这个毒性阈值ps阈值是什么意思思

基于根微形态测定土壤Zn对大麦的毒性阈值及其预测模型
何俊, 田昕竹, 王学东, 刘彬, 李宁, 郑涵, 孟楠, 陈世宝. 基于根微形态测定土壤Zn对大麦的毒性阈值及其预测模型[J]. 中国农业科学, ): HE Jun, TIAN XinZhu, WANG XueDong, LIU Bin, LI Ning, ZHENG Han, MENG Nan, CHEN ShiBao. Zn-Toxicity Thresholds as Determined by Micro Morphological Endpoints of Barley Roots in Polluted Soils and Its Prediction Models[J]. Scientia Acricultura Sinica, ): &&
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基于根微形态测定土壤Zn对大麦的毒性阈值及其预测模型
田昕竹1,3,
1首都师范大学资源环境与旅游学院,北京 100048
2中国农业科学院农业资源与农业区划研究所/农业部植物营养与肥料重点实验室,北京 100081
3北京市环境影响评价评估中心,北京 100161
联系方式:何俊,E-mail:。通信作者:陈世宝,E-mail:
基金资助:国家自然科学基金项目(77131)、国家科技支撑计划课题(2015BAD05B03)、国家重点研发计划课题(2016YFD0800707)
目的 随着对污染土壤管理要求的不断提高,受污染土壤生态风险评价的内容也在不断深入。目前,污染土壤风险评价毒性测试逐渐由单物种测试为基础的生态风险评价发展为基于物种敏感性分布的区域种群毒性测试;毒性中除了要包含测试物种的整个生命周期,还需要增加不同敏感的测试终点。基于不同测试终点的毒理学数据对于评价污染土壤中Zn的环境风险具有重要意义。根系生态是基于生态效应法推导土壤中重金属生态风险阈值的重要组成部分,论文中以大麦根尖数、总根长、根表面积和根平均直径为评价终点,研究污染土壤中Zn对大麦根微形态的毒性阈值及其与土壤性质间的量化关系,以期为中国Zn污染土壤的环境风险评价提供科学依据。方法 采集了8种不同性质的农田土壤,外源添加不同浓度Zn后进行盆栽试验,利用STD1600 Epson根系扫描仪测定不同根微形态指标,结合Log-logistic剂量-效应曲线测定基于不同根微形态为终点的毒性阈值(EC10,EC50),建立基于土壤性质的Zn毒性预测模型。结果 土壤Zn污染对不同根微形态指标的毒性阈值存在较大差异,基于大麦根尖数、总根长、根表面积和根平均直径的有机碳(EC10)和阳离子交换量EC50均值分别为228、295、335、261 mg&#x000b7;kg-1及702、779、837、739 mg&#x000b7;kg-1,以根尖数测定的EC值最低,根表面积的EC值最高,即根尖数指标对土壤Zn毒性最敏感。不同土壤中,EC10值的变异系数(34.1%)大于EC50(21.6%),而4种不同测试指标中,基于大麦根表面积测定的变异系数最大,EC10和EC50的变异系数分别达到43.4%和23.2%。土壤pH、有机碳(OC)、阳离子交换量(CEC)与Zn的毒性阈值EC x( x=10,50)呈正相关关系,其中pH的相关系数达到极显著水平( P<0.01)。结论 不同的根微形态指标中,土壤Zn污染对大麦根尖的毒性最敏感;基于pH、CEC、OC的预测模型可以很好地预测土壤中Zn的大麦毒性阈值。
Doi:10.3864/j.issn.17.07.009
Zn-Toxicity Thresholds as Determined by Micro Morphological Endpoints of Barley Roots in Polluted Soils and Its Prediction Models
TIAN XinZhu1,3,
WANG XueDong1,
ZHENG Han2,
MENG Nan2,
CHEN ShiBao2
1College of Resource Environment and Tourism, Capital Normal University, Beijing 100048
2Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Beijing 100081
3Beijing Environmental Impact Assessment Center, Beijing 100161
【Objective】With the continuous requirements for the management of contaminated soil, intensive studies on the ecological risk assessment of contaminated soil are increasingly important. At present, the toxicity test based on species sensitivity distribution for ecological risk assessment of regional contaminated soil has been becoming more and more important compared with the toxicity test based on single species. The toxicity assay should include not only the test for throughout the life cycle, but also the sensitivity of different test endpoints. Toxicity thresholds of Zn determined with different test endpoints are important for evaluation of the environmental risk of Zn in polluted soils. Root ecology plays an important role in the ecological risk assessments and the derivation of toxicity thresholds of heavy metals in polluted soils. The Zn toxicity thresholds (EC x, x=10, 50) of barley as determined by total root length, number of root tips, root surface area and the average diameter of barley root and the quantitative relationships between the EC x and soil properties were studied with the aim to provide basic data for environmental risk evaluation of Zn polluted soils. 【Method】 Eight kinds of field soils with various properties were collected around China, Zn (ZnCl2) was applied and the treated soils were used in a pot experiment after 4 weeks of incubation. Different micro morphological endpoints of barley roots were measured with root scanner (STD1600 Epson), the Zn toxicity thresholds (EC x, x=10, 50) of barley were determined based on the dose-responsive curve with Log-logistic model, the prediction models of Zn toxicity thresholds were developed based on the total Zn concentrations and soil properties (e.g. pH, CEC and org-C etc).【Result】The results indicated that toxicity thresholds of Zn varied significantly among the different micro morphological endpoints of barley roots. The average EC10 and EC50 determined with total root length, number of root tips, root surface area and the average diameter of the root were 228, 295, 335, 261 mg&#x000b7;kg-1 and 702, 779, 837, 739 mg&#x000b7;kg-1, respectively. The smallest EC x were observed with the test of number of root tips while the maximum EC xwere observed with endpoint of root surface area, which indicated that the growth of root tips is the most sensitive endpoint among the root micro morphological endpoints of barley when it is stressed by Zn pollution in soil. Meanwhile, the variation coefficient of EC10 (43.4%) was generally higher than that of EC50 (21.6%). A positive correlation was found between EC x ( x=10, 50) and the background Zn contents, soil properties (pH, OC contents), and correlation coefficient of pH between EC x reached was very significant ( P<0.01).【Conclusion】It was found that the growth of root tips is more sensitive than other root micro morphological endpoints when stressed by Zn pollution in soil. The toxicity thresholds of Zn to plant can be predicted very well based on soil pH, OC, and soil Zn background concentration.
toxicity threshold;
root micro morphology;
predict models
0 引言【研究意义】Zn作为一种微量元素在动植物的生长过程中至关重要, 而过量的Zn又会对动植物和人体健康造成一定的威胁与损害[]。近年来中国农田土壤锌(Zn)污染正以不同尺度的趋势快速蔓延[, ], 资料显示, 中国Zn污染土壤超标率达0.9%。虽然中国最新颁布的食品安全标准中删除了Zn的限量标准值[], 但由Zn污染产生的生态环境风险已引起广泛关注。目前, 在环境风险评价中, 对污染物评价终点的选取具有较大的偶然性, 从而增加了污染物风险评价结果的不确定性[], 因此, 不同测试终点的毒理学评价对于Zn污染土壤的环境风险评价具有重要意义。【前人研究进展】近年来, 随着中国土壤重金属污染形势的发展, 针对重金属污染土壤的生态风险评价成为新的研究热点。相比而言, 国外重金属污染土壤的风险评价研究较早。20世纪90年代开始, 美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究, 制定和颁布了许多行业标准、规范和技术框架[, ], 而国内的研究起步相对较晚, 在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[, , ]。目前, 国内有部分学者针对土壤重金属的风险评价进行了研究, 并取得一些进展[, , , ]。总体而言, 目前国内针对重金属污染土壤的生态风险评价主要集中在利用不同指数法对污染土壤进行的污染等级划分、污染来源调查等[, ], 大部分情况下没有能够与土壤利用相结合, 特别是在农田土壤的评价中, 忽略了土壤和农产品质量之间的联系; 而基于不同抑制率的毒理学阈值研究, 凸显了土壤-作物系统根际环境的重要性。本文采用的不同类型土壤-大麦系统方法较常用的溶液培养法, 其与作物实际生长条件更为接近, 对重金属污染土壤进行有效评价和土壤环境质量标准修订更具参考价值。根细胞是重金属进入植物体进行吸收、转运的第一道屏障[], 从植物地上部生物量及植物体重金属吸收测定评价而言, 重金属胁迫对植物根系发育的毒性研究对于探明重金属污染土壤的生态系统退化作用、机理和过程及地下生态风险有重要意义[]。【本研究切入点】本文从污染土壤中Zn对植物根系发育的不同微形态指标出发, 利用最新的环境风险评价方法, 测定Zn污染胁迫对植物根系发育的不同毒性阈值, 量化Zn毒性阈值与土壤性质间的关系, 以期为Zn污染土壤的风险评价提供依据。【拟解决的关键问题】通过对不同植物根系发育的微形态指标测试, 获得Zn污染对植物根系发育的敏感性测定指标, 基于不同性质土壤中大麦Zn毒性的阈值, 建立基于Zn对大麦根系毒性阈值的预测模型, 为中国Zn污染土壤的风险评价提供科学依据。1 材料与方法1.1 供试土壤和大麦根据土壤地带性分布特征, 采集了8个不同地区的典型农田表层(0&#x02014; 20 cm)土壤。土壤性质测试[]结果见, 土壤样品在室内风干后去除杂物, 并过2 mm的尼龙筛备用。供试大麦(Hordeum vulgare L.)购自中国农业科学院, 品种为HS41-1。表1Table 1表1(Table 1)
表1 供试土壤的基本理化性质
Table 1 Basic physic-chemical properties of the tested soils采集地点Soil site经纬度Longitude, LatitudepH (H2O1:2.5)阳离子交换量Cation exchange capacity (cmol&#x000b7; kg-1)有机碳Organic carbon(OC) (%)黏粒含量Clay content(< 2 &#x000b5; m) (%)Zn背景含量Background Zn(mg&#x000b7; kg-1)海口(砖红壤) Haikou (Latosol)19&#x000b0; 55&#x02032; N, 111&#x000b0; 29&#x02032; E4.938.751.5166.157.4祁阳(红壤) Qiyang (Red Soil)26&#x000b0; 45&#x02032; N, 111&#x000b0; 52&#x02032; E5.317.470.8746.175.6嘉兴(水稻土) Jiaxing (Paddy soil)30&#x000b0; 77&#x02032; N, 120&#x000b0; 76&#x02032; E6.7219.331.4241.290.6杭州(水稻土) Hangzhou (Paddy soil)30&#x000b0; 26&#x02032; N, 120&#x000b0; 25&#x02032; E6.8012.822.4638.9119.3广州(红壤) Guangzhou (Red soil)23&#x000b0; 10&#x02032; N, 113&#x000b0; 18&#x02032; E7.278.301.4725.333.6公主岭(黑土) Gongzhuling (Black soil)42&#x000b0; 40&#x02032; N, 124&#x000b0; 88&#x02032; E7.8228.802.1744.662.8石家庄(潮土) Shijiazhuang (Fluvo-aquic soil)38&#x000b0; 03&#x02032; N, 114&#x000b0; 26&#x02032; E8.1911.711.0121.453.8廊坊(潮土) Langfang (Fluvo-aquic soil)39&#x000b0; 31&#x02032; N, 116&#x000b0; 44&#x02032; E8.846.360.6010.133.8
表1 供试土壤的基本理化性质
Table 1 Basic physic-chemical properties of the tested soils1.2 试验方法1.2.1 不同浓度外源Zn污染土壤制备 根据剂量-效应预试验结果, 以土壤中Zn对植物毒性抑制率达到90%为依据, 不同土壤添加不同的Zn浓度。不同pH土壤添加方法如下:Zn以ZnCl2溶液的形式添加, pH< 5.0时, 添加剂量为0、50、100、200、400、600、800、1 000 mg&#x000b7; kg-1; pH为5.0&#x0时为0、100、200、400、600、800、1 200、1 600 mg&#x000b7; kg-1; pH> 7.0时, 添加剂量为0、200、400、600、800、200、1 600、2 400 mg&#x000b7; kg-1。根据重金属在不同性质土壤中平衡反应的时间[], 本试验中外源Zn平衡28 d后进行盆栽试验; 试验在人工气候箱中进行培养, 控制光照条件为12 000 lx, 温度为(25&#x000b1; 2)℃。试验设置3组重复, 每盆装土300 g, 栽培时间为21 d。1.2.2 大麦根系指标测定方法 将大麦根部清洗干净并保持其完整性, 然后利用STD1600 Epson数字化扫描仪进行图像扫描, 利用WinRHIZO软件对扫描图像进行分析, 获得大麦根的总表面积、平均直径、根尖数及总根长等数据。1.3 数据处理常用的剂量-效应曲线有Log-normal、Weibull、Gamma等, 其中Log-logistic函数因其拟合参数均与实际生物效应有关而被广泛采用[, ], 本研究采用Log-logistic剂量-效应函数模型进行阈值的计算:y=$\frac{y_0}{1+e{(b(x-M))}}$ (1)式中, y代表评价终点(如根面积、根总长等)相对于对照的百分比(%); x为log10(Zn的添加浓度); y0为对照的反应率(%); M为log10(EC50/EC10), 其中, EC50/EC10为与对照相比各评价终点受到50%与10%抑制时土壤中Zn的含量。1.4 统计分析数据采用Excel 2010、SPSS 19.0、Origin 9.0等软件进行分析。2 结果2.1 基于大麦总根长测试终点的Zn毒性剂量效应曲线不同污染土壤中, 基于Zn污染对大麦根尖数、总根长、根表面积和根平均直径的测定值, 利用Log-logistic函数拟合出Zn对不同大麦根微形态的剂量-效应曲线, 并在此基础上经过计算获得基于不同测试终点的ECx(x=10, 50)值。从测定数据结果看出, 不同根微形态测试指标中, 根尖数指标最为敏感。在植物根系发育中, 相对于总根长、根表面积和根平均直径指标而言, 根尖生长时对外部环境的胁迫更为敏感[]。为基于大麦根根尖数的Zn对大麦毒性的剂量-效应关系曲线, 大麦根总长、根表面积和根平均直径的剂量-效应曲线没有列出。由可看出, Zn对大麦根尖发育的毒性随着土壤中Zn浓度的升高而增加, 表现为相对根尖数的降低, 而不同性质土壤中, 相同浓度Zn对大麦根尖发育产生的毒性效应有显著差异。总体而言, 在产生相同毒性的条件下, 土壤pH及有机碳含量较低的土壤的剂量-效应拟合曲线越靠左, 也即土壤中Zn的阈值越小, 这说明土壤中Zn的毒性越高。在有机质含量较高的2种土壤(公主岭黑土与杭州水稻土)中, 在Zn低浓度(< 200 mg&#x000b7; kg-1)条件下, 产生了低剂量刺激效应, 最大刺激效应(相对根尖数%)达到112%。图1Fig.1 图1 土壤中Zn对大麦根尖毒性的剂量-效应关系曲线Fig.1 Dose-responsive curve of Zn to barley total root tips in different soils2.2 基于不同测试指标的ECx值及其比较 为不同性质土壤中Zn对大麦根尖数毒性的阈值及其95%置信区间。由可知, 不同性质土壤测定的Zn对大麦根尖数的毒性阈值差异较大。不同性质土壤中, EC10与EC50范围分别为106&#x0 mg&#x000b7; kg-1, 469&#x0 mg&#x000b7; kg-1, 最大和最小分别相差2.64倍和1.03倍, 最小EC10的土壤为祁阳的红壤, 而最大值为碱性的潮土(河北廊坊); EC50的情况与EC10的类似。基于大麦根系的根总长、根表面积及平均直径的测定结果没有单独列出, 只在中列出不同测试终点的结果比较。根据上述8种土壤中Zn的生物毒性剂量-效应曲线拟合结果, 得到基于4种不同根微形态指标的毒性阈值EC10和EC50()。表明, 8种不同土壤中各根微形态指标毒性阈值差异较大, 例如根尖数、根总长、根表面积及根平均直径对应的EC10的范围分别为:106&#x0、186&#x0、192&#x0和136&#x0 mg&#x000b7; kg-1, 平均值分别为:228、295、335和261 mg&#x000b7; kg-1, 而EC50的范围分别为:519&#x0、579&#x0、598&#x0和540&#x0 mg&#x000b7; kg-1, 平均值分别为:702、779、837和739 mg&#x000b7; kg-1。在2种不同抑制率(EC10、EC50)测定结果中, 均以根尖数毒性阈值的均值为最小, 而以根表面积测定的阈值最大, 说明在不同的根系微形态测定指标中, 植物根尖发育受污染物胁迫反应最为敏感。表2Table 2表2(Table 2)
表2 不同土壤中Zn对大麦根尖数的毒性阈值及其95%置信区间
Table 2 Toxicity threshold (EC10 and EC50) of Zn in soils derived from the number of barley root tips and its 95% confidence intervals (mg&#x000b7; kg-1)土壤地点Soil site土壤类型Soil typeEC1095%置信区间95% confidence intervalEC5095%置信区间95% confidence interval廊坊 Langfang潮土 Fluvo-aquic soil386200-627953817-1102石家庄Shijiazhuang潮土Fluvo-aquic soil311198-453789711-1016公主岭Gongzhuling黑土Black soil275177-401730649-941广州Guangzhou红壤Red soil258159-386691598-864杭州Hangzhou水稻土Paddy soil224131-331672583-811嘉兴Jiaxing水稻土Paddy soil147124-302582506-785祁阳Qiyang红壤Red soil118101-236557471-646海口Haikou砖红壤Latosol10665-201469351-593
表2 不同土壤中Zn对大麦根尖数的毒性阈值及其95%置信区间
Table 2 Toxicity threshold (EC10 and EC50) of Zn in soils derived from the number of barley root tips and its 95% confidence intervals (mg&#x000b7; kg-1)图2Fig. 2 图2 基于不同测试终点测定的土壤中Zn毒性阈值&#x000D7; :最大值和最小值; I:10%-90%置信区间值; □:25%&#x02014; 75%置信区间值; &#x02014; :中值; 口:平均值Fig. 2 Comparison of toxicity thresholds (EC50, EC10) of Zn in soils and its x% (x=10, 90) confidence interval as determined by different test endpoints (mg&#x000b7; kg-1) &#x000D7; : The maxim I: Values of 10%-90% □: Values of 25%-75% &#x02014; : Mid- 口: Mean value RT50:根尖数EC50 EC50to RD50: 根平均直径EC50 EC50 to the aver RL50:根总长 EC50 EC50 RS50:根表面积EC50 EC50
RT10:根尖数EC10 EC10 to RD10:根平均直径EC10 EC10to the aver RL10:根总长EC10 EC10
RS10:根表面积EC10 C10 to rootsurface area2.3 基于不同根微形态进行Zn毒性阈值测定结果的差异性2.3.1 敏感性差异 不同测定指标对Zn毒性的敏感性差异对于重金属环境风险评价具有重要意义[]。本文将不同测定指标对重金属的敏感性定义为:在同一种土壤中, 不同测定指标对应的毒性阈值ECx的差异, ECx越小, 则敏感性越强, 反之, ECx越大, 则敏感性就越弱。由可知, 在EC10、EC50测定的结果中, 4种根微形态对土壤Zn毒性的敏感性从强到弱(毒性阈值ECx由小到大)依次为:根尖数> 根平均直径> 根总长> 根表面积。2.3.2 变异性差异 不同测试终点的变异性是污染物环境风险评价的主要影响因子之一。土壤Zn对重金属不同根微形态毒性阈值的平均值及对应的变异性系数如所示。不同微形态对应的EC10均值大小顺序为:根尖数< 根平均直径< 根总长< 根表面积, 不同测试终点的变异性系数中, EC10的根平均直径测定变异系数最大; EC50测定平均值的顺序与EC10的相同, 但变异性系数并没有明显规律, 表现为根平均直径的最大, 根尖数的最小。通过比较还发现, EC10的变异系数要普遍大于EC50的测定结果。在利用Log-logistic函数拟合出的&#x0201c; S&#x0201d; 型剂量-效应曲线获得毒性阈值EC10、EC50过程中, EC10位于较为平缓的曲线上段即斜率较小, 生态反应率随物质浓度的增大缓慢降低, 而EC50位于陡直的曲线中段, 物质浓度稍有增减即可引起生态反应率剧烈的变化, 故EC10较EC50通常具有更大的变异性[]。表3Table 3表3(Table 3)
表3 不同根微形态对Zn毒性的敏感性及其毒性阈值的变异系数
Table 3 Comparison of different mean toxicity thresholds (EC10, EC50) and the variation coefficient根微形态Root micromorphologyEC50平均值Mean value (mg&#x000b7; kg-1)EC50变异系数Coefficient of variation (EC50)EC10平均值Mean value (mg&#x000b7; kg-1)EC10变异系数Coefficient of variation EC10根尖数Number of root tiops7020.2002280.335根平均直径Average diameter of root7390.2322610.367根总长Total root length7790.2092950.285根表面积Root surface area8360.2253350.276
表3 不同根微形态对Zn毒性的敏感性及其毒性阈值的变异系数
Table 3 Comparison of different mean toxicity thresholds (EC10, EC50) and the variation coefficient2.4 基于根尖毒性的土壤中Zn毒性预测模型污染土壤中重金属毒性阈值与土壤主要性质间的关系及其预测模型, 是进行重金属污染土壤管理和风险评价的基础。为基于大麦根尖毒性测试终点的EC50值与土壤性质间相关性分析结果, 土壤pH、阳离子交换量(CEC)及有机碳(OC)含量与土壤中Zn的毒性阈值ECx呈现出正相关关系。影响土壤中Zn的毒性阈值ECx最重要的因子为土壤pH, 其他依次OC、CEC。由知, pH与大麦根尖数毒性阈值EC50的偏相关系数高达0.879, OC的相关系数为0.434, 此研究结果与前人的研究结论相似[]。同样的, 大麦的根表面积、平均直径等指标与土壤性质及Zn的毒性阈值间也有类似的相关关系。表4Table 4表4(Table 4)
表4 基于土壤主控因子与Zn毒性阈值的多元回归方程
Table 4 The multiple regression equation of soil properties affecting toxicity thresholds of Zn in soils (partial correlation coefficients and prediction models)回归方程 Regression equation决定系数Correlation coefficient (R2)Log(EC50) = 0.308pH+4.8200.620Log(EC50) =0.304pH+ 0.108OC+4.6850.696Log(EC50) = 0.305pH + 0.004CEC +0.114OC+4.6830.723pH, CEC and OC were soil pH value, cation exchange capacity and organic carbon content respectivelypH, CEC及OC分别为土壤pH、阳离子交换量及有机碳含量
表4 基于土壤主控因子与Zn毒性阈值的多元回归方程
Table 4 The multiple regression equation of soil properties affecting toxicity thresholds of Zn in soils (partial correlation coefficients and prediction models)3 讨论随着对污染土壤风险管理要求的不断提高, 针对重金属污染土壤的环境风险评价中, 生态风险评价的内容也在不断的深入。经济合作与发展组织(OECD)对污染土壤的风险评价提出了更高层次的风险评价[], 要求毒性测试中要包含尽量多的测试物种和测试终点、增加敏感的测试终点, 而且指标的选择也不能是简单的死亡, 因为研究表明, 一个物种的不同组织器官对毒物的敏感性存在着较大的差异[]。有研究表明[, ], Zn作为植物生长必须的元素之一, 在较低浓度时能促进生物生长代谢, 而当浓度较高时, 又会对植物产生一定毒害作用, 例如抑制植物根系对土壤营养元素的吸收, 干扰Fe元素的代谢进而导致植物缺Fe性失绿等。污染土壤中重金属的毒性受多种因子控制, 包括土壤pH、阳离子交换量(CEC)及土壤中胶体的种类和数量等。目前, 针对Zn污染土壤的环境风险研究中, Zn污染带来的生态风险是关注的热点, 而在不同的生态测试终点中, 根系微形态的毒性测试是植物生长毒性测试的主要指标之一。在重金属污染土壤中, 探明植物根系发育的不同测试终点(如根尖数、根长、根面积与根直径等)对重金属的毒性胁迫反应间是否存在敏感性差异以及敏感性顺序对重金属污染土壤的生态风险评价具有重要意义。本研究选择大麦作为模式作物, 基于剂量-效应关系模型测定了Zn胁迫条件下大麦根尖数、根长、根面积与根直径的毒性反应, 不同测试指标间的敏感性顺序结果表明, 在4种不同的根系微形态指标中, 植物根系的根尖对Zn毒性最为敏感, 其次为根平均直径、总根长和根表面积, 此结果为Zn污染土壤毒性测试增加敏感的测试终点提供了重要的参考依据。根系是重金属进入植物的首要屏障, 土壤重金属对植物的毒害最先由根部开始。研究发现, 在重金属Zn污染土壤中, 植物根尖对Zn2+毒性最为敏感, 受到伤害也最明显, 其次是侧根发育受到抑制[, , ]。本文对8种不同性质土壤中Zn胁迫对大麦根系微形态毒性测试结果与上述报道基本一致。有学者通过重金属砷对小麦生长影响的研究发现, 随着砷浓度增加, 小麦出现次生根数减少, 根体积变小, 根干重减轻等症状, 这可能是由于砷影响了小麦根的正常伸长和下扎的缘故[]; 在植物根冠中, 根细胞膜对外界环境变化比较敏感, 其稳定性是细胞进行正常新陈代谢的基础。重金属的胁迫可以增加细胞膜的通透性, 使细胞内电解质等外渗, 进而降低细胞的活性甚至导致死亡, 最终影响到植物根系的生长[]; 有研究表明, 重金属能够对细胞的超微结构产生一定损伤, 例如有研究者人曾用一定浓度重金属离子溶液处理车前草, 发现细胞出现叶绿体类囊体膨胀, 外膜断裂, 核膜破裂等情况[]。污染土壤中, 重金属的植物有效性受多种土壤性质的影响, 其中包括pH、有机质及阳离子交换量等。本文所选用的8种土壤中, 不同土壤性质具有明显差异。其中, 海口、祁阳二个地点土壤为酸性土壤, 嘉兴、杭州为中性土壤, 而广州、公主岭等为碱性土壤。土壤pH与有机质含量是影响重金属生物毒性的两个重要因素。土壤中pH升高, 土壤溶液中能够与重金属竞争吸附点位的H+、Fe2+、Al3+、Mg2+等阳离子含量降低, 而土壤中水合氧化物、黏土矿物及有机质等的负电荷含量增加, 土壤吸附与保持重金属离子的能力随之加强, 重金属的生物有效性也就随之下降[]; 土壤有机质主要是通过络合作用对重金属的生物有效性产生影响的[]。因而通常在有机质含量较高的土壤中, 重金属的生物有效性就相对较低, 即有机质含量与重金属的生物有效性呈负相关关系。所以, 在其他条件一致情况下, 有机质含量越高的土壤, 重金属的毒性阈值也就越高, 这与本实验结果一致。在进行不同性质土壤中重金属风险评价中, 基于不同性质的重金属毒性阈值预测模型对评估污染土壤中重金属生态风险具有重要意义。本文基于根不同微形态毒性测定结果表明, 土壤性质可以影响Zn的植物毒性, 其中影响土壤中Zn毒性阈值变化的主要理化因子为土壤pH, 而土壤阳离子交换量(CEC)和土壤有机碳含量(OC)影响相对较小。因此, 在评价土壤中Zn对植物的毒性时, 除Zn浓度外, 还需考虑土壤本身性质之间的差异, 应根据土壤性质的不同制定相应的评价指标体系。4 结论4.1外源添加Zn进行Zn对大麦根生长毒性测试结果表明, 土壤Zn对不同根微形态的毒性阈值存在较大差异, 以EC10测定结果为例, 根尖数测定结果均值最低, 其次为根平均直径和总根长, 根表面积的最高, EC50测定结果与之类似。4.2不同根微形态对Zn毒性的敏感性顺序为根尖数> 根平均直径> 总根长> 根表面积, 即根尖数对土壤Zn毒性最敏感。此外, EC10测定结果的变异系数要普遍大于EC50的测定结果。4.2相关关系分析表明, 土壤pH、有机碳(OC)、阳离子交换量(CEC)与Zn的毒性阈值ECx(x=10, 50)呈正相关关系, 其中土壤pH为最重要的影响因子, 偏相关系数均达到极显著水平(P< 0.01), 其次为OC、CEC, 基于土壤pH、OC、CEC等主要因子可以较好预测土壤中Zn的毒性阈值。
The authors have declared that no competing interests exist.
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... 0 引言【研究意义】Zn作为一种微量元素在动植物的生长过程中至关重要,而过量的Zn又会对动植物和人体健康造成一定的威胁与损害[1] ...
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李荣华, 沈锋, 李晓龙, 张增强
The goal of remediating polluted soil is to ensure safe reuse of the polluted soil by reducing the concentrations of pollutants in soil to the environmental standard limits. However, there is currently lack of evaluation on techniques and their performance of soil remediation, which has limited applications of the soil remediation in China. In this paper, we proposed technique selection standards and efficiency evaluation criteria of soil remediation, based on the related regulations of soil pollution control, the ecological risks of pollutants, and the current situation of soil pollution, and then examined the performance of proposed soil remediation techniques in laboratory and in-situ polluted field in Tongguan. The results showed that both soil remediation techniques and their performance evaluation criteria were practicable. This research could provide some valuable information for restoration of polluted sites, remediation of polluted farmland soils and protection of agricultural product safety.
对污染土壤进行修复的目的是在保证污染土地再利用的前提下,使受到较为严重污染的土壤中污染物降低或削减到不足以导致较大的生态损害和健康危害。但污染土壤修复措施及修复效果的评价方法的缺乏已成为限制污染土壤工程修复的关键。本文在对潼关县某铅锌冶炼厂区及周边受重金属污染农田的土壤污染现状进行调查的基础上,结合实际工程修复目标,综合考虑土壤类型、土地利用方式、作物种植特点、土壤重金属的淋溶特性和污染生态毒理学评价等因素,提出了重金属污染土壤修复方案的选择依据和不同修复方案修复效果评价方法,最后通过试验研究和工程实践,对污染土壤修复方案的选择和修复效果进行了检验。结果表明,修复方案选择依据及修复效果评价方法在实际污染土壤修复实践中取得了较好的结果。该研究结果可为污染场地治理、农田土壤修复及保障农产品安全提供科学参考。
... 近年来中国农田土壤锌(Zn)污染正以不同尺度的趋势快速蔓延[2,3],资料显示,中国Zn污染土壤超标率达0 ...
. ):922-930
SONG W , CHEN B M , LIU L.
宋伟, 陈百明, 刘琳
依托收集的耕地土壤重金属污染案例资料,建立了我国138个典型区域的耕地土壤重金属污染数据库,并利用《土壤环境质量标准》(GB1)中的二级标准作为评价标准,测算了我国耕地的土壤重金属污染概况。研究表明:(1)我国耕地的土壤重金属污染概率为16.67%左右,据此推断我国耕地重金属污染的面积占耕地总量的1/6左右;(2)耕地土壤重金属污染等别中,尚清洁、清洁、轻污染、中污染、重污染比重分别为68.12%,15.22%,14.49%,1.45%,0.72%;(3)8种土壤重金属元素中,Cd污染概率为25.20%,远超过其他几种土壤重金属元素;此外,也有一些区域发生Ni,Hg,As和Pb土壤污染,但是Zn、Cr和Cu元素发生污染的概率较小;(4)辽宁、河北、江苏、广东、山西、湖南、河南、贵州、陕西、云南、重庆、新疆、四川和广西14个省、市和自治区可能是我国耕地重金属污染的多发区域,特别是辽宁和山西的耕地土壤重金属污染可能尤其严重。
... 近年来中国农田土壤锌(Zn)污染正以不同尺度的趋势快速蔓延[2,3],资料显示,中国Zn污染土壤超标率达0 ...
... 虽然中国最新颁布的食品安全标准中删除了Zn的限量标准值[4],但由Zn污染产生的生态环境风险已引起广泛关注 ...
. ):689-698
SONG N N , HAUNG J S , GUO X Y , CHENG W D , ZHANG H M , WANG B R , WEI D P , MA Y B.
宋宁宁, 黄锦孙, 郭雪雁, 程旺大, 张红梅, 王伯仁, 韦东普, 马义兵
In this paper, field experiments were conducted to study the phytotoxicity of added copper (Cu) to local main crops in three field sites with contrasting soil physicochemical properties. Meanwhile, the phytotoxicity of corresponding soil samples were also measured using laboratory bioassays (barley root elongation, tomato, bok choy and local main crops seedling stage biomass). The results indicated that the phytotoxicity of Cu to field wheat, maize and rice was overestimated by laboratory bioassays of barley root elongation and bok choy biomass but was underestimated by tomato biomass. The similar sensitivity of field rape and bok choy suggested that the bok choy biomass in laboratory testing may be a suitable method to assess the toxicity of Cu to rape yield in field. When laboratory bioassays and field tests were conducted by using same plants, the seedling stage biomass of wheat, maize and rape in the laboratory could be used to estimate the phytotoxicity of Cu to grain yields of wheat at Lingxian, maize at Qiyang and rape at Jiaxing in the field (expressed as Cu toxicity threshold values EC 10 ). However, the phytotoxicity of Cu to wheat grain yield in the field at Qiyang was underestimated but rice grain yield at Jiaxing in the field was overestimated by laboratory bioassay, which indicated the differences of the Cu phytotoxicity measured using laboratory and filed bioassay were influenced by the soil types and plant species.
本论文对山东陵县、湖南祁阳和浙江嘉兴3种性质差异较大的土壤上进行的室内外的土壤外源铜(Cu)的植物毒性试验结果进行了比较。结果发现3种室内评价终点(大麦根长、西红柿和小白菜苗期生物量)和田间植物(玉米、小麦、水稻和油菜产量)对土壤中Cu毒性的敏感性存在较大的差异。大麦根伸长和小白菜生物量法高估了土壤中Cu对田间小麦、玉米和水稻产量的毒害,而室内西红柿生物量法则低估了土壤中Cu对田间小麦、玉米和水稻产量的毒害。小白菜和田间油菜的敏感性接近,可以用室内小白菜苗期生物量作为土壤中Cu对田间油菜产量毒性评价的植物。当采用相同植物比较时,陵县小麦、祁阳玉米和嘉兴油菜的室内苗期值可以作为土壤Cu对相同田间植物产量的毒害作用(EC 10 )的评价指标。但是,室内苗期毒害指标会低估Cu对田间祁阳小麦和高估嘉兴水稻的毒害作用,说明土壤Cu植物毒害室内外测定的差别受土壤和植物的影响。
... 目前,在环境风险评价中,对污染物评价终点的选取具有较大的偶然性,从而增加了污染物风险评价结果的不确定性[5],因此,不同测试终点的毒理学评价对于Zn污染土壤的环境风险评价具有重要意义 ...
... 20世纪90年代开始,美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究,制定和颁布了许多行业标准、规范和技术框架[6,7],而国内的研究起步相对较晚,在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[8,9,10] ...
... 20世纪90年代开始,美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究,制定和颁布了许多行业标准、规范和技术框架[6,7],而国内的研究起步相对较晚,在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[8,9,10] ...
WANG X Q , WEI D P , HUANG Z B , MA Y B.
王小庆, 韦东普, 黄占斌, 马义兵
摘 要: 本文利用不同累计概率分布函数拟合了基于中国土壤的17个物种的镍毒理学数据。结果表明,BurrⅢ在X轴(浓度)方向及Y轴的较小累计概率范围内拟合优度较佳。在构建土壤中镍物种敏感性分布曲线时,利用镍生物毒害模型归一化处理能修正土壤性质的影响且可更好地体现物种敏感性差异,相比于未归一化处理的结果更具科学性。在此基础上结合镍的生物毒害模型利用BurrⅢ构建了中国土壤4种典型情景中的物种敏感性分布曲线,同时确定了不同土壤情景下的镍生态阈值,即酸性土壤、中性土壤(包括水稻土)、碱性非石灰性土壤和石灰性土壤的镍生态阈值分别为6.5、47.5、218.8mg.kg-1和120.3mg.kg-(1以土壤中外源镍为单位)。
... 20世纪90年代开始,美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究,制定和颁布了许多行业标准、规范和技术框架[6,7],而国内的研究起步相对较晚,在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[8,9,10] ...
SONG W E , CHEN S B.
宋文恩, 陈世宝
【Objective】Although the attention has been paid for decades to the ecological risk of Cd to rice in soils, most studies focused on its healthy risk in terms of the food standard instead of its ecological risk and toxicity thresholds in soils. The toxicity thresholds (ECx, x=10, 50) and its predicted models of Cd to rice cultivars in various soils in China were determined using ISO 11269-1 root-elongation endpoints with the aim of providing fundamental data for the revision of soil environmental quality standards of Cd in soils of China.【Method】Eight different soils with various properties and three rice cultivars were selected in this study, the dose-response curves and the toxicity thresholds were investigated using Log-Logistic distribution models based on the ISO 11269-1 root-elongation test in soils, the predicted models for Cd toxicity was also developed in this study. 【Result】The results indicated that the relative root elongation (%) decreased with the Cd concentrations increment in soils. The 10% (EC10) and the half inhibiting concentration (EC50) of Cd to rice cultivars varied significantly among the tested soils and the rice species. In general, the toxicity thresholds (ECx, x=10, 50) of Cd to rice species decreased with it&s sensitiveness to Cd stress in soils, i.e. the ECx followed the order of T167>L28>X45. The significant differences of the toxicity thresholds (ECx, x=10, 50) of Cd to rice species were also observed in this study as determined with single rice species, e.g. in terms of the Cd-stress-sensitive cultivar of T167, the 10% inhibiting concentration (EC10) of Cd to root-elongation varied form 1.40-5.25 mg&kg-1 with the maximum variety of 275.0%, the half inhibiting concentration (EC50) varied form 17.83-46.93 mg&kg-1 with the maximum variety of 163.2%, respectively. However, for the Cd-stress-tolerance cultivar of X45, the 10% inhibiting concentration (EC10) of Cd to root-elongation varied form 1.72-8.22 mg&kg-1 with the maximum variety of 377.9%, the EC50 varied form 26.96-68.16 mg&kg-1 with the maximum variety of 152.8%, respectively. The multiple regression analysis showed that there was a significant positive correlation (P<0.05) between soil pH, organic carbon (OC), cation exchange capacity (CEC) and the toxicity thresholds (ECx, x=10, 50) of Cd to rice cultivars in soils. A predicted model was developed and validated for the toxicity thresholds (ECx, x=10, 50) of Cd to rice with the measured ECx fell within the range of predicted values&2 standard deviations. 【Conclusion】 Significant difference of the toxicity thresholds (ECx, x=10, 50) of Cd to rice cultivars was observed in soils as determined by root-elongation test, and a significant positive correlation (P<0.05) was also observed between soil pH, OC, CEC and the toxicity thresholds. The ECx of Cd toxicity were affected by the variance of the tested rice cultivars in soils, the ecological toxicity of Cd to different test endpoints should be considered for the future revision of the soil environmental quality standards of Cd in soils of China.
【目的】虽然土壤中镉(Cd)污染对水稻的生态风险受关注已久,然而大量研究集中在基于稻米中Cd限量标准的健康风险研究,而针对土壤中Cd污染的生态风险阈值研究较少。研究通过ISO11269-1根伸长毒性测试方法,测定不同性质土壤中Cd对水稻的毒性阈值(ECx,x=10,50)及其预测模型,以期为基于生态毒理效应的中国土壤Cd污染基准值的修订提供参考。【方法】采用中国8种不同性质农田土壤和3种不同Cd敏感性差异的水稻品种(T优167,T167;陆两优28,L28;湘早45,X45)为试材,每种土壤添加7个Cd浓度,通过ISO11269-1根伸长测试方法,测量水稻根的相对伸长量,并结合Log-Logistic分布函数模型测定不同土壤中水稻Cd毒性的剂量-效应关系、毒性阈值(ECx, x=10, 50)及其预测模型。【结果】随着土壤Cd浓度的增加,不同土壤中水稻的相对根长(%)逐渐减小,基于根伸长的Cd对水稻毒性的10%抑制浓度的毒性阈值(EC10)和半抑制浓度(EC50)值在不同土壤和不同Cd敏感性水稻品种间有较大差异。总体而言,在3种不同Cd敏感性(T167>L28>X45)水稻品种中,同一土壤中Cd的水稻毒性ECx(x=10,50)随着水稻对Cd胁迫的敏感性增强而降低;就单一品种水稻而言,不同土壤的Cd水稻毒性阈值ECx间有显著差异。其中,以Cd敏感性水稻品种T167测试的不同土壤EC10变化为1.40&5.25 mg&kg-1,最大相差275.0%,EC50变化为17.83&46.93 mg&kg-1,最大相差163.2%;以Cd非敏感性水稻品种X45测试的不同土壤EC10变化为1.72&8.22 mg&kg-1,最大相差377.9%,EC50变化为26.96&68.16 mg&kg-1,最大相差152.8%。通过水稻Cd毒性阈值ECx与土壤性质间的多元回归分析表明,土壤pH、有机碳(OC)、阳离子交换量(CEC)与水稻Cd毒性阈值间呈正相关关系,基于土壤主要性质的水稻Cd毒性预测模型表明,EC50实测值均在预测值2倍误差(&S.D)范围内。【结论】基于ISO11269-1根伸长毒性测试结果表明,不同土壤中Cd的水稻毒性阈值间有显著差异,土壤pH、OC及CEC与水稻Cd的毒性阈值间呈显著正相关关系(P<0.05),基于上述土壤性质的预测模型可以很好预测不同土壤中Cd对水稻的毒性;不同Cd敏感性品种对测定土壤中水稻Cd毒性阈值有明显差异,因此,在制订土壤中Cd的生态基准时应充分考虑不同物种的敏感性差异特征。
... 20世纪90年代开始,美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究,制定和颁布了许多行业标准、规范和技术框架[6,7],而国内的研究起步相对较晚,在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[8,9,10] ...
... 目前,国内有部分学者针对土壤重金属的风险评价进行了研究,并取得一些进展[9, 11,12,13] ...
... 20世纪90年代开始,美国、英国、加拿大、澳大利亚等欧美发达国家在土壤生态风险评价领域开展了系列的研究,制定和颁布了许多行业标准、规范和技术框架[6,7],而国内的研究起步相对较晚,在土壤重金属污染的生态风险评价理论和方法方面总体比较薄弱[8,9,10] ...
. ):491-497
CHEN B Y , ZHENG S R , NIU X C , ZHAO J S.
陈波宇, 郑斯瑞, 牛希成, 赵劲松
物种敏感度分布是一种基于单物种测试的外推方法,其在生态毒理学中的应用近年来已成为研究热点.论文阐述了物种敏感度分布在生态毒理学的应用背景,以及其基本内涵与研究步骤,同时介绍了物种敏感度分布在生态毒理学中应用的两个方面:制定污染物的环境质量标准和对污染生态系统的生态风险评价,并对物种敏感度分布的不确定性和研究的发展趋势进行了讨论.
... 目前,国内有部分学者针对土壤重金属的风险评价进行了研究,并取得一些进展[9, 11,12,13] ...
... 目前,国内有部分学者针对土壤重金属的风险评价进行了研究,并取得一些进展[9, 11,12,13] ...
. ):922-930
CHEN S B , LIN L , WEI W , LIU J F , MA Y B.
陈世宝, 林蕾, 魏威, 刘继芳, 马义兵
The toxicity thresholds (ECx, x=10,50, the effective concentration causing 10% and half inhibition) of Zn in sixteen Chinese soils were determined using log-logistic distribution models with four different toxicity bioassay endpoints, i.e., the potential nitrification rate (PNR) test, the barley root elongation assay (BRE), tomato (TGT) and bok choy (BGT) phytotoxicity test respectively, the quantitative relationship between the ECx of Zn in soils and the main physic-chemical (e.g. pH, CEC and org-C etc) was also quantitatively measured, and the toxicity based predicted models of Zn in soils were developed. The results indicated that toxicity thresholds of Zn varied significantly among the different bioassay endpoints. The toxicity thresholds of EC10 of bok choy growth toxicity, barley root elongation, tomato growth toxicity and potential nitrification rate test were 322, 356, 336及297mg/kg, respectively, the lowest EC10 was observed with potential nitrification rate test while the highest with barley root elongation test. The determined EC50 of the same order of bioassay endpoints were 846,
and 768mg/kg respectively. In general, the sensitivity of the bioassay endpoints followed the order of: the potential nitrification rate test> tomato phytotoxicity test > bok choy phytotoxicity test> the barley root elongation test, while the test stability reversed. The result implied that the microbe were the most sensitive organism responded to the Zn toxicity and the tomato was the most sensitive plant among the tested crops. In terms of the applicability, the EC50 values were more sensitive than that of EC10, while the larger variation coefficient was observed with EC10 test. The pH value was the most important factor affecting the bioavailability of Z the environmental risk can be well predicted by the normalization models developed on the pH, CEC and organic carbon contents of the soils.
采用基质诱导硝化(PNR)、大麦根伸长、西红柿及小白菜生长毒性测试方法,结合Log-logistic模型,对我国16种典型土壤中锌(Zn)的毒性阈值(ECx)进行了测定,同时对Zn毒性与土壤主要影响因子间的量化关系及其预测模型进行了研究.结果表明:我国土壤中Zn的毒性阈值在不同测试物种间存在较大差异,以小白菜、大麦、西红柿及土壤微生物(PNR)测试的EC10均值分别为322,356,336,297mg/kg,以土壤微生物测试最低,以大麦根伸长测定结果最高; EC50均值则分别为: 846,8mg/kg.不同测试方法对土壤中Zn毒性的敏感性顺序为:土壤微生物(PNR)>西红柿>小白菜>大麦,而不同测试方法的稳健性顺序则相反,表明PNR法是土壤Zn毒害最敏感的测试方法,而西红柿则是对土壤Zn污染胁迫最敏感的植物品种; 不同毒性测试结果显示,EC50阈值的测定结果要敏感于EC10,而EC10测定结果的变异系数普遍大于EC50的测定结果.pH值是影响土壤Zn毒性阈值最为重要的因子,而基于土壤pH值,CEC,有机碳含量的归趋化预测模型可以很好地预测土壤中Zn的生态风险阈值.
... 目前,国内有部分学者针对土壤重金属的风险评价进行了研究,并取得一些进展[9, 11,12,13] ...
. ):692-703
ZHANG X M , ZHANG X Y , ZHONG T Y , JIANG H.
张小敏, 张秀英, 钟太洋, 江洪
摘 要: 在统计有关我国农田土壤重金属相关文献数据的基础上,探讨了我国农田土壤重金属Pb、Cd、Cu、Zn和cr的空间富集现状.收集到有关土壤Pb、Cd、Cu、Zn和cr含量的研究分别为173、138、156、139、140个.首先剔除异常值,然后利用剩余样本进行克里金插值,并统计各省地区重金属含量平均值.结果表明我国重金属空间分布具有明显的区域特征,西南地区土壤重金属含量较高,其他地区相对较低;与分省的土壤背景值相比较,农田土壤Ph和cd的含量明显高于背景值.土壤Pb在云南省超出背景值最高,为背景值的1.91倍;Cd在辽宁省超出背景值最高,为23.02倍;Zn在云南省富集最为严重,是背景值的1.55倍,Cu最高的是广东省,达到背景值的2.92倍.
... 总体而言,目前国内针对重金属污染土壤的生态风险评价主要集中在利用不同指数法对污染土壤进行的污染等级划分、污染来源调查等[14,15],大部分情况下没有能够与土壤利用相结合,特别是在农田土壤的评价中,忽略了土壤和农产品质量之间的联系 ...
HAO H Z , JIN M G , LI R M , WANG Z N , HAN B H.
郝汉舟, 靳孟贵, 李瑞敏, 王支农, 韩斌华
土壤重金属总量常被用来评估土壤质量安全,但是大量事实说明单纯用土壤重金属总量并不能完全说明土壤重金属的生物有效性及其环境风险.相对于国内外常用的Tessier的五态方法,欧共体标准物质局提出的三步提取法(BCR法),中国地质调查局地质连续提取法的七态标准少见报道.本研究选取河南平原耕地样品,采用中国地质调查局地质连续提取法(DD2005-03)进行耕地中重金属元素(Cu、Cd、Zn)的形态分布,结果表明:Cu、Zn主要以残渣态存在,其残渣态分别占全量的55.80%和67.35%.Cd以离子交换态为主,占全量的27.30%.Cu、Cd、Zn各态含量占全量比例的顺序是,Cu:残渣态)弱有机结合交换态)铁锰氧化态)碳酸盐结合态)强有机结合态)水溶态)离子交换态.Cd:离子交换态)弱有机结合交换态)强有机结合态)残渣态)碳酸盐结合态)铁锰氧化态)水溶态.Zn:残渣态)铁锰氧化态)弱有机盐结合态)离子交换态)强有机结合态)碳酸盐态)水溶态.从生物可利用性系数k来看,Cd主要以活动性较大的状态存在,很容易被作物吸收.
Abstract:
The complexity of metal contaminated sites has and continues to be simplified to a measure of the total metal content. While total metal content is a critical measure in assessing risk of a contaminated site, total metal content alone does not provide predictive insights on the bioavailability, mobility, and fate of the metal contaminant. The paper was based on heavy metal speciation of soil-plant system in cultivated land, Henan plain, the order of Cd in each fraction was Exchangeable (27.3%) ) Weakly bound to organic matter (22.7%) ) Strongly bound to organic matter (16.4%) ) Residual (15.1%) ) Carbonate (12.1%) ) Fe/Mn oxide bound (4.5%) ) Water soluble (2.0%), Zn was Residual (66.3%) ) Fe/Mn oxide bound (10.9%) ) Weakly bound to organic matter (9.4%) ) Exchangeable (6.0%) ) Strongly bound to organic matter (3.9%) ) Carbonate (2.9%) ) Water soluble (0.6%). The accuracy of the sequential extraction was judged by the relative error (RE). RE for Cd ranged from 0 to 45% with mean 16.3%.RE for Zn ranged from 0.1%-11.4% with mean 3.4%. On average, bioavailability index (BI) for Cd and Zn is 39.1% and 9.0% respectively. The mobil-ity of the elements in the order Cd ) Zn corresponds with the plant-availability of individual elements.
... 总体而言,目前国内针对重金属污染土壤的生态风险评价主要集中在利用不同指数法对污染土壤进行的污染等级划分、污染来源调查等[14,15],大部分情况下没有能够与土壤利用相结合,特别是在农田土壤的评价中,忽略了土壤和农产品质量之间的联系 ...
CHEN S B , SUN C , WEI W , LIN L , WANG M.
陈世宝, 孙聪, 魏威, 林蕾, 王萌
A hydroponic culture experiment was conducted to investigate the uptake and transfer factor (TF) of zinc (Zn) by different plant species, the translocation and the redistribution of Zn in the cell wall and its’ components were also studied. The results showed that the Zn uptake and its translocation differed significantly between six cultivars, the largest shoot Zn concentrations were found in Chinese cabbage and lettuce, while rice had the largest Zn concentration in root. With the addition of 50mg/L Zn in solution, the shoot to root transfer factors of Zn by plant species followed: Chinese cabbage ≈ leaf mustard ≈ lettuce>sweet green pepper > tomato > rice, however, the TF of lettuce exceeded the leaf mustard under the lower addition concentration (20mg/LZn), it’s probably related with the hormesis of Zn phyto-toxicity to lettuce. The Zn immobilization by cell wall was an important mechanism for Zn detoxification. By the in-situ desorption technique, the Zn accumulation in cell walls and their components were measured. The result showed that the Zn contents of cell walls increased significantly after removing pectin among plant species, the largest increment of 53.7% was found with rice while the least (21.1%) with sweet green pepper. The result of adsorption kinetics of Zn on the root cell walls indicated the adsorption of Zn by raw cell walls and treated cell walls was a fast reaction, more than 91% of total Zn was adsorbed by the adsorbents within 30min, the adsorption maximum of Zn by cell walls increased significantly after removing pectin among plant species, on the contrary, the adsorption maximum of Zn by cell walls decreased remarkably after removing pectin and hemicellulose, especially with the cell walls of rice. The results indicated that the hemicellulose components in cell walls played an important role in bonding Zn and thereafter reducing the translocation of Zn in xylem in plants.
采用水培实验,研究了不同植物根细胞壁组分差异对Zn吸收、转运的影响及其机制.结果表明,在50mg/LZn处理下,不同植物对Zn的吸收、转运系数顺序为:小白菜≈芥菜≈生菜>青椒>西红柿>水稻,而在20mg/L Zn处理下,生菜茎叶中Zn的转运系数则大于芥菜,这可能与低浓度条件下Zn对生菜产生的低剂量刺激效应有关;利用植物活体根细胞解吸法对不同植物活体根系细胞壁中的Zn含量测定结果表明,不同植物的根细胞壁在去除了果胶成分后,根细胞壁中Zn的含量显著增加,其中水稻根细胞壁增加最大,达到53.7%,增加最小的是青椒(21.1%),而去除半纤维素后则显著降低了不同植物根细胞壁中Zn的含量,尤其是水稻根细胞壁最明显;吸附动力学实验表明,不同处理后的细胞壁对Zn的吸附是个快速反应过程,在吸附30min内所有处理均达到最大吸附量的91%以上,去除果胶显著增加不同细胞壁对Zn的吸附量,而进一步去除半纤维素后,不同细胞壁对Zn的最大吸附量显著下降.以上结果表明,半纤维素含量的增加明显提高了不同植物根束缚Zn的能力而降低向地上部的运输.
... 根细胞是重金属进入植物体进行吸收、转运的第一道屏障[16],从植物地上部生物量及植物体重金属吸收测定评价而言,重金属胁迫对植物根系发育的毒性研究对于探明重金属污染土壤的生态系统退化作用、机理和过程及地下生态风险有重要意义[17] ...
ZHOU Q , OU X K , ZHANG Z M.
周庆, 欧晓昆, 张志明
生态系统破坏与退化的加剧使生态恢复成为全球性的挑战课题,近年来生态恢复的研究已逐渐由地上向地下部分转移,地下部分对生态系统退化所起的作用、机理和过程已倍受关注。本文通过探讨恢复生态学的关键概念,从土壤、地下水循环、生物系统3个方面探讨了地下生态系统对生态恢复的作用机理和反馈机制。针对目前的研究现状,指出地下生态系统研究中存在的问题,并提出今后需要深入研究的几个方向:1)生态系统退化程度的诊断及其标准;2)基于诊断标准,针对不同退化生态系统类型选定恢复的目标植物群落,如何改善土壤性质,确定土壤性质的改善程度;确定地下水位及土壤含水量的阈值;如何有效选择、引入和接种土壤生物;3)生态系统地上和地下部分整合及恢复过程中监测指标的确定。
... 根细胞是重金属进入植物体进行吸收、转运的第一道屏障[16],从植物地上部生物量及植物体重金属吸收测定评价而言,重金属胁迫对植物根系发育的毒性研究对于探明重金属污染土壤的生态系统退化作用、机理和过程及地下生态风险有重要意义[17] ...
... 土壤性质测试[18]结果见表1,土壤样品在室内风干后去除杂物,并过2 mm的尼龙筛备用 ...
LIN L , CHEN S B , LIU J F , MA Y B.
林蕾, 陈世宝, 刘继芳, 马义兵
(Ministry of Agriculture Key Laboratory of Crop Nutrition and Fertilization/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)
Six typical China soils with different properties were selected and added with seven concentrations of ZnCl 2 to study the effects of different aging time (14, 90, 180, 360, and 540 days) on the form transformation and eco-toxicity threshold (EC x ) of added Zn in the soils, with the main affecting factors analyzed. The results indicated that with the increase of aging time, the fraction of 0.01 mol&L -1 CaCl 2 ??extracted Zn in the soils decreased sharply initially, then slowed down, and reached the dynamic balance after 540 d incubation. The eco?toxicity thresholds (EC x , x=10, 50) of Zn to bok choy increased significantly with aging time ( P 10 ? and AF 50 ? of Zn ranged from 1.077-1.743 and 1.174-1.441, respectively, and increased with aging time. The balanced concentration of Zn in the soils was significantly negatively correlated with soil pH, CEC, and organic carbon (Org-C) content, and soil pH was the most important controlling factor, followed by CEC and Org-C. It took shorter time to reach Zn balance in the soils with higher pH. The prediction model of the EC x ? of Zn was developed based on the aging factors and the main soil properties, and could be well validated by the measured EC x ? under field condition. This study would provide theoretical basis for the normalization of the eco-toxicity thresholds of added Zn in different soils and the formulation of the environmental criterion of Zn in China soils.
选取了6种不同性质土壤, 添加7个浓度水平的Zn, 研究了不同老化时间(14、90、180、360和540 d)对土壤中外源性Zn有效形态及毒性阈值(EC x )的影响, 并对Zn老化过程的主要影响因子进行分析. 结果表明: 土壤中0.01 mol&L -1 ?CaCl 2 ?提取态Zn含量随着老化时间的增加先快速下降, 随后变化减缓, 到540 d时基本达到平衡.随着老化时间的增加, 土壤中Zn对小白菜生长的毒性阈值(EC x , x=10、50)逐渐增加,毒性显著降低( P 10 和AF 50 分别为1.077~1.743和1.174~1.441, 老化因子随老化时间增加而增大.土壤中Zn的平衡浓度( C & )与土壤pH、阳离子交换量(CEC)、有机碳含量呈显著负相关关系, 其中pH是决定Zn老化速率最重要的因素, 其次是CEC和有机碳含量,高pH下土壤中Zn达到平衡所需的时间较短. 基于土壤老化因子与主控因子建立土壤中Zn的毒性阈值预测模型,所得预测值与实测值之间有较好的相关性.研究结果将为不同土壤中外源性Zn毒性阈值的归一化处理及生态风险基准值的制定提供理论依据.
... 根据重金属在不同性质土壤中平衡反应的时间[19],本试验中外源Zn平衡28 d后进行盆栽试验 ...
. /3):350-358
LEI B L , HUANG S B , WANG Z J.
雷炳莉, 黄圣彪, 王子健
生态风险评价从最初单物种毒性测试数据为基础、从急性毒性数据外推获得慢性毒性数据的简单模型方法,逐步过渡到以多物种测试为基础和通过微、中宇宙生态系统模拟法获取数据、建立模型,以及以生态毒理模型为基础的生态风险评价方法。本文讨论生态风险评价方法的发展过程及不同阶段存在的问题,阐述以个体、种群和生态系统为基础的生态风险评价方法的特点和相互之间的区别,指出生态风险评价正在从个体走向群落的发展趋势。本文同时对风险表征方法、数据选择和常用统计方法作了评述,并对生态风险评价的发展趋势进行了预测。
... 3 数据处理常用的剂量-效应曲线有Log-normal、Weibull、Gamma等,其中Log-logistic函数因其拟合参数均与实际生物效应有关而被广泛采用[20,21],本研究采用Log-logistic剂量-效应函数模型进行阈值的计算: ...
... 经济合作与发展组织(OECD)对污染土壤的风险评价提出了更高层次的风险评价[24],要求毒性测试中要包含尽量多的测试物种和测试终点、增加敏感的测试终点,而且指标的选择也不能是简单的死亡,因为研究表明,一个物种的不同组织器官对毒物的敏感性存在着较大的差异[20] ...
... 有研究表明[20,21],Zn作为植物生长必须的元素之一,在较低浓度时能促进生物生长代谢,而当浓度较高时,又会对植物产生一定毒害作用,例如抑制植物根系对土壤营养元素的吸收,干扰Fe元素的代谢进而导致植物缺Fe性失绿等 ...
... 3 数据处理常用的剂量-效应曲线有Log-normal、Weibull、Gamma等,其中Log-logistic函数因其拟合参数均与实际生物效应有关而被广泛采用[20,21],本研究采用Log-logistic剂量-效应函数模型进行阈值的计算: ...
... 1 敏感性差异 不同测定指标对Zn毒性的敏感性差异对于重金属环境风险评价具有重要意义[21] ...
... 434,此研究结果与前人的研究结论相似 [21] ...
... 有研究表明[20,21],Zn作为植物生长必须的元素之一,在较低浓度时能促进生物生长代谢,而当浓度较高时,又会对植物产生一定毒害作用,例如抑制植物根系对土壤营养元素的吸收,干扰Fe元素的代谢进而导致植物缺Fe性失绿等 ...
... 研究发现,在重金属Zn污染土壤中,植物根尖对Zn2+毒性最为敏感,受到伤害也最明显,其次是侧根发育受到抑制[21,22, 24] ...
... 在植物根系发育中,相对于总根长、根表面积和根平均直径指标而言,根尖生长时对外部环境的胁迫更为敏感[22] ...
... 研究发现,在重金属Zn污染土壤中,植物根尖对Zn2+毒性最为敏感,受到伤害也最明显,其次是侧根发育受到抑制[21,22, 24] ...
. ):890-896
WANG X Q , LI J M , WEI D P.
王晓庆, 李菊梅, 韦东普
The dose-response relationship is an important part of ecotoxicology. Different effective concentrations causing inhibition for chemicals could be derived based on the dose-response relationship. The effective concentration causing 10% inhibition (EC 10 ) values are the basis for establishing risk-based environmental quality criteria, while most of the thresholds reported in the research about ecotoxicity were the effective concentration causing 50% inhibition (EC 50 ) values. To find out the quantative relationship of different ecotoxicity thresholds is a key issue needed to be addressed for deriving environmental quality criteria. In this paper, the dose-response curves of copper and nickel to barley root elongation, tomato and bok choy growth in 17 Chinese representative soils were fitted with log-logistic functions. The slopes (b) of the curves were obtained and the EC 10 and EC 50 values for the three plants in different soils were derived based on dose-response curves. The results showed that the soil properties affected the b values significantly. The b values for copper dose-response curves of barley, tomato and bok choy were in the range of 3.9~11.5, 2.7~12.1and 3.3~13.5, respectively. The b values for nickel dose-response curves of the three plants were in the range of 4.1~10.4、4.0~14.8 and 1.8~14.8, respectively. The b values for copper and nickel of the three plants were generally similar with an average mean value of 6.0 and 7.0 which implied that the variation of b value for a given toxicant in different plant species was not significant. The quantitative equations of EC 10 and EC 50 for copper and nickel were obtained based on ecotoxicity data from Chinese soils. The predictive models with the determination coefficient ( R 2 x ) of 0.704 and 0.799, respectively, could predict EC 10 values for copper and nickel based on EC 50 values accurately. When taking into account the effect of pH in copper EC 10 predictive model and organic carbon (OC) in nickel EC 10 predictive model, the determination coefficient of the models increased up to 0.730 and 0.885, respectively. The quantitative equations of EC 10 and EC 50 for copper and nickel will provide more data basis for the risk assessment and the establishment of related soil standards.
污染物的剂量-效应关系是生态毒理学的重要基础。在剂量-效应关系中,EC 10 (10%有效抑制浓度) 是建立基于风险的环境质量基准值的基础,但有关污染物生态效应的研究报导中多数采用毒性阈值EC 50 (半数抑制浓度),如何将EC 50 转化为EC 10 是建立污染物环境质量基准急需解决的问题。利用log-logistic拟合了中国17种代表性土壤中大麦、西红柿、小白菜3种植物的铜和镍剂量—效应曲线,获得了不同土壤中铜、镍剂量—效应曲线中段的斜率(b值),并依据计量—效应曲线获得3种植物在不同土壤中的铜、镍EC 10 和EC 50 值。结果表明:铜和镍的剂量—效应曲线 b值受土壤性质显著影响,但不同物种间的变化较小,大麦、西红柿及小白菜的铜、镍剂量—效应曲线b值绝对值的平均值分别接近于6.0和7.0。利用来自中国土壤的毒理学数据建立的铜和镍EC 50 和EC 10 单因子量化模型能较为准确地通过铜和镍EC 50 值预测其EC 10 值,其量化模型的决定系数 分别为0.704和0.799,当分别考虑土壤pH和有机碳 (OC) 的影响时,铜和镍的EC 10 量化模型的决定系数分别提高至0.730和0.885。土壤中铜、镍EC 10 与EC 50 量化关系的建立可为中国土壤中铜、镍的风险评价及相关标准的制定提供更多的数据基础。
... 型剂量-效应曲线获得毒性阈值EC10、EC50过程中,EC10位于较为平缓的曲线上段即斜率较小,生态反应率随物质浓度的增大缓慢降低,而EC50位于陡直的曲线中段,物质浓度稍有增减即可引起生态反应率剧烈的变化,故EC10较EC50通常具有更大的变异性[23] ...
... 经济合作与发展组织(OECD)对污染土壤的风险评价提出了更高层次的风险评价[24],要求毒性测试中要包含尽量多的测试物种和测试终点、增加敏感的测试终点,而且指标的选择也不能是简单的死亡,因为研究表明,一个物种的不同组织器官对毒物的敏感性存在着较大的差异[20] ...
... 研究发现,在重金属Zn污染土壤中,植物根尖对Zn2+毒性最为敏感,受到伤害也最明显,其次是侧根发育受到抑制[21,22, 24] ...
... 有学者通过重金属砷对小麦生长影响的研究发现,随着砷浓度增加,小麦出现次生根数减少,根体积变小,根干重减轻等症状,这可能是由于砷影响了小麦根的正常伸长和下扎的缘故[25] ...
... 重金属的胁迫可以增加细胞膜的通透性,使细胞内电解质等外渗,进而降低细胞的活性甚至导致死亡,最终影响到植物根系的生长[26] ...
... 有研究表明,重金属能够对细胞的超微结构产生一定损伤,例如有研究者人曾用一定浓度重金属离子溶液处理车前草,发现细胞出现叶绿体类囊体膨胀,外膜断裂,核膜破裂等情况[27] ...
... 土壤有机质主要是通过络合作用对重金属的生物有效性产生影响的[27] ...
... 土壤中pH升高,土壤溶液中能够与重金属竞争吸附点位的H+、Fe2+、Al3+、Mg2+等阳离子含量降低,而土壤中水合氧化物、黏土矿物及有机质等的负电荷含量增加,土壤吸附与保持重金属离子的能力随之加强,重金属的生物有效性也就随之下降[28] ...
基于根微形态测定土壤Zn对大麦的毒性阈值及其预测模型
[何俊1, 田昕竹1,3, 王学东1, 刘彬2, 李宁2, 郑涵2, 孟楠2, 陈世宝2]

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