Article(id=1240689591255102070, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1240689590315569990, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720540800000, receivedDateStr=2024-07-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773733049453, onlineDateStr=2026-03-17, pubDate=1739980800000, pubDateStr=2025-02-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773733049453, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773733049453, creator=13701087609, updateTime=1773733049453, updator=13701087609, issue=Issue{id=1240689590315569990, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='2', pageStart='593', pageEnd='1184', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773733049228, creator=13701087609, updateTime=1773733150042, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240690013239825123, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1240689590315569990, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240690013239825124, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1240689590315569990, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=829, endPage=840, ext={EN=ArticleExt(id=1240689592328843896, articleId=1240689591255102070, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Study on the pollutant migration interception performance of passive convergence-permeable reactive barrier, columnId=1234106386360103680, journalTitle=China Environmental Science, columnName=Water Pollution Control, runingTitle=null, highlight=null, articleAbstract=

Passive convergence-permeable reactive barrier (PC-PRB) is an eco-friendly and sustainable in-situ groundwater remediation technology. Based on mathematical models of groundwater flow and contaminant transport, this study innovatively proposed a grid self-adaptive refinement algorithm and developed a contaminant convection-diffusion numerical simulation software PRB-Trans. Utilizing PRB-Trans, the impact of the decompression convergence process on the contaminant capture performance of PC-PRB was analyzed. Under given simulation contaminant source conditions, compared with the continuous permeable reactive barrier (C-PRB), the required PRB length (LPRB) and PRB height (HPRB) of PC-PRB were reduced by 40.0% and 70.0%, respectively. The PC-PRB's planar and cross-sectional contaminant treatment efficiencies were increased by 102.9% and 348.3%, respectively. The results of the investigation of influencing factors show that with the increase of the drainage pipe length (Lp), the required LPRB and HPRB of PC-PRB decreased, but the reduction rate gradually decreased. Simultaneously, the PRB thickness (HPRB) increased significantly, leading to an increase in the PRB filler volume. To avoid this situation, it is recommended that the Lp/LPRB ratio is less than 2. In addition, due to the mixing and matching function of the decompression convergence wells and the uniform water distribution function of the buffer layer, PC-PRB can effectively solve the problems of low filler utilization rate and local breakthrough of C-PRB, demonstrating its application potential in the field of groundwater remediation.

, correspAuthors=Jie DING, Xiang-qin PENG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Kai-xuan ZHENG, Yi-hao LI, Fu-li LI, Ping CHEN, Jie-yong OU, Lei LEI, Yan-zhi CHEN, Wei WANG, Jie DING, Xiang-qin PENG, Na LIU, Yong WEN, Xiao-wen LIU, Hong-tao WANG), CN=ArticleExt(id=1240689595927556776, articleId=1240689591255102070, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=减压汇流式PRB污染物迁移阻控性能研究, columnId=1234106386565624579, journalTitle=中国环境科学, columnName=水污染与控制, runingTitle=null, highlight=null, articleAbstract=

减压汇流式渗透性反应墙(PC-PRB)是一种绿色可持续的地下水原位修复技术.本研究基于地下水运动和污染物迁移数学模型,创新性地提出网格自适应细化算法,并开发了基于此算法的污染物对流-弥散数值模拟软件PRB-Trans;利用PRB-Trans解析了减压汇流过程对PC-PRB污染物捕集性能的影响规律;在给定模拟污染源条件下,与连续式PRB(C-PRB)相比,PC-PRB所需的PRB长度LPRB和PRB高度HPRB分别减少40.0%和70.0%;PC-PRB平面和剖面污染物处理效率分别增加102.9%和348.3%.影响因素探究结果表明,随着导水管长度Lp的增加,PC-PRB所需的LPRBHPRB减少,但减少幅度逐渐降低,同时,PRB厚度HPRB显著增加,导致PRB填料体积增大.为避免此情况出现,建议Lp/LPRB比值小于2.此外,由于减压汇流井的混合调配功能和缓冲层的均匀布水功能,PC-PRB可有效解决C-PRB填料利用率低和局部击穿等问题,显示出其在地下水修复领域的应用潜力.

, correspAuthors=丁洁, 彭香琴, authorNote=null, correspAuthorsNote=
*责任作者,工程师,;
**工程师,
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=PW0lJqoQEKOrFd+Ua0ZK+Q==, magXml=Cmp6mwu8X8ZZ5YkPbg3Tng==, pdfUrl=null, pdf=Dp1JEgQeNHzaS1jK2YPc+w==, pdfFileSize=2710623, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=nLdbfE1Z8ltTnMu7dD8rLg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ejImGzZyzk1fiwZyHJ0y/g==, mapNumber=null, authorCompany=null, fund=null, authors=

郑凯旋(1995-),男,湖北咸宁人,助理研究员,博士,主要从事地下水污染模拟与控制研究.发表论文10余篇. .

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郑凯旋(1995-),男,湖北咸宁人,助理研究员,博士,主要从事地下水污染模拟与控制研究.发表论文10余篇. .

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郑凯旋(1995-),男,湖北咸宁人,助理研究员,博士,主要从事地下水污染模拟与控制研究.发表论文10余篇. .

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PC-PRB and C-PRB performance evaluation indicators and their evaluation methods

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评价指标定义单位估算方法
LPRBHPRB完全拦截污染羽流所需的最小PRB长度或高度mPRB-Trans溶质迁移模块
Q单位时间内进入PRB的地下水体积m3/dPRB-Trans区域水均衡模块
q单位时间内通过单位PRB长度或高度的地下水体积m2/dqh = Qh / LPRBqv = Qv / HPRB
u通过PRB的地下水实际流速m/duh = Qh / LPRBnuv = Qv / HPRBn
tPRB中污染物与活性填料的接触时间dth = TPRB / uhtv = TPRB / uv
C流入PRB的受污染地下水中氨氮浓度mg/LPRB-Trans溶质迁移模块
F单位时间内进入PRB的氨氮质量g/dFh = Ch / QhFv = Cv / Qv
f单位时间内进入单位PRB长度或高度的氨氮质量g/(m•d)fh = Fh / LPRBfv = Fv / HPRB
), ArticleFig(id=1240715198785450125, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1240689591255102070, language=CN, label=表1, caption=

PC-PRB和C-PRB性能评价指标及其评估方法

, figureFileSmall=null, figureFileBig=null, tableContent=
评价指标定义单位估算方法
LPRBHPRB完全拦截污染羽流所需的最小PRB长度或高度mPRB-Trans溶质迁移模块
Q单位时间内进入PRB的地下水体积m3/dPRB-Trans区域水均衡模块
q单位时间内通过单位PRB长度或高度的地下水体积m2/dqh = Qh / LPRBqv = Qv / HPRB
u通过PRB的地下水实际流速m/duh = Qh / LPRBnuv = Qv / HPRBn
tPRB中污染物与活性填料的接触时间dth = TPRB / uhtv = TPRB / uv
C流入PRB的受污染地下水中氨氮浓度mg/LPRB-Trans溶质迁移模块
F单位时间内进入PRB的氨氮质量g/dFh = Ch / QhFv = Cv / Qv
f单位时间内进入单位PRB长度或高度的氨氮质量g/(m•d)fh = Fh / LPRBfv = Fv / HPRB
), ArticleFig(id=1240715198865141903, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1240689591255102070, language=EN, label=Table 2, caption=

Comparison of PC-PRB and C-PRB planar performance indicators

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指标类型1区2区3区4区5区总和均值
LPRBC-PRB10.010.010.010.010.050.0-
PC-PRB6.06.06.06.06.030.0-
QhC-PRB0.120.110.110.110.120.55-
PC-PRB0.100.100.100.100.100.51-
qhC-PRB0.010.010.010.010.01-0.01
PC-PRB0.020.020.020.020.02-0.02
uhC-PRB0.030.030.030.030.03-0.03
PC-PRB0.040.040.040.040.04-0.04
thC-PRB100.68113.77114.57113.77100.68-108.29
PC-PRB70.4370.4370.4370.4370.43-70.43
ChC-PRB40.7954.8560.0055.4340.79-50.26
PC-PRB65.8365.8365.8365.8365.83-65.83
FhC-PRB4.865.796.285.854.8627.64-
PC-PRB6.736.736.736.736.7333.65-
fhC-PRB0.490.580.630.590.49-0.55
PC-PRB1.121.121.121.121.12-1.12
), ArticleFig(id=1240715198949027986, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1240689591255102070, language=CN, label=表2, caption=

PC-PRB和C-PRB平面性能指标对比表

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指标类型1区2区3区4区5区总和均值
LPRBC-PRB10.010.010.010.010.050.0-
PC-PRB6.06.06.06.06.030.0-
QhC-PRB0.120.110.110.110.120.55-
PC-PRB0.100.100.100.100.100.51-
qhC-PRB0.010.010.010.010.01-0.01
PC-PRB0.020.020.020.020.02-0.02
uhC-PRB0.030.030.030.030.03-0.03
PC-PRB0.040.040.040.040.04-0.04
thC-PRB100.68113.77114.57113.77100.68-108.29
PC-PRB70.4370.4370.4370.4370.43-70.43
ChC-PRB40.7954.8560.0055.4340.79-50.26
PC-PRB65.8365.8365.8365.8365.83-65.83
FhC-PRB4.865.796.285.854.8627.64-
PC-PRB6.736.736.736.736.7333.65-
fhC-PRB0.490.580.630.590.49-0.55
PC-PRB1.121.121.121.121.12-1.12
), ArticleFig(id=1240715199053885589, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1240689591255102070, language=EN, label=Table 3, caption=

Comparison of PC-PRB and C-PRB cross-sectional performance indicators

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指标类型1区2区3区4区总和均值
HPRBC-PRB5.05.05.05.020.0-
PC-PRB1.51.51.51.56.0-
QvC-PRB0.050.050.050.060.22-
PC-PRB0.050.050.050.050.19-
qvC-PRB0.010.010.010.01-0.01
PC-PRB0.030.030.030.03-0.03
uvC-PRB0.030.030.030.03-0.03
PC-PRB0.080.080.080.08-0.08
tvC-PRB115.08114.35111.9093.36-107.87
PC-PRB37.3337.3337.3337.33-37.33
CvC-PRB53.1548.8541.5432.28-43.95
PC-PRB68.1968.1968.1968.19-68.19
FvC-PRB2.772.562.232.079.78-
PC-PRB3.293.293.293.2913.15-
fvC-PRB0.550.510.450.42-0.49
PC-PRB2.192.192.192.19-2.19
), ArticleFig(id=1240715199150354583, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1240689591255102070, language=CN, label=表3, caption=

PC-PRB和C-PRB剖面性能指标对比表

, figureFileSmall=null, figureFileBig=null, tableContent=
指标类型1区2区3区4区总和均值
HPRBC-PRB5.05.05.05.020.0-
PC-PRB1.51.51.51.56.0-
QvC-PRB0.050.050.050.060.22-
PC-PRB0.050.050.050.050.19-
qvC-PRB0.010.010.010.01-0.01
PC-PRB0.030.030.030.03-0.03
uvC-PRB0.030.030.030.03-0.03
PC-PRB0.080.080.080.08-0.08
tvC-PRB115.08114.35111.9093.36-107.87
PC-PRB37.3337.3337.3337.33-37.33
CvC-PRB53.1548.8541.5432.28-43.95
PC-PRB68.1968.1968.1968.19-68.19
FvC-PRB2.772.562.232.079.78-
PC-PRB3.293.293.293.2913.15-
fvC-PRB0.550.510.450.42-0.49
PC-PRB2.192.192.192.19-2.19
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减压汇流式PRB污染物迁移阻控性能研究
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郑凯旋 1 , 李义豪 1 , 李富丽 2 , 陈平 3 , 区杰泳 1 , 雷蕾 1 , 陈岩贽 1 , 王炜 1 , 丁洁 1, * , 彭香琴 1, ** , 刘娜 2 , 温勇 1 , 刘晓文 1 , 王洪涛 4
中国环境科学 | 水污染与控制 2025,45(2): 829-840
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中国环境科学 | 水污染与控制 2025, 45(2): 829-840
减压汇流式PRB污染物迁移阻控性能研究
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郑凯旋1 , 李义豪1, 李富丽2, 陈平3, 区杰泳1, 雷蕾1, 陈岩贽1, 王炜1, 丁洁1, * , 彭香琴1, ** , 刘娜2, 温勇1, 刘晓文1, 王洪涛4
作者信息
  • 1.生态环境部华南环境科学研究所,国家环境保护环境污染健康风险评价重点实验室,广东 广州 510655
  • 2.暨南大学生命科学技术学院,广东 广州 510632
  • 3.广东工业大学环境科学与工程学院,广东 广州 510006
  • 4.清华大学环境学院,北京 100084
  • 郑凯旋(1995-),男,湖北咸宁人,助理研究员,博士,主要从事地下水污染模拟与控制研究.发表论文10余篇. .

通讯作者:

*责任作者,工程师,;
Study on the pollutant migration interception performance of passive convergence-permeable reactive barrier
Kai-xuan ZHENG1 , Yi-hao LI1, Fu-li LI2, Ping CHEN3, Jie-yong OU1, Lei LEI1, Yan-zhi CHEN1, Wei WANG1, Jie DING1, * , Xiang-qin PENG1, ** , Na LIU2, Yong WEN1, Xiao-wen LIU1, Hong-tao WANG4
Affiliations
  • 1.State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Science, Ministry of Ecological Environment, Guangzhou 510655, China
  • 2.College of Life Science and Technology, Jinan University, Guangzhou 510632, China
  • 3.School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • 4.School of Environment, Tsinghua University, Beijing 100084, China
出版时间: 2025-02-20
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减压汇流式渗透性反应墙(PC-PRB)是一种绿色可持续的地下水原位修复技术.本研究基于地下水运动和污染物迁移数学模型,创新性地提出网格自适应细化算法,并开发了基于此算法的污染物对流-弥散数值模拟软件PRB-Trans;利用PRB-Trans解析了减压汇流过程对PC-PRB污染物捕集性能的影响规律;在给定模拟污染源条件下,与连续式PRB(C-PRB)相比,PC-PRB所需的PRB长度LPRB和PRB高度HPRB分别减少40.0%和70.0%;PC-PRB平面和剖面污染物处理效率分别增加102.9%和348.3%.影响因素探究结果表明,随着导水管长度Lp的增加,PC-PRB所需的LPRBHPRB减少,但减少幅度逐渐降低,同时,PRB厚度HPRB显著增加,导致PRB填料体积增大.为避免此情况出现,建议Lp/LPRB比值小于2.此外,由于减压汇流井的混合调配功能和缓冲层的均匀布水功能,PC-PRB可有效解决C-PRB填料利用率低和局部击穿等问题,显示出其在地下水修复领域的应用潜力.

渗透性反应墙  /  减压汇流  /  污染物迁移阻控  /  数值模拟  /  影响因素分析

Passive convergence-permeable reactive barrier (PC-PRB) is an eco-friendly and sustainable in-situ groundwater remediation technology. Based on mathematical models of groundwater flow and contaminant transport, this study innovatively proposed a grid self-adaptive refinement algorithm and developed a contaminant convection-diffusion numerical simulation software PRB-Trans. Utilizing PRB-Trans, the impact of the decompression convergence process on the contaminant capture performance of PC-PRB was analyzed. Under given simulation contaminant source conditions, compared with the continuous permeable reactive barrier (C-PRB), the required PRB length (LPRB) and PRB height (HPRB) of PC-PRB were reduced by 40.0% and 70.0%, respectively. The PC-PRB's planar and cross-sectional contaminant treatment efficiencies were increased by 102.9% and 348.3%, respectively. The results of the investigation of influencing factors show that with the increase of the drainage pipe length (Lp), the required LPRB and HPRB of PC-PRB decreased, but the reduction rate gradually decreased. Simultaneously, the PRB thickness (HPRB) increased significantly, leading to an increase in the PRB filler volume. To avoid this situation, it is recommended that the Lp/LPRB ratio is less than 2. In addition, due to the mixing and matching function of the decompression convergence wells and the uniform water distribution function of the buffer layer, PC-PRB can effectively solve the problems of low filler utilization rate and local breakthrough of C-PRB, demonstrating its application potential in the field of groundwater remediation.

permeable reactive barrier  /  passive convergence  /  pollutant migration interception  /  numerical simulation  /  influencing factors analysis
郑凯旋, 李义豪, 李富丽, 陈平, 区杰泳, 雷蕾, 陈岩贽, 王炜, 丁洁, 彭香琴, 刘娜, 温勇, 刘晓文, 王洪涛. 减压汇流式PRB污染物迁移阻控性能研究. 中国环境科学, 2025 , 45 (2) : 829 -840 .
Kai-xuan ZHENG, Yi-hao LI, Fu-li LI, Ping CHEN, Jie-yong OU, Lei LEI, Yan-zhi CHEN, Wei WANG, Jie DING, Xiang-qin PENG, Na LIU, Yong WEN, Xiao-wen LIU, Hong-tao WANG. Study on the pollutant migration interception performance of passive convergence-permeable reactive barrier[J]. China Environmental Science, 2025 , 45 (2) : 829 -840 .
渗透性反应墙技术(PRB)的工作原理是在污染羽流动路径上设置含有特定活性填料的渗透性反应区,污染物与反应区内的填料接触时,通过吸附、沉淀或降解等作用实现污染物的去处或截留[1-4].与其它地下水修复技术相比,PRB技术具有无需外源动力和地面装置、运行寿命长、维护费用低等优点[5-8].典型的PRB结构类型主要包括连续式PRB(C-PRB)、漏斗导水门式PRB和非连续式PRB等[9-13].然而,在实际应用中,这些PRB结构类型面临着一系列挑战,例如开挖工程量大、填料利用率低、对地下水流场干扰大以及应用范围受限等[14-18].
减压汇流式渗透性反应墙技术(PC-PRB)是一种绿色可持续的地下水原位修复技术,可有效克服传统PRB技术存在的开挖工程量大、填料利用率低、对地层结构破坏严重和应用范围受限等局限性[19].PC-PRB技术通过在PRB上游适当位置布设若干井,利用导流管的引流减压效应调控井内水头,促使受污染地下水从四周向井中汇聚并导向PRB系统,从而达到阻控污染物迁移、缩小PRB规模和提高污染物处理效率的目的[19].PC-PRB技术由减压汇流系统和PRB系统共同构成.减压汇流系统包括减压汇流井、导流管和缓冲布水层. PRB系统内填充能够拦截或去除受污染地下水中污染物的活性填料.
在前期研究中,我们基于地下水渗流及流函数微分方程,开发了渗流模拟软件PRB-Flow,实现了PC-PRB渗流调控过程的精准模拟[20].同时,利用PRB-Flow探究了PC-PRB的渗流调控机制及其主要影响因素.研究结果表明,导流管的引流减压作用使得减压井内产生降深,促使井周围地下水在水头差的驱动下向井内汇聚,从而显著提升了PC-PRB的水力捕集性能[20].然而,减压汇流过程对PC-PRB污染物迁移阻控性能的影响规律有待进一步研究.本文基于地下水运动和溶质迁移数学模型,开发嵌入网格自动细分算法的污染物对流-弥散数值模拟软件PRB-Trans,利用PRB-Trans解析减压汇流过程对PC-PRB污染物迁移阻控性能的影响规律.本文研究结果以期为PC-PRB技术的工程应用提供参考.
基于二维地下水运动和溶质迁移数学模型,运用标准Galerkin有限单元法求解PC-PRB修复受污染地下水过程中水运动和污染物迁移问题的数值解,同时引入网格自适应细分算法,开发了非稳态多组分污染物对流-弥散数值模拟软件PRB-Trans.其假设条件和数学模型如下:
1)含水介质与参数:研究域G由非均质各向异性承压含水层或潜水含水层构成,水运动和污染物迁移参数已知,包括渗透系数K,含水层厚度b,承压含水层厚度M,弹性贮水系数S,给水度Sy,纵向弥散度αL和横向弥散度αT,有效孔隙度n,化学反应常数k等,各参数可以是常数,也可以是分片常数或者是空间坐标(xy)的已知函数.滞留因子Rd则由等温吸附模式确定,通常也是时间和空间变量的函数.
2)水运动和污染物迁移条件:平面二维稳定流或非稳定流;平面二维非稳定污染物迁移.
3)源汇条件:研究域中存在源汇的作用,强度为WM,可包含点源汇、线源汇和面源汇、河流补给、管道渗漏、降雨补给、越流补给、蒸发排泄等.源汇的作用可以是源(补给作用),也可以是汇(排泄作用).
4)初始条件:初始时刻全域G上水头H0xy)和污染物浓度C0xy)的分布已知.
5)边界条件:研究域的边界可以是第一类、第二类、第三类(仅溶质迁移问题)边界及其组合,也可以有内边界.对于给定边界类型,边界条件已知.
6)流体的密度保持不变.对于承压含水层,贮水量的改变通过孔隙度和含水层厚度的改变实现;贮水量由孔隙水量和弹性贮水量组成;对于潜水含水层,仅考虑可给出水(可运动水),忽略不可运动水的作用.
二维地下水运动问题的微分方程为:
式中:H为待求水头,m;E为贮水系数,承压水E=S,潜水E=SyS为弹性贮水系数;Sy为给水度;KxKy分别为xy方向上的渗透系数分量,m/d;b为含水层厚度,m,承压水b=M,为给定值,潜水b=Hzz为潜水含水层底板高度,m;WO为面汇排水强度,m/d,指单位时间单位面积的排水量,排水所含污染物浓度与含水层污染物浓度相同;WE为蒸发强度,m/d,指单位时间单位面积的蒸发量,WE中不含污染物;WI为面源注水强度,m/d,指单位时间单位面积的注水量,注水所含污染物浓度已知.
二维溶质迁移问题的微分方程为:
式中:I=WICIL为算子,即:
式中:C为待求污染物浓度,mg/L;Rd为滞留因子;n为有效孔隙度;DxDy分别为xy方向上的水动力弥散系数分量,m2/d;qxqy分别为xy方向上的单宽流量,m2/d;CI为注入水WI所含污染物浓度,mg/L;k为一级反应速率常数,d-1C0xy)为给定研究域上污染物初始浓度,mg/L.
和传统溶质迁移模型相比,PRB-Trans具有以下特点:(1)针对以对流为主的污染物迁移问题,提出网格自适应细分算法,通过自主搜索对流为主的网格并实施精细剖分(图1),保证单元的Peclet数小于2,从而克服了传统模型采用标准Galerkin方法和上游加权方法所带来的数值解的振动和数值弥散大等问题;(2)针对PRB活性填料对渗滤液中不同污染物去除机理的差异性,引入非线性等温模式和一级化学反应方程;(3)考虑到PRB活性填料的渗透性能和反应活性会随着运行时间有所下降,渗透系数、衰变常数和吸附常数等参数均可以设置为时间变量的函数.
利用PRB-Trans比较PC-PRB和C-PRB在平面含水层和剖面含水层中的污染物迁移阻控性能.PRB-Trans模型输入条件如下:
平面含水层长和宽分别为400m和200m(图2(a)),剖面含水层长和高分别为400m和50m(图2(b)).图2还展示了模拟区域的有限元网格剖分情况.剖分网格时应遵循越靠近PC-PRB,有限元网格尺寸越小的原则.
两个含水层均是均质性和各向同性的(即理想含水层),含水介质为粉砂,渗透系数和有效孔隙度分别为1m/d和0.46.
采用优先流模型来描述减压汇流过程对地下水流场和溶质运移的影响,即将其视为含水层中具有高渗透系数和高孔隙度的优先流动路径.减压汇流系统的渗透系数为80000m/d,有效孔隙度为1.00.PRB系统的渗透系数为含水介质的10倍,即10m/d,有效孔隙度为0.40.
平面含水层的南、北边界为隔水边界,东、西边界为定水头边界,其水头值分别为10m和6m,因此水力梯度为0.01;剖面含水层的顶部、底部边界为隔水边界,东、西边界为定水头边界,其水头值同样分别为10m和6m.
目标污染物为氨氮,初始时刻研究域上各点氨氮浓度为0mg/L.
第一类边界条件,即给定浓度边界.在平面含水层中,污染源为宽度40m的线性源,其中心坐标为(0m,200m);在剖面含水层中,污染源为深度15m的线性源,其中心坐标为(0m,42.5m);两个污染源在模拟时间内连续释放氨氮,浓度为200mg/L.
水头有限元方程和溶质迁移有限元方程SOR最大迭代次数均为900万次,收敛误差均为10-7.
为了评估和比较PC-PRB和C-PRB对污染物的迁移阻控性能,本研究共设有9个评价指标(表1),可分为3类:(1)PRB尺寸参数,即完全截获污染羽所需要的最小PRB长度(LPRB)和高度(HPRB);(2)水力捕集性能评价指标,包括通过PRB的地下水流量(Q),通过单位PRB长度/高度的地下水通量(q),通过PRB的地下水实际流速(u)和PRB水力停留时间(t);(3)污染物处理性能评价指标,包括流入PRB的污染物平均浓度(C)、通过PRB的污染物通量(F)和通过单位PRB长度或高度的污染物通量(f).
图3展示了PC-PRB和C-PRB在平面含水层中截获污染羽的对比情况.表2列出了两种类型PRB在各评价指标上的模拟值.结果表明,在处理同一污染羽(线源宽度为40m、浓度为200mg/L)时,采用PC-PRB所需的LPRB同比C-PRB减少20.0m,降幅为40.0%.这一结果表明,PC-PRB能够显著降低LPRB需求,实现对污染羽的集中高效处理.这是由于PC-PRB利用减压汇流效应,从水平方向上对污染羽进行汇聚,使得其宽度有效缩小[20].
与C-PRB相比,PC-PRB的Qh略有下降,降幅为7.8%.尽管PC-PRB的水力捕集能力略差于C-PRB,但是两者的污染羽迁移阻控效果相当.这是由于PC-PRB对污染羽具有捕集和迁移阻隔的双重阻控作用,即不仅可以有效收缩和集中处理污染羽,还可以通过被动降低减压井的水头以形成水力原位屏障,进而遏制污染羽向下游迁移的速度.PC-PRB与C-PRB的Qh差值ΔQh可以定量表征PC-PRB对污染羽的阻控作用大小.若ΔQh为负值,则表示PC-PRB对污染羽存在阻控作用,且ΔQh越小,表明阻控作用越强.PC-PRB的qh同比C-PRB增加53.7%,表明PC-PRB的水力捕集效率(即单位PRB长度水力捕集能力)明显优于C-PRB.这一显著提升主要归因于平面方向上的减压汇流效应,该效应使得减压井内水头下降,从而促使井周围的受污染地下水在水头差的驱动下向井中汇流,并且经由导流管和缓冲布水层流入PRB进行集中处理.另外,在图3(b)中,水头值为8.0m的等值线较图3(a)明显向井左侧弯曲,也进一步证实了减压井内水头低于其周围水头的现象.PC-PRB的减压汇流效应使得通过PRB的uh同比C-PRB增加53.7%,th相应的有所下降,th平均降低率为35.0%.与C-PRB相比,PC-PRB的ChFhfh均有所增加,增幅依次为31.0%、21.7%和102.9%.这一结果说明PC-PRB的污染物处理效率均明显优于C-PRB.
为了进一步比较PC-PRB和C-PRB各个性能评价指标在PRB横向方向上的分布情况,将PRB等分为5个区域,即1区、2区、3区、4区和5区.表2结果显示,在水力性能评价指标方面,C-PRB在不同PRB分区上的Qhqhuh均呈现出中间小两侧大的分布特征,而th恰好与之相反;而由于缓冲布水层的均匀布水作用,PC-PRB在不同PRB分区上的Qhqhuhth未见显著差异.在污染物处理性能评价指标方面,C-PRB在不同PRB分区上的ChFhfh则呈现出中间高两侧低的分布特征.这与污染羽本身污染物浓度分布不均(中心区域浓度高、周围区域浓度低)有关.而PC-PRB在各PRB分区上的ChFhfh则较为一致.这得益于减压汇流井的混合调配功能,即能够对含有不同污染物浓度的地下水进行均一化处理.C-PRB在PRB横向方向上流速和污染物浓度均存在不均匀现象,这可能造成PRB系统的局部击穿和活性填料利用率低等问题[20];而PC-PRB有助于缓解因污染羽污染物浓度分布不均导致的PRB填料利用率低和局部击穿等问题.此外,与C-PRB相比,PC-PRB中通过PRB的污染物浓度有所提升.
为了达到相同的处理目标,不可避免地需要增加PRB厚度.PRB厚度的计算方法有停留时间法和最大吸附法,两者的计算式如下[10]
式中:TPRB为PRB厚度,m;tR为污染物降低至目标浓度水平所需的停留时间,d;C0Cs分别为PRB进水和目标出水浓度,mg/L;k为一级反应速率常数,h-1;SF为安全系数,通常取3~5.
在PRB工程设计中,PRB厚度应由不同PRB分区计算出的最大PRB厚度值确定[21].基于式(4),以1.5mg/L为氨氮出水目标浓度(即地下水Ⅳ类水质标准),计算出PC-PRB所需PRB厚度是C-PRB的1.59倍,增幅为58.9%.对于PC-PRB,减压汇流井的混合调配过程使得污染羽中污染物的峰值浓度降低,从而降低污染物浓度达到目标水平所需的水力停留时间.这在一定程度上可以抵消PC-PRB污染物捕集能力增强造成PRB厚度增大的负面效果.
图4展示了PC-PRB和C-PRB在剖面含水层中截获污染羽的对比情况.表3列出了两种类型PRB在不同评价指标上的模拟值.结果表明,当处理线源深度为15m、浓度为200mg/L的污染羽时,采用PC-PRB所需的HPRB相较于C-PRB减少14.0m,降幅达到了70.0%.这表明PC-PRB同样能够从垂直方向上有效汇聚污染羽并缩小其深度,从而显著降低所需HPRB.虽然采用PC-PRB所需HPRB减少量相比于LPRB减少量较小,但其降幅却更为显著.
与C-PRB相比,PC-PRB的Qv下降13.3%,表明PC-PRB在剖面方向上对污染羽的阻控作用较平面方向上更强.虽然PC-PRB的总水力捕集能力低于C-PRB,但是两种类型PRB对污染羽的拦截效果相当.这是由于PC-PRB不仅可以通过减压汇流机制汇聚收缩污染羽,还可以通过被动降低减压汇流井的水头形成水力原位阻隔,进而遏制污染羽的绕流迁移速度,即PC-PRB具有污染羽阻隔效应.同样可以用ΔQv来定量表征PC-PRB对污染羽的阻隔作用大小.ΔQv与ΔQh相比降幅更大,说明PC-PRB在剖面方向上的污染羽阻隔能力更强.PC-PRB的qv同比C-PRB增长189.0%,表明PC-PRB的剖面水力捕集效率相比于C-PRB有显著提高.这同样归因于剖面方向上的减压汇流效应,该效应使得减压井内水头低于其底部,从而促使井底部的受污染地下水在水头差的驱动下向井中汇流,并且经由导流管和缓冲布水层流入PRB进行集中处理.图4(b)中水头值为8.0m的等值线较图4(a)明显向左弯曲,也进一步证明了减压井内水头低于周围水头.PC-PRB剖面方向上的减压汇流效应使得通过PRB的平均uv同比C-PRB增加189.0%,平均th降低65.4%.与C-PRB相比,PC-PRB的CvFvfv均有所增加,增幅依次为55.1%、34.5%和348.3%.这一结果说明PC-PRB在剖面方向上的污染物捕集能力和污染物捕集效率均显著高于C-PRB.
为了进一步比较两种类型PRB的各个评价指标在PRB垂直方向上的分布情况,将PRB等分为4个区域,即1区、2区、3区和4区.表3结果显示,在水力性能指标方面,C-PRB在不同PRB垂向分区上的Qvqvuv呈现上小下大的分布特征,而tv恰好与之相反.由于缓冲布水层的均匀布水作用,PC-PRB
在不同PRB垂向分区上的Qvqvuvtv没有显著差异.在污染物处理性能指标方面,C-PRB在不同PRB垂向分区上的CvFvfv则呈现出上大下小的分布规律.这同样和污染羽本身污染物浓度分布不均有关(垂直方向上靠近污染源的区域浓度较高,远离的区域浓度较低).
图5展示了Lp在10~60m范围内变化对PC-PRB平面污染物迁移阻控性能的影响规律.如图5(a)所示,随着Lp的增加,PC-PRB所需的LPRB呈现出减小的趋势,但减小幅度逐渐降低.在同一Lp水平下,当污染源的宽度或浓度增加时,PC-PRB完全拦截污染羽所需的LPRB也相应增大.这是因为污染源宽度越大,污染羽在横向方向上的扩展面积越大;而当污染源浓度增加时,一方面由于浓度梯度增加,溶质分子的扩散速率增加,使得污染羽在横向方向上变宽;另一方面由于污染物浓度增加,在PRB绕流量不变的情况下,绕流水体的浓度变高,因此要达到相同的污染物迁移阻控效果,LPRB必须增大.
图5(b)所示,在Lp逐渐增大的过程中,Qh呈现出先下降后上升的变化趋势,对于3种污染情景Ph,1、Ph,2和Ph,3Qh分别在Lp为40,30和30m时达到最小.这一现象形成的原因在于,PC-PRB水力捕集能力是决定其污染物迁移阻控能力的基础.前期研究结果表明,LPRBLp是影响PC-PRB平面水力性能的两个主要影响因素,且LPRB的影响程度大于Lp[20].在保持LPRB不变的前提下,PC-PRB水力捕集性能随着Lp的增加而提升.然而,在处理同一污染羽时,随着Lp的增加,所需LPRB随之减小,这又反过来会降低PC-PRB的水力捕集性能.当Lp不超过与Qh为最小值对应的Lp值时,LPRB随着Lp的增加而明显减少,导致PC-PRB的水力捕集性能下降;随后当Lp继续增加时,LPRB的减少幅度减缓,使得PC-PRB的水力捕集性能有所回升.此外,对于3种污染情景Ph,1、Ph,2和Ph,3,当Lp分别低于60,50和60m时,PC-PRB的捕集流量低于C-PRB,即ΔQh为负值,此时表明PC-PRB对污染羽存在阻控作用.当Lp分别为40,30和30m,即Lp与污染源宽度相等时,ΔQh达到最小值,此时PC-PRB对污染羽的阻控作用最强.当Lp继续增加时,ΔQh逐渐增大至正值,表明阻控作用逐渐减弱甚至消失.这是由于当Lp不大于与ΔQh为最小值对应的Lp值时,Lp的增加使得井内降深增大(图5(c)),并且此时LPRB尚且较大,故PC-PRB的阻控作用增强;当Lp继续增加时,此时降深的增幅减缓以及LPRB较小,因此导致阻控作用又逐渐减弱.
PC-PRB对污染羽的阻控作用大小变化可以通过减压井的降深进行解释.如图5(c)所示,随着Lp的增加,即使LPRB减小,减压井的降深亦逐渐升高.这一结果表明Lp对降深的影响显著大于LPRB.然而,PC-PRB对污染羽的阻控作用大小随着Lp的增加呈现先增后减的趋势.因此可以推断,PC-PRB对污染羽迁移的阻控作用大小不仅取决于水头降深,还与LPRB有密切关系.以降深均为0.25m为例,可以计算出对应的LPRB分别约为20,10和42m.结合图5(c)发现,LPRB越大,ΔQh越小.故在同一降深下,LPRB越大,PRB对污染羽的迁移阻控作用越强.
图5(d)图5(e)所示,随着Lp的增加,PC-PRB所处理的污染物浓度Ch和污染物通量Fh均呈现增加趋势.在同一污染情景下,Lp的增加意味着减压汇流井与污染源的距离缩短,这将导致井中汇聚的受污染地下水中的污染物浓度Ch升高.在同一Lp水平下,污染源的宽度或浓度增加时,PC-PRB所处理的污染物浓度C和污染物通量F也相应增大.与此同时,PC-PRB所需PRB厚度与C-PRB所需PRB厚度的比值TPC-PRB/TC-PRB随着Lp的增加而显著提升(见图5(f)),而LPRB减少幅度逐渐减缓.这将导致PC-PRB所需的填料体积显著提升,进而增加修复成本.以PC-PRB填料体积估算值的增幅小于50%为设计目标时,Lp/LPRB不超过2.
图6展示了Lp在10~60m范围内变化对PC-PRB剖面污染物迁移阻控性能的影响规律.如图6(a)所示,随着Lp的增加,HPRB呈现出减小的趋势,但减小幅度逐渐降低.这和平面情景中LPRB的变化趋势类似.在同一Lp水平下,当污染源的深度或浓度增加时,PC-PRB从剖面方向上完全拦截污染羽所需的HPRB也相应增大.如图6(b)所示,Qv随着Lp的增加呈现出先下降后上升的变化规律.对于3种污染情景Pv,1、Pv,2和Pv,3Qv均在Lp为30m时达到最小.这一现象形成的原因是,HPRBLp是影响PC-PRB剖面水力性能的两个主要影响因素,且HPRB的影响程度大于Lp.当Lp小于30m时,HPRBLp的增加而显著减少,导致PC-PRB的剖面水力性能下降;而当Lp继续增大时,HPRB的降低幅度逐渐减缓,使得PC-PRB的剖面水力性能有所回升.
此外,对于3种污染情景Pv,1、Pv,2和Pv,3,当Lp分别低于50,40和50m时,PC-PRB的剖面捕集流量低于C-PRB,即ΔQh为负值,此时表明PC-PRB对污染羽具有阻控作用.三者的ΔQvLp增加的变化规律与Qv一致,当Lp为30m时达到最小,表明此时PC-PRB从剖面方向上对污染羽的阻控作用最强.当Lp继续增加时,ΔQv逐渐增大至正值,表明阻控作用逐渐减弱甚至消失.这是由于当Lp不超过30m时,Lp的增加使得井内降深增大,并且此时HPRB尚且较大,故PC-PRB对污染羽的阻控作用增强;当Lp继续增加时,此时降深的增幅减缓以及HPRB较小,因此导致阻控作用逐渐减弱.如图6(c)所示,随着Lp的增加,即使HPRB减小,减压井的降深亦逐渐升高.这一结果表明Lp对降深的影响大于HPRB.
图6(d)图6(e)所示,随着Lp的增加,PC-PRB所处理的污染物浓度Cv和污染物通量Fv均呈现增加趋势.与此同时,PC-PRB所需PRB厚度与C-PRB所需PRB厚度的比值TPC-PRB/TC-PRB随着Lp的增加而显著提升(见图6(f)),而HPRB随着Lp的增加减少幅度减缓.这将导致PC-PRB所需的填料体积显著提升,进而增加修复成本.以PC-PRB填料体积估算值的增幅小于50%为设计目标时,Lp/HPRB不超过2.
图7展示了TDw在4~50m范围内变化对PC-PRB平面污染物迁移阻控性能的影响规律.如图7(a)所示,随着TDw的增加,PC-PRB所需的LPRB呈现先减少后增大的变化规律,但后续增加幅度不明显.对于3种污染情景Ph,1、Ph,2和Ph,3LPRB分别在Lp为30,20和30m时达到最小.这一现象产生的原因是,增加TDw扩大了减压汇流井的汇水面积,进而提高了减压汇流井的汇流量.但是由于PC-PRB后端处理能力有限,井中汇流量的增加会引起井内降深减少(图7(c)),导致井和其下游的水头差降低甚至可能超过下游水头,从而造成井内汇聚的受污染地下水直接向下游溢流的风险.因此,当TDw继续增大时,反而需要更大的LPRB拦截来自井中直接溢流的受污染地下水.
图7(b)所示,当TDw小于与LPRB为最小值所对应的TDw值时,TDw的增加对Qh影响不大,而当TDw大于该TDw值后,Qh随着TDw的增加而显著升高.这是由于在后述情形下,TDw的增加导致所需的LPRB增大,进而影响了Qh的变化趋势.对于3种污染情景Ph,1、Ph,2和Ph,3,当TDw分别低于40,30和40m时,PC-PRB的捕集流量低于C-PRB,即ΔQh为负值,此时表明PC-PRB对污染羽存在阻控作用.当TDw增加时,ΔQh逐渐增大至正值,表明阻控作用逐渐减弱甚至消失,这与减压井降深随着TDw的增加而逐渐减小有关(图7(c)).
图7(d)所示,随着TDw的增加,PC-PRB所处理的污染物浓度Ch呈现先增加后降低的变化规律.对于3种污染情景Ph,1、Ph,2和Ph,3Ch分别在TDw为12,12和20m时达到最大.当TDw小于与Ch为最大值所对应的TDw值时,更多含高浓度污染物的地下水汇入井中,导致Ch随着TDw的增加而增大;但是当TDw超过该TDw值后,减压井汇流面积的增加反而会将含低浓度污染物的地下水甚至未受污染的地下水汇入井中,从而造成Ch下降.PC-PRB所处理的污染物通量Fh随着TDw的增加而略有上升(图7(e)),这是由于尽管TDw增加导致后期Ch有所下降,但是Qh的增幅更为显著.此外,TPC-PRB/TC-PRB随着TDw的增加呈现先增大后减小的变化规律(如图7(f)所示).
图8展示了Hw在4~25m范围内变化对PC-PRB剖面污染物迁移阻控性能的影响规律.如图8(a)所示,Hw的变化对PC-PRB所需HPRB的影响相对较小.对于污染情景Pv,1和Ph,3,随着Hw的增加,HPRB呈现先减少后增加的变化规律,且在Hw为12m时达到最小.这一现象产生的原因是,增加Hw扩大了减压汇流井的汇水深度,进而提高了减压汇流井在剖面方向上的汇流量.井中汇流量的增加会引起井内降深减少(图8(c)),导致井内汇聚的受污染地下水直接向下游溢流的风险增大.因此,当Hw继续增大时,反而需要更大的HPRB拦截来自井中直接溢流的受污染地下水.对于污染情景Pv,2HPRB几乎不随Hw的增加而变化.在同一Hw水平下,污染源的深度或浓度越大,PC-PRB所需要的HPRB越大.
图8(b)所示,随着Hw的增加,Qv逐渐增大.对于污染情景Pv,1、Pv,2和Pv,3,当Hw分别低于40,12和30m时,PC-PRB的剖面捕集流量低于C-PRB,即ΔQv为负值,表明PC-PRB在剖面方向上对污染羽的迁移扩散存在阻控作用.当Hw增加时,ΔQv逐渐增大至正值,表明阻控作用逐渐减弱甚至消失,这与减压井的降深随着Hw的增加而逐渐减小有关(图8(c)).
图8(d)所示,随着Hw的增加,PC-PRB所处理的污染物浓度Cv呈现先增加后降低的变化规律.对于污染情景Pv,1和Pv,2Cv分别在Hw为8和6m时达到最大.对于污染情景Pv,3CvHw的增加呈现逐渐减小的变化趋势.当Hw小于与Cv为最大值所对应的Hw值时,更多含高浓度污染物的地下水汇入井中,导致Cv随着Hw的增加而增大;但是当Hw超过该Hw值后,减压井汇流面积的增加反而会将含低浓度污染物的地下水甚至未受污染的地下水汇入井中,从而造成Cv下降.此外,随着Hw的增加,PC-PRB所处理的污染物通量Fv变化不明显(如图8(e)所示),而TPC-PRB/TC-PRB呈现先增大后减小的变化规律(如图8(f)所示).
4.1 基于地下水运动和多组分污染物迁移数学模型,创新性地提出网格自适应细分算法,开发了污染物对流-弥散数值模拟软件PRB-Trans.网格自适应细分算法通过搜索对流为主的网格实施精细剖分,保证单元的Peclet数小于2,为克服传统数值方法在求解对流为主的污染物迁移问题时所面临的困难提供了一种有效解决方法.
4.2 PC-PRB污染物迁移阻控性能相较于C-PRB有显著提升.在给定模拟污染源条件下,与C-PRB相比,PC-PRB所需的LPRBHPRB分别减少40.0%和70.0%,PC-PRB平面和剖面污染物处理效率分别增加102.9%和348.3%.由于减压汇流井的混合调配功能和缓冲层的均匀布水功能,PC-PRB可有效解决C-PRB填料利用率低和局部击穿等问题.
4.3 当处理同一污染羽时,随着Lp的增加,PC-PRB所需的LPRBHPRB减少,但减少幅度逐渐降低,与此同时,PC-PRB所需的TPRB显著增加,导致PRB填料体积增大.为避免这一情况出现,建议Lp/LPRB小于2.
4.4 随着TDwHw的增加,PC-PRB所需的LPRBHPRB呈现先减后增的变化规律.当TDwHw分别超过LPRBHPRB时,井内受污染地下水直接向下游溢流的风险增大,此时PC-PRB反而需要更大的LPRBHPRB拦截受污染地下水.为降低溢流风险,建议TDw/LPRBHw/HPRB均小于1.
  • 国家重点研发计划项目(2018YFC1802300)
  • 中央级公益性科研院所基本科研业务专项(PM-zx703-202406-192)
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2025年第45卷第2期
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  • 接收时间:2024-07-10
  • 首发时间:2026-03-17
  • 出版时间:2025-02-20
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  • 收稿日期:2024-07-10
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国家重点研发计划项目(2018YFC1802300)
中央级公益性科研院所基本科研业务专项(PM-zx703-202406-192)
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    1.生态环境部华南环境科学研究所,国家环境保护环境污染健康风险评价重点实验室,广东 广州 510655
    2.暨南大学生命科学技术学院,广东 广州 510632
    3.广东工业大学环境科学与工程学院,广东 广州 510006
    4.清华大学环境学院,北京 100084

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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