1. Main ions concentration distribution of the study area in 2010 and 2020离子类型 2010年测试值 2020年测试值 最大值(mg/L) 最小值(mg/L) 平均值(mg/L) 最大值(mg/L) 最小值(mg/L) 平均值(mg/L) K+ 225 0.02 4.11 226 0.380 5.89 Ca2+ 680 15.1 95.7 470 2.40 95.1 Na+ 1.97×103 16.8 203 894 17.6 188 Mg2+ 834 15.9 76.7 417 5.95 72.6 HCO3- 1.48×103 209 626 1.21×103 252 617 Cl- 2.49×103 10.1 195 1.38×103 8.51 165 SO42- 4.43×103 5.82 200 1.58×103 5.76 182 TDS 9.37×103 326 1.10×103 4.73×103 374 1.04×103 3.2 2010—2020年地下水砷和氟分布特征
为了展示As与F元素在研究区内空间的分布特征及两种元素在2010—2020期间整体浓度与空间变化，依据地下水质量标准及饮用水标准对两种元素浓度的划分，利用Arcgis将地下水中As与F元素按照不同浓度标准(As：≤10μg/L，10~50μg/L，>50μg/L；F：≤1mg/L，1~2mg/L，>2mg/L)投影至研究区范围内。
2020年研究区As浓度分布介于0~128μg/L之间，平均浓度为10.5μg/L。根据As在研究区内的分布(图 2a)可以看出，研究区内地下水中高砷点(浓度大于10μg/L)的分布呈现明显的空间差异性。As浓度高于10μg/L的地下水普遍分布于新乡地区的延津县、原阳县、封丘县，新乡与安阳北部滑县交界处地下水As浓度超过50μg/L，个别高砷点位于濮阳市北部濮阳县、范县等地。取样结果中最大As浓度点位于新乡市延津县胙城乡，该点位与2010年最高值点位一致，这表明该处地下水长期稳定地保持高砷状态。在新乡大部分中部平原地区，黄河的多次改道在该地区形成了砂与土互层的沉积环境。新乡北部与滑县交界处于冲洪积洼地地带，地下水在此区域径流不畅。该地区为山前冲洪积扇裙的前缘部位，砂层的厚度逐渐变薄，黏土的厚度开始增加，总体上同样呈现“下粗上细”的砂、泥互层特征[34]。研究表明在砂土互层与弱径流条件下，地下水会保持强还原环境，随着土砂比越高，地下水还原性越强，因此有利于高砷地下水的形成[35]。
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图 2 2020年(a)砷与(b)氟元素空间分布图Figure 2. Spatial distribution of (a) arsenic and (b) fluorine in 2020而F元素在研究区的空间分布(图 2b)表明高氟地下水(浓度大于1mg/L)主要分布于新乡市东南部的封丘县与长垣县的黄河沿线地区，以及濮阳市的濮阳县、范县和台前县等黄河冲积平原。研究区整体F离子浓度介于0.06~6mg/L，平均浓度为0.88mg/L。F离子最高浓度点位于新乡市长垣县芦岗镇，地处黄河沿线附近。
Gibbs[36]根据全球不同类型地表水中TDS与不同离子之间毫克当量比的分布，判断地表水的来源。而学者们发现同样可利用Gibbs图识别地下水化学的主要来源[37-38]。通过2020年不同浓度As与F的数据点在Gibbs图中的分布(图 3)可以明显看出，黄河典型灌区(河南)农业区地下水主要受到岩石风化作用与蒸发浓缩作用的共同影响。高砷与高氟地下水的分布更靠近岩石风化区，表明该地区中地下水中的高砷(图 3a)与高氟(图 3b)是受到原生地层中矿物风化溶解作用所导致。已有研究表明黄土中具有大量云母、角闪石等含氟矿物，因此黄河影响区内黄土等含氟土壤是高氟地下水的直接来源[7, 21]。在灌溉、降雨等作用的影响下，土壤矿物中F通过淋滤、溶解等作用进入地下水中。
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图 3 2020年Gibbs图中不同浓度(a)砷与(b)氟分布Figure 3. Distribution of (a) arsenic and (b) fluorine in different concentrations in Gibbs diagram in 20203.3 2010—2020年砷和氟浓度变化特征
3.3.1 研究区砷浓度变化特征
通过As、F元素在研究区近十年浓度的变化，可以反映出该地区地下水环境在此阶段的演化。为了消除测试中检出限对区域内As、F元素演化的影响，将As、F元素分别在0±1μg/L与0±0.05mg/L之间浓度变化视为未发生改变。对As元素浓度两期的数据进行对比，并通过研究区各点浓度在近十年的改变情况(图 4a)可以看出，As浓度升高点与2020年高砷点具有良好的对应性，除在新乡冲积平原西南至东北方向高砷区范围浅层地下水中As浓度有所减少，个别点As浓度减少达到50μg/L以上，其余高砷地下水中在近十年都出现不同程度升高。而As浓度减少的范围则集中在平原的低砷区中，安阳市与濮阳市低砷区整体浓度以保持稳定和略有降低为主，新乡市低砷区有所减小。以As浓度大于10μg/L作为分界线，发现研究区内As超标率从23.9%升高至26.1%，说明研究区高砷分布范围有所扩大。近十年水样点中As浓度增加的占31.8%，As浓度减少的水样占总数36.7%。这表明在黄河下游典型灌区(河南)地下水中As元素浓度受到不同环境因素影响呈现两种变化趋势，高砷区As的浓度除新乡北部地区外逐渐增加，低砷区As的浓度变化不大或逐渐减少。
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图 4 2010—2020年(a)砷与(b)氟浓度变化图变化值大于零代表浓度增加，变化值小于零代表浓度降低。Figure 4. Arsenic and fluorine concentration variation in 2010—2020 (a—arsenic, b—fluorine; A change value greater than zero represents an increase in concentration, and a change value less than zero represents a decrease)3.3.2 研究区氟浓度变化特征
近十年间氟元素在研究区内浓度整体降低(图 4b)，大多数水样浓度降低幅度在0.05~1mg/L之间，这表明研究区地下水环境不利于氟元素的富集。但是在新乡南部黄河沿线附近与濮阳市的高氟区中，浅层地下水中的F元素浓度得到进一步增加，F离子浓度范围从2010年的0.13~4.94mg/L变化至2020年的0~6mg/L，这说明高氟区的地下水环境对F元素的进一步富集起到促进作用。而2010—2020年期间高氟水占比从25.69%变化至26.06%，地下水F浓度减少的占总数60.2%，F浓度增加的占总数32.1%。高氟地下水比例变化不大，整个地区F离子浓度有下降的趋势。
4. 2010—2020年砷和氟演化过程机制
4.1 近十年地下水中砷演化机制
影响As离子浓度变化的因素较多，氧化还原环境变化、水文地球化学作用等因素均会导致地下水中As元素向不同方向发生改变[39]。利用地下水中不同类型离子比可以反映地下水环境的变化情况。
4.1.1 氧化还原条件影响作用
为了进一步探究研究区内As浓度不同变化方向的作用机理，通过As与不同离子比之间关系和2010—2020As与其他离子成分的变化值之间的关系来判断As演化机制。在还原条件下，SO42-还原成S2-，HCO3-在微生物作用下逐渐增加，HCO3-/SO42-比值升高，比值越大，地下水还原性越强[35]。因此(HCO3-+CO32-)/SO42-可作为氧化还原条件的敏感因子来判断地下水还原性的强弱。结果表明2010年与2020年两期数据中As与(HCO3-+CO32-)/SO42-比值呈现正相关性(图 5a)。随着地下水中As元素浓度增加，(HCO3-+CO32-)/SO42-比值变大，地下水还原性增加，氧化性逐渐减弱。
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图 5 2010—2020年砷元素变化与各离子比变化之间关系Figure 5. Relationship between the change of arsenic and the change of ion ratios in 2010—2020利用2020年与2010年地下水As浓度之间差值与环境敏感元素近十年间的差值进行对比，可以判断不同因素对As近十年间发生演化的影响作用。氨氮的变化受地下水中氧化还原条件的影响较大，不同氧化还原条件造成各类型氮素之间相互转化，因此氨氮也可作为氧化还原环境的敏感指标。根据近十年间As-NH4+-N变化量之间关系(图 5b)可以看出，样品主要分布在第一、第三象限。在As浓度减少的过程中，氨氮同样发生降低且降低量有所增加(第三象限)。在As浓度发生恶化的区域，氨氮浓度相应增加且增加量变大(第一象限)。可以看出在地下水As改善与恶化的两种环境中，氨氮浓度与其均具有良好的相关关系。在厌氧环境中，在微生物的作用下，氮素之间会发生反硝化作用，氨氮浓度逐渐增加；而在好氧环境中，地下水中的氨氮通过硝化作用发生减少[40]。这表明在地下水As浓度发生明显变化的过程中，氧化还原条件的改变是其中的重要因素。而在As-Mn两者变化量之间关系图(图 5c)可以看出，在As浓度变化明显的地下水中，Mn浓度同样随之变化。随着As浓度进一步增加，其所在地下水中的锰浓度也出现增加(第一象限)，而Mn浓度也随着地下水As浓度减少而降低(第三象限)。两者虽然相关性相对不高，但两者变化量之间相似的变化趋势表明锰氧化物等氧化物的吸附或释放会导致地下水中As的改善或恶化[41]。近十年间黄河下游河南段范围内地下水由于受到不同因素影响使得水位发生波动，封丘等部分地区地下水受到农业灌溉的影响造成水位呈现下降[26]。水位的下降会导致地下水中的含氧量上升，进而使得地下水中As在氧化环境中被吸附于固相中而使其浓度降低[42]。另外，部分水源置换区地下水的开采量减少引起水位回升[26]，使得地下水环境还原性增加，会促进As释放进入水体。
4.1.2 水文地球化学影响作用
Na+/Ca2+可以指示地下水中阳离子的主要类型，从图 5d中可以看出As在不同水化学类型地下水中同样存在差异。Na+/Ca2+与As之间存在负相关关系。随着地下水中As浓度的增加，Na+/Ca2+比值快速降低。表明高砷地下水中的水文地球化学作用导致Na+的相对含量减少，Ca2+的相对含量增加。Na+/Cl-比值可以指示水盐机制，当该比值接近于1∶1时，表明地下水钠盐主要源于岩盐溶解[43]。在As-Na+/Cl-图(图 5e)中可以看出，地下水中大部分点位于y=1线上，这说明地下水中还存在硅酸盐等矿物溶解作用。而随着地下水中As浓度增加，Na+/Cl-比值也在迅速降低，这说明地下水中Na+会通过水岩作用浓度发生降低。
为了进一步明确地下水中影响高砷变化的水文地球化学作用，利用As与[(Ca2++Mg2+)-(HCO3-+ SO42-)]/(Na+-Cl-)比值之间的相关关系来判断阳离子交换作用强弱。分析结果(图 5f)表明随着地下水中As浓度增加，[(Ca2++Mg2+)-(HCO3-+ SO42-)]/(Na+-Cl-)比值逐渐趋近于-1，这表明地下水中Na会与含水层中Ca发生阳离子交换作用，使得水中Na浓度降低，Ca浓度增加。研究表明在高砷地下水中径流不畅，阳离子交换作用会发生充分反应[44]。
4.2 2010—2020年地下水中氟演化机制
4.2.1 阳离子类型影响作用
氟离子变化值与研究区内不同主要指标变化情况之间的相关性结果表明，F离子浓度变化整体与井深(R2=-0.102)和K+(R2=-0.130)、Mn(R2=-0.284)、NO3-(R2=-0.235)、As(R2=-0.145)、Ca2+(R2=-0.307)等六种指标变化之间存在弱负相关关系，F离子的变化与Ca2+、Mn、NO3-之间的负相关程度较强，表明这几种离子表现出地下水环境对F离子变化的影响较大。而F与SO42-(R2=0.103)、HCO3-(R2=0.118)、Na+(R2=0.169)之间存在弱正相关关系。F离子变化和各指标变化之间的关系说明，F离子浓度的变化受到地下水主要阴阳离子浓度、氮素变化和含水层介质的影响。
根据2010年与2020年水质中F与Na+/Ca2+之间关系(图 6a)看出，Na+/Ca2+与F之间呈现正相关关系。在F浓度较高的地区，Na+/Ca2+比值也较高，表明高氟地下水地区地下水径流条件较好，阳离子交换作用较弱。结合3.2节分析表明了高砷点分布于黄河沿线，由于阳离子含量受到黄河水影响，使得F离子浓度得到增加[45]。而进一步判断F在2010—2020之间变化所受影响，则通过2020年与2010年地下水F浓度之间差值与Ca差值之间关系(图 6b)能够发现两者差值之间具有良好的负相关关系。随着地下水中F离子逐渐升高，所处地下水环境中Ca浓度随之减少(第四象限)，而F浓度改善的地下水中Ca浓度出现增加(第二象限)。两者变化值之间良好的相关关系，表明地下水中钙离子浓度是影响F离子变化的重要因素。
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图 6 2010年和2020年氟离子变化与不同离子比变化之间关系Figure 6. Relationship between the change of fluorine ion and the change of different ion ratios in 2010 and 2020萤石(CaF2)作为一种同时含有钙与氟元素的矿物，在天然条件下的水体中会同时存在着以下两种反应[46]:
$ {\rm{C}}{{\rm{a}}^{2 + }} + {\rm{HCO}}_3^ - + {\rm{O}}{{\rm{H}}^ - } \leftrightarrow {\rm{CaC}}{{\rm{O}}_3} + {{\rm{H}}_2}{\rm{O}} $
(1) $ {\rm{C}}{{\rm{a}}^{2 + }} + 2{{\rm{F}}^ - } \leftrightarrow {\rm{Ca}}{{\rm{F}}_2} $
(2) 通过上述反应式可以看出，水文地球化学作用显著影响F离子的分布。低钙的碱性重碳酸盐型水中有利于含氟矿物产生溶解作用。随着地下水中pH值升高，重碳酸根离子浓度增加，反应式(1)向生成碳酸钙的方向进行移动，使得Ca2+浓度降低，这就会引起反应式(2)中的反应向萤石溶解的方向进行移动，使得F离子浓度得到增加[47-48]。所以，研究区中高氟地下水同样主要赋存于低钙的环境中[45, 49]。F离子主要来源于含氟矿物，但在黄河冲积平原内沉积物中钙质矿物较多，受到地下水中钙离子浓度较高的影响，使得F离子在萤石溶解平衡的反应中其浓度显著减小，且随着时间增加，钙离子浓度逐渐增加，F离子浓度减少。而在黄河沿线附近，地下水阳离子受到黄河地表水的影响，以钠离子为主，造成地下水F离子浓度显著增加。
4.2.2 氟与砷之间演化关系
根据研究区内As-F之间的关系可以看出(图 6c)，两者分布具有负相关关系，高砷水环境不利于F离子的富集，高氟水环境中也不利于As的赋存。研究表明河套平原中干旱-半干旱地区的气候等因素使得As、F两者之间具有正相关关系[50]，说明在本研究区中As与F富集机制与其有所不同。结合相关性关系图和As、F分布演化机制，在径流条件较差的环境中，As在锰氧化物等固相上通过还原溶解释放进入地下水中，但地下水中阳离子交换作用较强，地下水中钙离子的升高使得F离子无法存在于其中，因此造成在As浓度增加的地区F离子浓度出现降低。同样，高氟地区普遍分布于黄河沿线，受到黄河补给影响作用较大，径流条件较好，此时As容易被吸附于固相上，造成在水中浓度较低。而As-F近十年间变化之间相关关系中(图 6d)，在F浓度增加地区中地下水As浓度降低(第四象限)。由上述关系可知，F增加地区Ca2+减少，表明该地区中地下水径流较好，该环境中As逐渐吸附于固相，在液相中浓度降低。而在F浓度减少的地区，As浓度变化无明显规律，表明在F减少地区As与F之间演化关系还受其他因素影响。
5. 结论
本文在黄河下游灌区(河南)取地下水样品327组，发现2020年研究区浅层地下水中钠离子与重碳酸根离子为主要阴阳离子。浅层地下水平均TDS超过1g/L，属于微咸水。高砷区主要分布于太行山山前洼地与黄河冲积平原内，而高氟区主要分布于新乡南部与濮阳等黄河沿线附近。通过分析研究区2010—2020年As、F离子浓度的变化可以看出，As与F增加区与高砷、高氟区具有良好的对应关系。区域内As浓度变化出现两种趋势，近十年间As浓度增加数量占总数31.8%，As浓度减少数量占36.7%。在As浓度增加区(增加超过1μg/L)，除在新乡冲积平原西南至东北方向高砷区浅层地下水中As浓度减少，其余高砷地下水中在近十年间都出现升高。F离子升高区(增加超过0.05mg/L)则主要分布在新乡与濮阳沿黄河一带，研究区中F离子浓度减少数量占总数60.2%，F离子浓度增加数量占32.1%，整体出现向好趋势。
高砷水主要赋存在还原性较强的环境中。同时高砷地下水环境由于径流不畅，使得水中Na+与含水层矿物中Ca2+之间发生较强的阳离子交换作用，高砷水中Na+浓度降低，Ca2+浓度升高。而2010—2020年As浓度的变化受到氧化还原条件的影响较大，氨氮浓度增加的地区中还原性增强，可溶性Mn浓度变高，同时水中As浓度在近十年间出现增长，表明锰氧化物等在该条件下释放As，而在氨氮降低地区氧化性增加，As与Mn浓度都出现减少，表明锰氧化物在该条件下会吸附As。F离子分布与Ca2+呈反比，高氟地区地下水中Ca2+浓度明显低于其余地区。而近十年间氟离子变化与Ca2+的变化同样呈明显的反向关系。在地下水中Ca2+升高地区，F离子浓度受到萤石矿物溶解平衡影响其浓度降低，而在黄河沿线地下水钠离子浓度升高地区，F离子浓度升高。地下水中As与F受到阳离子类型影响，使得两者之间分布具有负相关性。在地下水中氟增加地区，钙离子浓度普遍降低，表明此时径流条件较好，阳离子交换作用减弱，造成氟增加的演化过程中As浓度出现降低。本研究阐明了黄河下游灌区(河南)浅层地下水中As和F在2020年的分布特征，揭示了2010—2020近十年As和F在研究区中的演化情况与变化机制，该成果将为研究区中浅层地下水的合理开发利用和健康风险评价提供依据。
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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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