Effects of Different Artificial Vegetation Communities on Characteristics of Heavy Metal Loss in Runoff of Lead Zinc Mine Wasteland

TAO Chenbin; ZHU Yuhang; CHEN Jianjun; YAN Kai; LI Yuan; LI Bo

doi:10.13870/j.cnki.stbcxb.2022.01.048

您当前的位置：

首页 >

文章列表页 >

Effects of Different Artificial Vegetation Communities on Characteristics of Heavy Metal Loss in Runoff of Lead Zinc Mine Wasteland

更新时间：2025-03-12

- Effects of Different Artificial Vegetation Communities on Characteristics of Heavy Metal Loss in Runoff of Lead Zinc Mine Wasteland
- Vol. 36, Issue 1, Pages: 375-383(2022)
- 作者机构：
  
  云南农业大学资源与环境学院,昆明,650201
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2022.01.048
  CLC： X53
- Published：2022
- 稿件说明：
移动端阅览
TAO Chenbin, ZHU Yuhang, CHEN Jianjun, et al. Effects of Different Artificial Vegetation Communities on Characteristics of Heavy Metal Loss in Runoff of Lead Zinc Mine Wasteland[J]. 2022, 36(1): 375-383.
DOI：

TAO Chenbin, ZHU Yuhang, CHEN Jianjun, et al. Effects of Different Artificial Vegetation Communities on Characteristics of Heavy Metal Loss in Runoff of Lead Zinc Mine Wasteland[J]. 2022, 36(1): 375-383. DOI： 10.13870/j.cnki.stbcxb.2022.01.048.

摘要

研究不同人工植被群落及土壤改良对铅锌矿废弃地径流重金属流失特征的影响

为矿区废弃地的生态恢复提供前期修复思路。采用径流小区试验

通过混合施加有机肥和钙肥对土壤进行改良

在自然降雨条件下

分别在铅锌矿废弃地原状土及改良土上构建不同人工植被群落(草、灌—草、乔—灌—草)

对地表径流的产生量与径流中泥沙、Cd、Pb、As的含量和流失量进行了分析研究。结果表明: (1)原状土下

乔—灌—草模式相较于草模式和灌—草模式

累计径流产生量分别减少11.3%和0.8%

同一人工植被群落

改良土相较于原状土累计径流产生量减少3.2%~18.8%;原状土下

灌—草模式相较于草模式、乔—灌—草模式

累计泥沙量分别减少28.9%

14.0%

同一人工植被群落

改良土相较于原状土累计泥沙量减少40.0%~63.3%。(2)原状土下

不同人工植被群落溶解态Cd、Pb、As累计流失量分别为2.7~7.2

104.3~295.1

1.4~5.4 mg/m2

改良土相较于原状土

不同人工植被群落溶解态Cd、Pb、As累计流失量分别减少47.7%~61.0%

43.8%~64.6%

43.8%~63.8%。(3)原状土下

不同人工植被群落颗粒态Cd、Pb、As累计流失量分别为2.5~9.0 g/m2

437.5~1 347.2

16.2~89.9 mg/m2; 改良土相较于原状土

不同人工植被群落颗粒态Cd、Pb、As累计流失量分别减少53.7%~72.0%

55.4%~65.8%

60.2%~71.1%。(4)颗粒态Cd、Pb、As流失量分别占总流失量的99.8%~99.9%

77.1%~84.1%

85.1%~96.7%。综上所述

人工植被群落越复杂

径流量、泥沙和重金属的流失量越低; 施加改良剂能进一步强化植被群落的截流功能; 重金属的流失主要以颗粒态为主。

Abstract

This paper studied the effects of different artificial vegetation communities and soil improvement on the characteristics of heavy metal loss in the runoff of lead-zinc mine wasteland

in order to provide early restoration ideas for the ecological restoration of mining wasteland. The runoff plot experiment was used to improve the soil by adding organic fertilizer and calcium fertilizer. Under the condition of natural rainfall

different artificial vegetation communities (grass

shrub grass and tree shrub grass) were constructed on the undisturbed soil and improved soil of lead-zinc mine wasteland respectively. The production of surface runoff

the content and loss of sediment

cadmium

lead and arsenic in runoff were analyzed and studied. The results showed that: (1) In undisturbed soil

the cumulative runoff decreased by 11.3% and 0.8% respectively compared to grass communities and irrigated grass communities. Compared with undisturbed soil

the cumulative runoff of improved soil decreased by 3.2%~18.8% in the same artificial vegetation community. In undisturbed soil

the accumulated sediment of shrub grass community decreased by 28.9% and 14.0% respectively compared with grass community and tree shrub grass community. Compared with undisturbed soil

the cumulative sediment of improved soil decreased by 40.0%~63.3% in the same artificial vegetation community. (2) In undisturbed soil

the cumulative losses of dissolved cadmium

lead and arsenic in different artificial vegetation communities were 2.7~7.2

104.3~295.1 and 1.4~5.4 mg / m2 respectively. Compared with the undisturbed soil

the cumulative losses of dissolved cadmium

lead and arsenic in different artificial vegetation communities decreased by 47.7%~61.0%

43.8%~64.6% and 43.8%~63.8% respectively. (3) In undisturbed soil

the cumulative losses of particulate cadmium

lead and arsenic in different artificial vegetation communities were 2.5~9.0 g/m2

437.5~1 347.2 and 16.2~89.9 mg/m2 respectively. Compared with the undisturbed soil

the cumulative loss of particulate cadmium

lead and arsenic in different artificial vegetation communities decreased by 53.7%~72.0%

55.4%~65.8% and 60.2%~71.1% respectively. (4) The losses of particulate cadmium

lead and arsenic accounted for 99.8%~99.9%

77.1%~84.1% and 85.1%~96.7% of the total loss respectively. In conclusion

the more complex the artificial vegetation community

the lower the runoff

sediment and heavy metal loss. Adding soil amendment could further strengthen the interception function of vegetation community. Under different plant communities

the loss of particulate heavy metals dominated.

关键词

Keywords

references

储彬彬, 罗立强. 南京栖霞山铅锌矿地区土壤重金属污染评价[J]. 岩矿测试, 2010, 29(1): 5-8, 13.

Briki M, Ji H B, Li C, et al. Characterization, distribution, and risk assessment of heavy metals in agricultural soil and products around mining and smelting areas of Hezhang, China [J]. Environmental Monitoring and Assessment, 2015, 187(12): 460-469.

骆永明, 滕应. 我国土壤污染的区域差异与分区治理修复策略[J]. 中国科学院院刊, 2018, 33(2): 145-152.

邹小冷, 祖艳群, 李元, 等. 云南某铅锌矿区周边农田土壤Cd、Pb分布特征及风险评价[J]. 农业环境科学学报, 2014, 33(11): 2143-2148.

Liu L H, Ouyang W, Wang Y D, et al. Heavy metal accumulation, geochemical fractions, and loadings in two agricultural watersheds with distinct climate conditions [J]. Journal of Hazardous Materials, 2020, 389: e122125.

Rothwell J J, Evans M G, Daniels S M, et al. Baseflow and stormflow metal concentrations in streams draining contaminated peat moorlands in the Peak District National Park (UK) [J]. Journal of Hydrology, 2007, 341(1): 90-104.

Silva E, Almeida S, Nunes M L, et al. Heavy metal pollution downstream the abandoned Coval da Mó mine (Portugal) and associated effects on epilithic diatom communities [J]. Science of the Total Environment, 2009, 407(21): 5620-5636.

Dai Y J, Dong Z, Li H L, et al. Effects of checkerboard barriers on the distribution of aeolian sandy soil particles and soil organic carbon [J]. Geomorphology, 2019, 338: 79-87.

Wang P, Sun Z H, Hu Y N, et al. Leaching of heavy metals from abandoned mine tailings brought by precipitation and the associated environmental impact [J]. Science of the Total Environment, 2019, 695(10): e133893.

张龙, 张云霞, 宋波, 等. 云南兰坪铅锌矿区优势植物重金属富集特性及应用潜力[J]. 环境科学, 2020, 41(9): 4210-4217.

李静, 俞天明, 周洁, 等. 铅锌矿区及周边土壤铅、锌、镉、铜的污染健康风险评价[J]. 环境科学, 2008, 29(8): 2327-2330.

房辉, 曹敏. 云南会泽废弃铅锌矿重金属污染评价[J]. 生态学杂志, 2009, 28(7): 1277-1283.

李航, 肖唐付, 双燕, 等. 云南金顶铅锌矿区水系沉积物中镉的地球化学分布及其环境质量[J]. 环境科学, 2008, 29(10): 2894-2898.

缪福俊, 孙浩, 陈玲, 等. 兰坪铅锌尾矿区土壤与自然发生的5种植物的研究[J]. 环境工程学报, 2011, 5(1): 189-194.

Festin E S, Tigabu M, Chileshe M N, et al. Progresses in restoration of post-mining landscape in Africa [J]. Journal of Forestry Research, 2019, 30(2): 381-396.

李博, 阎凯, 付登高, 等. 滇中地区4种覆被类型地表径流的氮磷流失特征[J]. 水土保持学报, 2016, 30(2): 50-55.

李琦, 时鹏, 杨倩, 等. 土地利用和侵蚀过程对土壤重金属分布的影响[J]. 北京师范大学学报(自然科学版), 2019, 55(1): 153-159.

韩煜, 赵伟, 张淇翔, 等. 不同植被恢复模式下矿山废弃地的恢复效果研究[J]. 水土保持研究, 2018, 25(1): 120-125.

张运红, 和爱玲, 杨占平, 等. 土壤改良剂对镉污染土壤小麦抗性, 光合特性及产量的影响[J]. 河南农业科学, 2018, 47(12): 57-63.

Hu X F, Huang X R, Zhao H H, et al. Possibility of using modified fly ash and organic fertilizers for remediation of heavy-metal-contaminated soils [J]. Journal of Cleaner Production, 2020, 284(7): e124713.

许剑臣, 李晔, 肖华锋, 等. 改良剂对重金属复合污染土壤的修复效果[J]. 环境工程学报, 2017, 11(12): 6511-6517.

章文波, 谢云, 刘宝元. 降雨侵蚀力研究进展[J]. 水土保持学报, 2002, 16(5): 43-46.

环境保护部. HJ 694-2014水质汞、砷、硒、铋和锑的测定原子荧光法[S]. 北京: 中国环境科学出版社, 2014: 1-9.

环境保护部. GB 7475-1987水质铜、锌、铅、镉的测定原子吸收分光光度法[S]. 北京: 中国环境科学出版社, 2014: 1-7.

生态环境部. HJ 168-2020环境监测分析方法标准制订技术导则[S]. 北京: 中国环境科学出版社, 2020: 1-18.

鲍士旦. 土壤农化分析[M]. 3版. 北京: 中国农业出版社, 2000: 370-390.

农业部. G/BT 2379-2009土壤质量有效态铅和镉的测定原子吸收法[S]. 北京: 中国国家标准化管理委员会, 2009: 1-4.

李元寿, 王根绪, 沈永平, 等. 长江源区不同植被覆盖下产流产沙效应初步研究[J]. 冰川冻土, 2005, 27(6): 869-875.

杨洋, 铁柏清, 张鹏, 等. 降雨和植被覆盖对土壤重金属流失的影响[J]. 水土保持学报, 2011, 25(1): 39-42, 46.

Baets S D, Poesen J, Gyssels G, et al. Effects of grass roots on the erodibility of topsoils during concentrated flow [J]. Geomorphology, 2006, 76(1): 54-67.

Anish K, Garey A F. Detachment characteristics of root-permeated soils from laboratory jet erosion tests [J]. Ecological Engineering the Journal of Ecotechnology, 2017, 100: 335-343.

Chen Z X, Guo M M, Wang W L. Variations in soil erosion resistance of gully head along a 25-year revegetation age on the Loess Plateau [J]. Water, 2020, 12(12): e3301.

胡绍颖, 于冰沁, 陈嫣, 等. 滨海盐碱地区的雨水花园介质土对水文特征的影响: 以上海临港新城为例[J]. 上海交通大学学报, 2019, 37(3): 61-67.

刘晓媛, 刘品祯, 杜启露, 等. 地质高背景区铅锌矿废弃地土壤重金属污染评价[J]. 有色金属, 2019, 17(2): 76-82.

梁涛, 王浩, 张秀梅, 等. 不同土地类型下重金属随暴雨径流迁移过程及速率对比[J]. 应用生态学报, 2003, 14(10): 1756-1760.

李贵, 童方平, 刘振华, 等. 植物原位阻截铅锌矿区土壤重金属效果和配置模式研究[J]. 中国农学通报, 2012, 28(31): 61-64.

孙健, 铁柏清, 周浩, 等. 不同改良剂对铅锌尾矿污染土壤中灯心草生长及重金属积累特性的影响[J]. 农业环境科学学报, 2006, 25(3): 637-643.

刘秀珍, 马志宏, 赵兴杰. 不同有机肥对镉污染土壤镉形态及小麦抗性的影响[J]. 水土保持学报, 2014, 28(3): 243-247, 252.

Liao J B, Wen Z W, Ru X, et al. Distribution and migration of heavy metals in soil and crops affected by acid mine drainage: Public health implications in Guangdong Province, China [J]. Ecotoxicology and Environmental Safety, 2016, 124: 460-469.

Views

909

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Effects of Coal Gangue and Microbial Inoculant Co-Amendment on Physicochemical Properties of Aeolian Sandy Soil and Alfalfa Growth

Progress and Prospects of Role and Multidimensional Mechanisms of Green Manure in Driving Soil Improvement in Arid Regions of Northwest China

Hydraulic-infiltration Characteristics and Proportion Optimization of Coconut Coir-type Ecological Conservation Substrate

Effects of Bacillus Subtilis on Water Movement and Water Stable Aggregate in Saline Alkali Soil

Vegetation Community and Soil Nutrient Characteristics of the Regions with Different Desertification Degrees Around the Jartai Saline Lake

Related Author

HAN Fengpeng

XIN Wenxuan

FENG Yuchao

YANG Jiejun

LI Meirui

LI Wangcheng

JIA Zhenjiang

HUANG Yahao

Related Institution

College of Resources and Environment， Northwest A&F University， Yangling

University of Chinese Academy of Sciences

Institute of Soil and Water Conservation， Chinese Academy of Sciences and Ministry of Water Resources， Yangling

Research Center of Soil and Water Conservation and Ecological Environment， Chinese Academy of Sciences and Ministry of Education， Yangling

Key Laboratory of the Internet of Water and Digital Water Governance of the Yellow River in Ningxia

⁰