环境科学  2023, Vol. 44 Issue (5): 2849-2855   PDF    
长株潭地区土壤Cd和Pb固液分配特征与环境风险
李钰滢, 彭驰, 刘乐乐, 张严, 何亚磊, 郭朝晖, 肖细元     
中南大学冶金与环境学院环境工程研究所, 长沙 410083
摘要: 区域尺度上土壤重金属下渗迁移的环境风险存在较大空间变异性.以长株潭城市及其周边土壤为对象,研究了不同土地利用类型,土壤Cd和Pb有效态含量和固液分配系数(Kd)的分布特征及其影响因素,并基于CaCl2(固液比为1:0.5)测定的Kd揭示了研究区土壤重金属下渗迁移的环境风险.结果表明,研究区土壤Cd和Pb有效态含量大小呈现出:自然林地>郊区农田>城市绿地>工业区绿地.土壤Cd的Kd均值为449.79 L ·kg-1,Pb的Kd均值为27604.07 L ·kg-1,说明土壤Cd迁移性显著高于Pb.林地土壤重金属的Kd显著低于其它3种土地利用类型土壤.土壤Cd和Pb的Kd主要受土壤pH和重金属总量的影响.在此基础上,引入CaCl2(固液比为1:10)测定的重金属有效态含量作为因变量,构建的多元回归模型可以较好地预测土壤Cd和Pb的KdR2分别为84.2%和67.6%.环境风险评估结果表明,研究区93.8%~96.1%采样点的土壤Cd和Pb无下渗迁移风险,少数靠近工厂且土壤pH较低的采样点存在轻度风险.土壤重金属的迁移性和污染源分布共同决定了重金属下渗迁移的环境风险.研究结果可以为区域土壤重金属污染风险防控提供方法和理论支撑.
关键词: 城市化区域      重金属      有效态含量      下渗迁移风险      回归预测     
Solid-solution Partitioning Coefficients and Environmental Risk of Cd and Pb in Soil in Chang-Zhu-Tan Area
LI Yu-ying , PENG Chi , LIU Le-le , ZHANG Yan , HE Ya-lei , GUO Zhao-hui , XIAO Xi-yuan     
Institute of Environmental Engineering, School of Metallurgy and Environment, Central South University, Changsha 410083, China
Abstract: The leaching risk of heavy metals in soil has a large spatial variability on a regional scale. Taking the Chang-Zhu-Tan area as the research object, this work studied the distribution and influencing factors of available contents and solid-solution partition coefficient (Kd) of Cd and Pb in soil with land uses and clarified the environmental risk of heavy metals in soil based on Kd values measured by CaCl2 (soil-to-water ratio, 1:0.5). The results showed that the contents of available Cd and Pb in soil followed the order of forest land>suburban farmland>urban green space>industrial green space. The average Kd of Cd in soil was 449.79 L·kg-1, and that of Pb was 27604.07 L·kg-1, indicating that the mobility of Cd in the soil was significantly higher than that of Pb. The Kd values of forest soil were significantly lower than that in the other land uses. The Kd values were mainly affected by soil pH and the total content of heavy metals in soil. Adopting the available content of heavy metals measured by CaCl2 (soil-to-water ratio, 1:10) as a dependent variable, the multiple regressions effectively predicted the Kd values of Cd and Pb in soil, with R2 values of 84.2% and 67.6%, respectively. The environmental risk assessment indicated that the leaching risk in 93.8%-96.1% of the sampling sites could be ignored, whereas a few sampling sites near factories with low pH may pose a risk to the groundwater environment. The mobility of heavy metals in soil and the distribution of pollution sources determined the leaching risk of heavy metals. The results provide a method and theoretical support for preventing the environmental risk of heavy metals in soil on a regional scale.
Key words: urbanized area      heavy metals      available contents      leaching risk      regression prediction     

快速的城市化带来经济发展的同时也导致了生态环境的恶化, 交通运输和工业活动产生的大量重金属在城市土壤中逐渐累积[1~3].由于土壤-植物-水体之间复杂的相互作用, 过量的重金属不仅会降低土壤的生态功能[4]和危害人体健康[5], 还可以通过淋溶作用迁移至地下水, 威胁饮用水安全[6, 7].土壤重金属下渗迁移的环境风险与重金属总量和其迁移性密切相关[8].由于污染源分布不均和土地利用斑块破碎化, 城市化区域土壤重金属含量及其迁移性都呈现出较大的空间变异性[9~11].研究城市化区域土壤重金属环境风险的分布规律和影响因素, 有助于指导区域土壤污染风险防控工作.

土壤重金属的迁移性受到土壤环境和重金属赋存形态的影响[12, 13].重金属有效态含量和固液分配系数(Kd)是评价土壤重金属迁移性的重要指标[14], 常用于植物吸收预测和风险评估[15~17].土壤重金属的有效态含量和Kd不仅与元素种类和含量有关, 还与土壤pH、有机质和质地有关[18~21].目前土壤重金属下渗迁移的环境风险研究主要集中于特定污染场地[22~25], 对于区域尺度上土壤重金属下渗迁移风险的分布规律及其影响因素研究较少.本文以长株潭地区为研究对象, 分析不同土地利用间土壤Cd和Pb有效态含量及其Kd的分布特征, 揭示影响土壤重金属迁移性的关键因素; 基于Kd评价研究区土壤重金属的潜在环境风险, 揭示其空间分布规律, 以期为区域土壤重金属污染风险防控提供理论支撑.

1 材料与方法 1.1 研究区概况与采样

长株潭城市群位于我国湖南省, 由长沙、株洲和湘潭这3个城市组成.该区域土地总面积28 069 km2, 根据城市统计年鉴数据2020年总人口数达到1 667.68万.长株潭地区森林和矿产资源丰富, 总地势东西较高, 中部较低, 以丘陵、盆地和平原为主, 适合城镇布局和发展.该区域经济发展要素密集, 冶金、钢铁、机械、汽车和纺织等工业发达, 导致区域土壤重金属明显累积[26].

本研究选取长株潭地区及其周边区域采集土壤样品, 涵盖郊区农田、城市绿地、工业区绿地和自然林地4种典型土地利用类型.在考虑点位空间均匀性的基础上, 共计布设130个土壤采样点位(郊区农田50个, 城市绿地49个, 工业区绿地16个, 自然林地15个).每个土壤样品由采样点周围100 m2的5个表层土(0~10 cm)均匀混合而成.土壤样品经自然风干与碾磨过筛后测定土壤pH、有机质、重金属总量和有效态含量.

1.2 土壤样品分析

土壤pH值用Mettler Toledo 420 pH计进行测定(土水比为1∶2.5); 有机质含量采用重铬酸钾氧化-比色法测定; 土壤Cd和Pb含量经HNO3-HF-HClO4微波法消解后用ICP-MS(电感耦合等离子体质谱仪Nex ION2000)测定[27].

1.3 土壤重金属有效态含量测定

土壤重金属有效态提取方法通常采用固液比为1∶10的0.01 mol·L-1 CaCl2提取法[28].称取5.00 g粒径 < 2 mm的土壤样品于100 mL离心管中, 用移液管加入50.0 mL 0.01 mol·L-1 CaCl2溶液, 放置于180 r·min-1的恒温振荡器中振荡提取2 h.振荡结束后在离心机中以1 000 r·min-1离心15 min, 并用0.45 μm滤膜过滤上清液于干净的锥形管中.通过ICP-MS测定提取液重金属浓度, 土壤Cd和Pb有效态含量计算过程见文献[29].

1.4 固液分配系数测定

固液分配系数Kd是平衡状态下重金属在土壤固相和液相中的浓度比[30], 采用固液比为1∶0.5的CaCl2提取方法可以测定非饱和水分条件下土壤孔隙水中重金属浓度[29], 基于该方法测定的Kd可以更好地反映土壤重金属的吸附解吸平衡状态, 常用于环境预测模型[6, 31].因此本研究基于CaCl2(固液比为1∶0.5)提取法测定土壤重金属的Kd.

CaCl2(固液比为1∶0.5)提取方法为:称取12.00 g粒径 < 2 mm的土壤样品于50 mL离心管中, 用移液管加入6.0 mL 0.01 mol·L-1 CaCl2溶液, 放置于180 r·min-1的恒温振荡器中振荡提取48 h.振荡结束后在离心机中以1 000 r·min-1离心15 min, 并用0.45 μm滤膜过滤上清液于干净的锥形管中.通过ICP-MS测定提取液重金属浓度.

计算公式:

(1)

式中, Kd为固液分配系数, L·kg-1; Ct为土壤中某重金属含量, μg·kg-1; ce为固液比为1∶0.5提取液中重金属浓度, μg·L-1; Vs为提取液体积, L; Msoil为土壤样品质量, kg.

1.5 环境风险

本研究采用USEPA[32]公布的土壤-地下水环境风险评价模型来评估重金属的下渗迁移风险.其中土壤渗滤液中重金属浓度cw, mg·L-1, 为[33]

(2)

式中, ρ为土壤容重, kg·L-1; θw为土壤孔隙度, 取默认值0.3.

土壤重金属下渗迁移的环境风险SGR为:

(3)

式中, cR为地下水中重金属浓度限值, mg·L-1, 参照《地下水质量标准》(GB/T 14848-2017)中Ⅲ类水质量限值, Cd和Pb的参考值分别为0.005和0.01 mg·L-1.DF为稀释系数, 假设研究区域位于平地, 地下水深度一致, 取默认值10.SGR<1表示无风险, 1≤SGR<10表示轻度风险, 10≤SGR<100表示中风险, SGR≥100表示强风险.

1.6 统计分析

实验数据采用Excel 2010进行数据整理, 使用Spss 19.0统计软件完成正态分布检验、方差分析、相关性分析和多元逐步回归分析.利用ArcGIS 10.2进行空间统计分析和制图, 运用Sigmaplot 14.0绘制其余图表.

2 结果与讨论 2.1 土壤Cd和Pb总量、有效态含量和Kd分布特征

图 1(a)所示, 不同土地利用之间土壤ω(Cd)为:工业区绿地1.15 mg·kg-1、郊区农田0.79 mg·kg-1、自然林地0.52 mg·kg-1和城市绿地0.46mg·kg-1.土壤ω(Pb)为工业区绿地53.36 mg·kg-1、郊区农田54.16 mg·kg-1、自然林地46.97 mg·kg-1和城市绿地37.07mg·kg-1.不同土地利用间土壤重金属含量的差异与污染源有关, 工业区涉及的钢铁生产、金属冶炼和电镀等活动导致其土壤Cd和Pb含量升高[34, 35].其余土地利用类型中重金属污染排放源较少, 因此土壤Cd和Pb含量相对较低.

小写字母表示不同土地利用类型间均值的差异显著性, 相同字母表示差异不显著(P>0.05), 不同字母表示差异显著(P < 0.05) 图 1 不同土地利用类型土壤Cd和Pb总量、有效态含量和Kd分布特征 Fig. 1 Distribution of total contents, available contents, and Kd of Cd and Pb in soil with land uses

研究区土壤有效态ω(Cd)均值为21.74 μg·kg-1, 有效态ω(Pb)均值为60.06 μg·kg-1, Cd有效态含量普遍低于Pb.土壤重金属有效态含量大小总体呈现出:自然林地>郊区农田>城市绿地>工业区绿地[图 1(b)].自然林地和郊区农田土壤Cd有效态含量显著高于城市绿地和工业区绿地(P < 0.05).自然林地土壤Pb有效态含量显著高于其余土地利用类型(P < 0.05).自然林地土壤Cd和Pb总量均低于工业区绿地, 但其有效态含量较高, 主要是因为林地土壤呈酸性(pH=4.62), 较低的土壤pH值提高了重金属的有效性.

研究区土壤Cd的Kd均值为449.79 L·kg-1, Pb的Kd均值为27 604.07 L·kg-1, Cd的Kd普遍低于Pb的.不同土地利用之间土壤Cd和Pb的Kd也存在显著性差异(P < 0.05), 如图 1(c)所示.郊区农田土壤Cd和Pb的Kd均值分别为256.55 L·kg-1和34 331.60 L·kg-1, 城市绿地分别为585.10 L·kg-1和28 370.04 L·kg-1, 工业区绿地分别为989.57 L·kg-1和18 020.06 L·kg-1, 自然林地分别为15.11 L·kg-1和2 700.67 L·kg-1.工业区绿地、城市绿地和郊区农田土壤中Cd和Pb的Kd显著高于自然林地.Kd反映土壤重金属的迁移性, 林地土壤Kd最小, 说明其重金属迁移性最大.对于不同重金属, 仅比较有效态含量无法准确表征其迁移性, 如土壤Cd有效态含量普遍低于Pb[图 1(b)], 但Cd的Kd值更低[图 1(c)], 说明土壤Cd迁移性更高.

2.2 土壤Cd和Pb有效态含量和Kd影响因素分析

相关性分析结果表明(表 1), 土壤Cd有效态含量与pH呈极显著负相关(P < 0.01).土壤pH值较低时, 大量氢离子与Cd在土壤表面形成竞争吸附, 提高了Cd的有效态含量[36, 37].土壤Cd总量是决定Cd离子活性的重要因素[38], 重金属总量越高, 可提取的有效态含量越高.一般来说土壤有机质会增加土壤对Cd的吸附[39], 但相关性分析显示土壤有机质与Cd有效态含量呈正相关(P < 0.01).这是因为有机质与Cd总量呈正相关, 共线性效应造成了土壤有机质与Cd有效态含量之间的相关性.土壤Pb有效态含量只与土壤pH显著相关(P < 0.01), 与土壤有机质含量和Pb总量无显著相关性.由此可见, pH值是决定土壤Cd和Pb有效性的关键因素.

表 1 土壤Cd和Pb有效态含量及Kd与土壤性质的相关性分析1) Table 1 Correlation analysis of available Cd and Pb contents and Kd with soil properties

表 1所示, 土壤Cd的Kd与其有效态含量呈极显著负相关(P < 0.01), 与其总量和土壤pH呈极显著正相关(P < 0.01).类似地, 土壤Pb的Kd与其有效态含量呈极显著负相关(P < 0.01), 与土壤pH呈极显著正相关(P < 0.01).土壤有机质与Cd和Pb的Kd均无显著相关性(P>0.05).在复杂的土壤系统中, 有机质对土壤重金属吸附-解吸行为影响复杂, 这取决于有机物的组分与存在形式[40].大分子的有机质会增加腐殖质对阳离子的吸附量, 从而降低重金属的迁移性, 而与小分子有机酸络合的重金属会经溶解作用重新进入土壤溶液, 进而增加重金属的迁移性[41].因此土壤重金属的迁移性与土壤有机质含量无显著相关性, 主要受到土壤pH、重金属总量和有效态含量的影响.

2.3 土壤重金属Kd回归预测

土壤中重金属的Kd反映了其自身的迁移性, 在土壤重金属溶质运移模型中发挥重要作用[42], 是预测重金属下渗迁移速率和环境风险的关键参数[17, 43].有研究表明, Kd的测量值会随土壤与提取液的比例而波动[44].Chen等[45]研究发现, CaCl2(固液比为1∶0.5)测定的Kd值最能反映田间土壤非饱和水分条件下的吸附平衡状态, 更适合评估自然条件下重金属的迁移性.然而, 我国土壤重金属有效态含量的测定常采用饱和水分条件下的CaCl2(固液比为1∶10)提取方法[46].构建基于土壤性质、重金属总量和有效态含量的土壤重金属迁移回归预测模型, 可以为环境风险评估提供方法支撑.

表 2所示, 土壤重金属Kd的回归预测模型均达极显著水平(P < 0.001).土壤pH和Cd总量对Cd的Kd多元回归模型R2达到71.8%, 加入CaCl2(固液比为1∶10)提取测定的重金属有效态含量作为因变量后, R2提高到84.2%.土壤pH和Pb总量对Pb的Kd多元回归R2为61.0%, 加入有效态含量参数后, R2提高到67.6%.表明土壤重金属的迁移性主要受到土壤pH和重金属总量的影响.引入CaCl2(固液比为1∶10)测定的重金属有效态含量可以更为有效地预测土壤重金属迁移性.

表 2 土壤重金属Kd与影响因子的回归关系 Table 2 Regression relationship between the Kd values of heavy metalsin soil and influencing factors

2.4 区域土壤Cd和Pb环境风险评估

土壤重金属下渗迁移的环境风险等级如表 3所示.不同土地利用之间土壤Cd的环境风险SGRCd均值呈现出自然林地(0.83)>郊区农田(0.22)>城市绿地(0.13)>工业区绿地(0.04).研究区内超过97.7%的郊区农田、城市绿地和工业区绿地采样点处于无风险水平(SGRCd < 1), 有35.7%的林地采样点Cd环境风险处于轻度水平(SGRCd>1).土壤Pb的环境风险SGRPb均值呈现出自然林地(0.69)>城市绿地(0.06)>郊区农田(0.05)>工业区绿地(0.04).农田和工业区绿地土壤Pb均无环境风险(SGRPb < 1), 仅有21.4%的林地采样点处于轻度风险水平(SGRPb>1).环境风险的大小与土壤中重金属含量和Kd有关, 各土地利用之间土壤Cd和Pb含量仅相差1.0~2.5倍, 而其Kd值相差1.1~81.7倍.工业区绿地土壤重金属含量最高, 但其较高的土壤pH值(pH=7.01)降低了重金属的迁移性, 因此工业区土壤环境风险最小.此外, 土壤中Pb含量和其有效态含量均高于重金属Cd, 但其Kd较高, 迁移性较小, 因此土壤中Pb环境风险低于Cd.此外, Cd的地下水质量标准(0.005mg·L-1)低于Pb(0.01 mg·L-1), 由此可见, 土壤重金属环境风险主要受重金属Kd值和评价标准的影响.

表 3 不同土地利用类型土壤Cd和Pb环境风险评价结果 Table 3 Environmental risk assessment of Cd and Pb in soil with different land uses

图 2可知, 研究区土壤重金属下渗迁移的环境风险空间分布不均.SGRCd>2的3个采样点分别位于研究区北部和中南部, 其土壤ω(Cd)分别为0.78、0.94和1.75 mg·kg-1, Cd的Kd分别为1.26、3.31和4.35 L·kg-1.SGRPb>2的2个采样点均位于研究区中南部, 其土壤ω(Pb)分别为61.40和149.00 mg·kg-1, Pb的Kd分别为301.39和136.98 L·kg-1.这些点位相应土壤pH值在4.29~4.64之间, 都位于工厂附近, 重金属含量均高于平均水平[ω(Cd)均值为0.67 mg·kg-1, ω(Pb)均值为46.71 mg·kg-1], 并且Kd较低, 因此环境风险较高.除此之外, 同一采样点土壤Cd和Pb环境风险也存在差异.如Cd表现出轻度环境风险, 而Pb无环境风险, 主要是因为土壤Cd的Kd均值(449.79 L·kg-1)低于Pb的Kd均值(27 604.07 L·kg-1).由此可知, 土壤重金属的迁移性和污染源分布共同决定了重金属下渗迁移的环境风险.

图 2 土壤Cd和Pb环境风险空间分布 Fig. 2 Spatial distribution of environmental risks of Cd and Pb in soil

3 结论

(1) 长株潭地区土壤Cd和Pb有效态含量大小呈现出:自然林地>郊区农田>城市绿地>工业区绿地.研究区土壤Cd的Kd均值为449.79 L·kg-1, Pb的Kd均值为27 604.07 L·kg-1.不同功能区之间林地土壤重金属的Kd最小, 迁移性最强.

(2) 土壤Cd和Pb的有效态含量主要受到土壤pH的影响.土壤Cd和Pb的Kd主要受到土壤pH、重金属总量和有效态含量的影响, 其多元回归预测模型R2分别达到84.2%和67.6%.

(3) 土壤重金属的迁移性和污染源分布共同决定了重金属下渗迁移的环境风险.基于CaCl2(固液比为1∶0.5)测定的Kd可以较好地表征区域土壤重金属的下渗迁移风险.研究区93.8%~96.1%的采样点土壤Cd和Pb无下渗迁移风险, 少数靠近工厂且土壤pH较低的点位存在轻度的下渗迁移风险.土壤中Cd的迁移性高于Pb, 其环境风险更高.

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