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In this study, fly ash, blast furnace slag, desulfurization gypsum, sludge, straw, and sawdust were utilized as raw materials. These materials were mixed at varying ratios, and Solanum nigrum was selected as the experimental plant for indoor pot trials. Farmland soil and contaminated soil from a metal mining wasteland were employed as controls. Variance analysis and Mantel tests were employed to analyze the effects of substrate ratios on Solanum nigrum growth characteristics, physicochemical properties of reconstructed soil, and relationships between substrate materials. A minimum dataset(MDS)for soil quality evaluation and entropy-weighted TOPSIS were applied to identify optimal substrate ratios. The results demonstrated that reconstructed soils formed by different solid waste ratios exhibited loose textures and enhanced water retention. Organic matter content was measured within a range of 39.01~70.03g/kg. All solid waste-based reconstructed soils were found to support Solanum nigrum growth, with biomass ranging from 0.11 to 3.18g/pot. A minimum dataset for soil quality assessment was established based on four critical indicators: chlorophyll content, plant height, pH, and water stability of 0.5~1mm aggregates. Subsequently, the entropy-weighted TOPSIS model was applied to systematically evaluate the comprehensive quality of the reconstructed soils. The optimal combination ratio, identified as fly ash: blast furnace slag : desulfurization gypsum : sludge : straw at a mass ratio of 4:2:1:1:2, demonstrated superior performance in both plant growth and soil functionality.

, correspAuthors=Zhong-qiu ZHAO, 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=Zhen-ran MEI, Zhong-qiu ZHAO, Qiao YANG, Ying HE, Hang BAI, Meng-chao SHI), CN=ArticleExt(id=1241057222051033613, articleId=1241057217760260165, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=全固废材料土壤重构对土壤质量和龙葵生长的影响, columnId=1234106394572550190, journalTitle=中国环境科学, columnName=土壤污染与控制, runingTitle=null, highlight=null, articleAbstract=

以粉煤灰、高炉渣、脱硫石膏、污泥、稻草秸秆、锯末为原材料,按照不同配比混匀后选用龙葵为试验材料进行室内盆栽试验.以农田土壤和某金属矿区废弃地污染土壤为对照,采用方差分析和Mantel检验,分析不同配比下龙葵生长特性、重构土壤理化性质及不同基质材料对其影响关系,并通过土壤质量评价最小数据集和熵权TOPSIS综合评价法确定最优配比方案.结果表明:不同固废材料配比形成的重构土壤质地疏松,持水保墒能力强;有机质含量高,范围介于39.01~70.03g/kg之间;不同固废基重构土壤均能适应龙葵生长,生物量介于0.11~3.18g/pot;基于叶绿素含量、株高、pH值及0.5~1mm水稳性团聚体四项关键指标,构建了用于评价固废基重构土壤质量的最小数据集并通过熵权TOPSIS综合评价模型,对重构土壤的综合质量进行了系统分析,筛选出最佳固废组合配比方案,即粉煤灰、高炉渣、脱硫石膏、污泥和秸秆按4:2:1:1:2的质量比为最优组合.

, correspAuthors=赵中秋, authorNote=null, correspAuthorsNote=
* 责任作者,教授,
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梅振然(1999-),男,安徽亳州人,中国地质大学(北京)博士研究生,主要研究方向为矿山生态修复.发表论文2篇..

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梅振然(1999-),男,安徽亳州人,中国地质大学(北京)博士研究生,主要研究方向为矿山生态修复.发表论文2篇..

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梅振然(1999-),男,安徽亳州人,中国地质大学(北京)博士研究生,主要研究方向为矿山生态修复.发表论文2篇..

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Agriculture,Ecosystems & Environment2010136(1):16-27., articleTitle=Impact of fly ash incorporation in soil systems, refAbstract=null), Reference(id=1241057245123899477, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, doi=null, pmid=null, pmcid=null, year=2009, volume=28, issue=3, pageStart=139, pageEnd=163, url=null, language=null, rfNumber=[46], rfOrder=60, authorNames=Blanco-canquI H, Lal R, journalName=Critical Reviews in Plant Sciences, refType=null, unstructuredReference=Blanco-canquI HLal R. Crop Residue removal impacts on soil productivity and environmental quality[J]. Critical Reviews in Plant Sciences200928(3):139-163., articleTitle=Crop Residue removal impacts on soil productivity and environmental quality, refAbstract=null), Reference(id=1241057245207785563, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, doi=null, pmid=null, pmcid=null, year=2018, volume=38, issue=12, pageStart=4769, pageEnd=4778, url=null, language=null, rfNumber=[47], rfOrder=61, authorNames=陈莺燕, 刘文深, 丁铿博, journalName=环境科学学报, refType=null, unstructuredReference=陈莺燕,刘文深,丁铿博,等. 有机改良剂及生物炭对离子型稀土矿尾砂地生态修复的改良探究[J]. 环境科学学报201838(12):4769-4778., articleTitle=有机改良剂及生物炭对离子型稀土矿尾砂地生态修复的改良探究, refAbstract=null), Reference(id=1241057245329420385, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, doi=null, pmid=null, pmcid=null, year=2018, volume=38, issue=12, pageStart=4769, pageEnd=4778, url=null, language=null, rfNumber=[47], rfOrder=62, authorNames=Chen Y Y, Liu W S, Ding K B, journalName=Acta Scientiae Circumstantiae, refType=null, unstructuredReference=Chen Y YLiu W SDing K B,et al. Effects of organic amendments and biochar on ecological remediation of ionic rare earth mine tailings[J]. Acta Scientiae Circumstantiae201838(12):4769-4778., articleTitle=Effects of organic amendments and biochar on ecological remediation of ionic rare earth mine tailings, refAbstract=null), Reference(id=1241057245430083689, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, doi=null, pmid=null, pmcid=null, year=2007, volume=29, issue=1, pageStart=96, pageEnd=104, url=null, language=null, rfNumber=[48], rfOrder=63, authorNames=Cheng H F, Xu W P, Liu J L, journalName=Ecological Engineering, refType=null, unstructuredReference=Cheng H FXu W PLiu J L,et al. Application of composted sewage sludge(CSS)as a soil amendment for turfgrass growth[J]. 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Journal of Integrative Plant Biology201860(9):796-804., articleTitle=Unraveling salt stress signaling in plants, refAbstract=null)], funds=[Fund(id=1241057233056887284, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, awardId=2020YFC1807604, language=CN, fundingSource=国家重点研发计划项目(2020YFC1807604), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241057222323663404, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, xref=1., ext=[AuthorCompanyExt(id=1241057222332052015, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222323663404, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.School of Land Science and Technology, China University of Geosciences(Beijing), Beijing 100083, China), AuthorCompanyExt(id=1241057222340440623, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222323663404, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国地质大学(北京)土地科学技术学院,北京 100083)]), AuthorCompany(id=1241057222457881153, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, xref=2., ext=[AuthorCompanyExt(id=1241057222466269762, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222457881153, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China), AuthorCompanyExt(id=1241057222474658372, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222457881153, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.自然资源部土地整治重点实验室,北京 100035)]), AuthorCompany(id=1241057222717928028, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, xref=3., ext=[AuthorCompanyExt(id=1241057222722122334, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222717928028, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.Technology Innovation Center for Ecological Restoration in Mining Areas, Ministry of Natural Resources, Beijing 100035, China), AuthorCompanyExt(id=1241057222730510943, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222717928028, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.自然资源部矿区生态修复工程技术创新中心,北京 100035)]), AuthorCompany(id=1241057222864728690, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, xref=4., ext=[AuthorCompanyExt(id=1241057222868922996, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222864728690, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing 100035, China), AuthorCompanyExt(id=1241057222873117299, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, companyId=1241057222864728690, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.自然资源部国土整治中心,北京 100035)])], figs=[ArticleFig(id=1241057228627701864, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Fig.1, caption=Reconstructed soil chemical properties, figureFileSmall=6rBf9i/SQ+DS4jyZN3pPZw==, figureFileBig=0VYCrNazyQkeCBF4bj66Yg==, tableContent=null), ArticleFig(id=1241057228753530994, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=图1, caption=重构土壤化学性质

不同字母表示同组处理间土壤pH值和养分含量组成具有显著差异(P<0.05)

, figureFileSmall=6rBf9i/SQ+DS4jyZN3pPZw==, figureFileBig=0VYCrNazyQkeCBF4bj66Yg==, tableContent=null), ArticleFig(id=1241057230510944415, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Fig.2, caption=Correlation analysis of different substrate materials with soil physicochemical properties and plant growth factors, figureFileSmall=wxv1kgQjVUoDRdDt7eydEw==, figureFileBig=ApIdEUkoApIr3BceZursuw==, tableContent=null), ArticleFig(id=1241057230624190641, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=图2, caption=不同基质材料与土壤理化性质及植物生长因素相关性分析, figureFileSmall=wxv1kgQjVUoDRdDt7eydEw==, figureFileBig=ApIdEUkoApIr3BceZursuw==, tableContent=null), ArticleFig(id=1241057230762602690, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 1, caption=

Heavy metal content and physical and chemical properties of different materials

, figureFileSmall=null, figureFileBig=null, tableContent=
材料pH值MgOCaOAl2O3SiO2Fe2O3TCTNTKTP
(mg/kg)(%)
FA10.0312.00.5446.540.1412.044.990.2813.610.342.5910.0451.852.29
BFS8.955.840.0116.820.032.842.190.278.320.7430.500.920.150.22
DG8.434.661.4114.030.093.560.980.762.959.7034.9311.7735.700.46
SS7.5813.705.1242.100.5520.807.640.3786.6058.611.780.162.49
SA43.225.610.220.04
ST60.630.921.380.37
), ArticleFig(id=1241057230905209045, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表1, caption=

不同材料的重金属含量及理化性质

, figureFileSmall=null, figureFileBig=null, tableContent=
材料pH值MgOCaOAl2O3SiO2Fe2O3TCTNTKTP
(mg/kg)(%)
FA10.0312.00.5446.540.1412.044.990.2813.610.342.5910.0451.852.29
BFS8.955.840.0116.820.032.842.190.278.320.7430.500.920.150.22
DG8.434.661.4114.030.093.560.980.762.959.7034.9311.7735.700.46
SS7.5813.705.1242.100.5520.807.640.3786.6058.611.780.162.49
SA43.225.610.220.04
ST60.630.921.380.37
), ArticleFig(id=1241057231018455271, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 2, caption=

Mixed pot trial program

, figureFileSmall=null, figureFileBig=null, tableContent=
组别FABFSDGSSSAST
C15010102010
C24020102010
C33030102010
C42040102010
C51535202010
C62525202010
C73515202010
T15010101020
T24020101020
T33030101020
T42040101020
T51535201020
T62525201020
T73515201020
), ArticleFig(id=1241057231135895802, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表2, caption=

混合盆栽试验方案

, figureFileSmall=null, figureFileBig=null, tableContent=
组别FABFSDGSSSAST
C15010102010
C24020102010
C33030102010
C42040102010
C51535202010
C62525202010
C73515202010
T15010101020
T24020101020
T33030101020
T42040101020
T51535201020
T62525201020
T73515201020
), ArticleFig(id=1241057231270113549, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 3, caption=

Evaluation steps based on entropy weight TOPSIS method

, figureFileSmall=null, figureFileBig=null, tableContent=
步骤公式含义
(1)构建评价矩阵A=(xijm×nxij是初始矩阵中的值(i=1,…,mj=1,…,n
(2)数据标准化 xij是原矩阵的指标值;zi为标准化处理后的指标值.
(3)计算第项指标下第个方案的值占该指标的比重 计算第j项指标下第i个方案的值占该指标的比重Pij
(4)计算各项指标熵值 计算各项指标熵值Ej,当Pij=0时,Pijln Pij=0,
(5)计算各指标的权重 计算各指标的权重Wj
(6)构建评价指标加权规范化矩阵 W为熵权法构建的权重向量;Zij为第i个对象的第j个指标经加权规范化后的指标值
(7)利用TOPSIS法确定正、负理想解 Zj+Zj-分别表示第j个指标在第i个对象取得的最偏好方案值和最不偏好方案值
(8)使用欧式距离计算评价对象与正、负理想解的距离 Di+表示第j个指标与正理想解Zj+的距离,Di-表示第j个指标与负理想解Zj-的距离
(9)计算相对贴近度 式中相对贴近度Si表示所评价对象与理想状态的差距,其值介于0~1之间
), ArticleFig(id=1241057231370776860, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表3, caption=

基于熵权TOPSIS法的评价步骤

, figureFileSmall=null, figureFileBig=null, tableContent=
步骤公式含义
(1)构建评价矩阵A=(xijm×nxij是初始矩阵中的值(i=1,…,mj=1,…,n
(2)数据标准化 xij是原矩阵的指标值;zi为标准化处理后的指标值.
(3)计算第项指标下第个方案的值占该指标的比重 计算第j项指标下第i个方案的值占该指标的比重Pij
(4)计算各项指标熵值 计算各项指标熵值Ej,当Pij=0时,Pijln Pij=0,
(5)计算各指标的权重 计算各指标的权重Wj
(6)构建评价指标加权规范化矩阵 W为熵权法构建的权重向量;Zij为第i个对象的第j个指标经加权规范化后的指标值
(7)利用TOPSIS法确定正、负理想解 Zj+Zj-分别表示第j个指标在第i个对象取得的最偏好方案值和最不偏好方案值
(8)使用欧式距离计算评价对象与正、负理想解的距离 Di+表示第j个指标与正理想解Zj+的距离,Di-表示第j个指标与负理想解Zj-的距离
(9)计算相对贴近度 式中相对贴近度Si表示所评价对象与理想状态的差距,其值介于0~1之间
), ArticleFig(id=1241057231504994608, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 4, caption=

Reconstructed soil physical properties at different ratios

, figureFileSmall=null, figureFileBig=null, tableContent=
编号容重(g/cm3饱和含水量(%)毛管持水量(%)渗透性K10(mm/min)水稳性团聚体(%)
0.2~0.5mm0.5~1mm1~2mm2~5mm>5mm
CK1.41±0.04a29.40±0.28e15.79±0.28c0.71±0.04a6.90±0.19d5.94±0.20f1.26±0.05e0.94±0.04c1.76±0.05g
DBS1.50±0.02a28.25±1.91e16.28±0.48c0.14±0.01c12.25±0.59a12.55±0.52a13.45±0.78ab9.55±0.88b3.65±0.51g
T10.92±0.09b80.43±2.82bcd49.23±0.33ab0.17±0.03bc5.86±0.71e6.39±0.51ef14.32±1.18a19.11±0.69a40.10±2.07a
T20.95±0.04b83.66±2.82abc50.31±1.97ab0.20±0.01b5.88±0.58e7.04±0.22de11.83±0.44bc20.54±2.63a31.02±0.31d
T30.91±0.07b85.75±5.06ab51.64±1.06ab0.16±0.02bc6.53±0.13de8.56±0.65c10.72±1.63cd20.92±0.30a26.78±0.76e
T40.94±0.06b87.30±0.32a53.69±0.28a0.20±0.02b7.23±0.22bcd10.92±0.31b9.52±0.22d20.96±1.05a24.68±1.78f
T51.00±0.07b82.71±3.79abc53.92±2.36a0.22±0.03b7.14±0.09cd7.73±0.25cd10.61±0.82cd20.33±0.73a37.33±1.54b
T60.92±0.05b79.33±0.74cd49.33±1.29ab0.16±0.06bc7.74±0.47bc7.76±1.39cd11.12±1.82cd20.67±2.65a34.97±1.07c
T70.91±0.07b75.47±4.65d48.59±6.60b0.18±0.05bc7.98±0.23b7.47±0.19cd11.07±0.43cd20.76±0.28a27.09±1.06e
CK1.41±0.04a29.40±0.28d15.79±0.28e0.71±0.04a6.90±0.19g5.94±0.20e1.26±0.05f0.94±0.04e1.76±0.05g
DBS1.50±0.02a28.25±1.91d16.28±0.48e0.14±0.01bc12.25±0.59a12.55±0.52a13.45±0.78bc9.55±0.88d3.65±0.51f
C10.93±0.07b61.63±2.16abc40.59±0.78cd0.15±0.02bc9.36±0.39b8.84±0.29cd11.08±0.61e15.47±0.66c14.95±0.61cde
C20.88±0.05b62.33±0.48ab44.24±1.66ab0.12±0.02c8.92±0.27bc8.52±0.4cd12.47±0.61cd20.32±1.01ab15.93±0.48bc
C30.92±0.09b64.22±1.00a44.71±1.72ab0.13±0.01c7.92±0.30de8.47±0.82cd14.05±0.85b22.24±1.26a16.57±1.07b
C40.91±0.07b64.77±3.11a46.60±1.64a0.17±0.02b6.36±0.24g8.19±0.26d15.52±0.72a22.35±0.62a17.86±0.54a
C50.84±0.06b61.68±0.98abc43.29±0.28bc0.13±0.03c6.40±0.27g8.63±0.22cd11.78±0.47de19.13±2.67b15.56±0.89bcd
C60.82±0.04b59.71±0.31bc40.72±3.86cd0.14±0.01bc7.58±0.22ef9.18±0.70c14.14±0.30b19.41±0.71b14.34±0.31de
C70.86±0.03b58.47±3.75c39.09±1.14d0.14±0.01bc8.40±0.93cd11.24±0.50b15.35±0.50a22.40±0.31a14.15±1.15e
), ArticleFig(id=1241057231672766788, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表4, caption=

不同配比下重构土壤物理性质

, figureFileSmall=null, figureFileBig=null, tableContent=
编号容重(g/cm3饱和含水量(%)毛管持水量(%)渗透性K10(mm/min)水稳性团聚体(%)
0.2~0.5mm0.5~1mm1~2mm2~5mm>5mm
CK1.41±0.04a29.40±0.28e15.79±0.28c0.71±0.04a6.90±0.19d5.94±0.20f1.26±0.05e0.94±0.04c1.76±0.05g
DBS1.50±0.02a28.25±1.91e16.28±0.48c0.14±0.01c12.25±0.59a12.55±0.52a13.45±0.78ab9.55±0.88b3.65±0.51g
T10.92±0.09b80.43±2.82bcd49.23±0.33ab0.17±0.03bc5.86±0.71e6.39±0.51ef14.32±1.18a19.11±0.69a40.10±2.07a
T20.95±0.04b83.66±2.82abc50.31±1.97ab0.20±0.01b5.88±0.58e7.04±0.22de11.83±0.44bc20.54±2.63a31.02±0.31d
T30.91±0.07b85.75±5.06ab51.64±1.06ab0.16±0.02bc6.53±0.13de8.56±0.65c10.72±1.63cd20.92±0.30a26.78±0.76e
T40.94±0.06b87.30±0.32a53.69±0.28a0.20±0.02b7.23±0.22bcd10.92±0.31b9.52±0.22d20.96±1.05a24.68±1.78f
T51.00±0.07b82.71±3.79abc53.92±2.36a0.22±0.03b7.14±0.09cd7.73±0.25cd10.61±0.82cd20.33±0.73a37.33±1.54b
T60.92±0.05b79.33±0.74cd49.33±1.29ab0.16±0.06bc7.74±0.47bc7.76±1.39cd11.12±1.82cd20.67±2.65a34.97±1.07c
T70.91±0.07b75.47±4.65d48.59±6.60b0.18±0.05bc7.98±0.23b7.47±0.19cd11.07±0.43cd20.76±0.28a27.09±1.06e
CK1.41±0.04a29.40±0.28d15.79±0.28e0.71±0.04a6.90±0.19g5.94±0.20e1.26±0.05f0.94±0.04e1.76±0.05g
DBS1.50±0.02a28.25±1.91d16.28±0.48e0.14±0.01bc12.25±0.59a12.55±0.52a13.45±0.78bc9.55±0.88d3.65±0.51f
C10.93±0.07b61.63±2.16abc40.59±0.78cd0.15±0.02bc9.36±0.39b8.84±0.29cd11.08±0.61e15.47±0.66c14.95±0.61cde
C20.88±0.05b62.33±0.48ab44.24±1.66ab0.12±0.02c8.92±0.27bc8.52±0.4cd12.47±0.61cd20.32±1.01ab15.93±0.48bc
C30.92±0.09b64.22±1.00a44.71±1.72ab0.13±0.01c7.92±0.30de8.47±0.82cd14.05±0.85b22.24±1.26a16.57±1.07b
C40.91±0.07b64.77±3.11a46.60±1.64a0.17±0.02b6.36±0.24g8.19±0.26d15.52±0.72a22.35±0.62a17.86±0.54a
C50.84±0.06b61.68±0.98abc43.29±0.28bc0.13±0.03c6.40±0.27g8.63±0.22cd11.78±0.47de19.13±2.67b15.56±0.89bcd
C60.82±0.04b59.71±0.31bc40.72±3.86cd0.14±0.01bc7.58±0.22ef9.18±0.70c14.14±0.30b19.41±0.71b14.34±0.31de
C70.86±0.03b58.47±3.75c39.09±1.14d0.14±0.01bc8.40±0.93cd11.24±0.50b15.35±0.50a22.40±0.31a14.15±1.15e
), ArticleFig(id=1241057231777624405, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 5, caption=

Particle composition of reconstituted soil with different ratios

, figureFileSmall=null, figureFileBig=null, tableContent=
组别颗粒组成(%)土壤质地
0.05~2mm0.002~0.05mm<0.002mm
CK47.44±2.33a45.28±1.07d7.28±1.29e壤土
DBS7.06±0.08b51.58±0.24cd41.36±0.20a(砂)质黏土
T17.21±3.05b70.59±8.62ab22.20±8.55bcd粉(砂)壤土
T28.67±6.78b71.72±12.65ab19.61±6.10cd粉(砂)壤土
T38.50±2.42b73.72±7.33ab17.78±6.16cd粉(砂)壤土
T47.98±4.38b78.51±9.91a13.51±6.02de粉(砂)壤土
T56.38±2.53b69.58±2.38ab24.04±2.54bc粉(砂)质黏壤土
T612.11±3.15b61.36±6.24bc26.53±4.47bc粉(砂)壤土
T75.56±2.93b63.29±1.92bc31.15±1.62b粉(砂)壤土
CK47.44±2.33a45.28±1.07e7.28±1.29e壤土
DBS7.06±0.08b51.58±0.24de41.36±0.21a(砂)质黏土
C19.03±0.72b81.11±2.75a9.86±3.43de粉(砂)土
C28.58±1.82b74.31±8.36abc17.12±8.74cd粉(砂)壤土
C35.79±2.91b67.11±1.83c27.10±4.70bc粉(砂)壤土
C45.72±1.45b67.07±9.87c27.21±8.44bc粉(砂)壤土
C55.40±3.71b77.12±3.03ab17.48±6.63cd粉(砂)质黏壤土
C67.42±2.17b68.84±5.7bc23.74±4.46c粉(砂)壤土
C77.81±2.29b57.39±1.55d34.80±3.84ab粉(砂)壤土
), ArticleFig(id=1241057231895064936, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表5, caption=

不同配比下重构土壤的颗粒组成

, figureFileSmall=null, figureFileBig=null, tableContent=
组别颗粒组成(%)土壤质地
0.05~2mm0.002~0.05mm<0.002mm
CK47.44±2.33a45.28±1.07d7.28±1.29e壤土
DBS7.06±0.08b51.58±0.24cd41.36±0.20a(砂)质黏土
T17.21±3.05b70.59±8.62ab22.20±8.55bcd粉(砂)壤土
T28.67±6.78b71.72±12.65ab19.61±6.10cd粉(砂)壤土
T38.50±2.42b73.72±7.33ab17.78±6.16cd粉(砂)壤土
T47.98±4.38b78.51±9.91a13.51±6.02de粉(砂)壤土
T56.38±2.53b69.58±2.38ab24.04±2.54bc粉(砂)质黏壤土
T612.11±3.15b61.36±6.24bc26.53±4.47bc粉(砂)壤土
T75.56±2.93b63.29±1.92bc31.15±1.62b粉(砂)壤土
CK47.44±2.33a45.28±1.07e7.28±1.29e壤土
DBS7.06±0.08b51.58±0.24de41.36±0.21a(砂)质黏土
C19.03±0.72b81.11±2.75a9.86±3.43de粉(砂)土
C28.58±1.82b74.31±8.36abc17.12±8.74cd粉(砂)壤土
C35.79±2.91b67.11±1.83c27.10±4.70bc粉(砂)壤土
C45.72±1.45b67.07±9.87c27.21±8.44bc粉(砂)壤土
C55.40±3.71b77.12±3.03ab17.48±6.63cd粉(砂)质黏壤土
C67.42±2.17b68.84±5.7bc23.74±4.46c粉(砂)壤土
C77.81±2.29b57.39±1.55d34.80±3.84ab粉(砂)壤土
), ArticleFig(id=1241057232104780159, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 6, caption=

Growth indexes of Lobelia under different ratios

, figureFileSmall=null, figureFileBig=null, tableContent=
组别株高(cm)根长(cm)生物量(g)叶面积(cm2叶绿素(SPAD)CAT(U/g)SOD(U/g)POD(U/g)
CK66.85±1.65c11.03±0.49a1.86±0.41b38.88±2.82c35.96±0.79c124.32±10.26e637.80±41.3e98.21±9.9e
DBS0±0g0±0g0±0e0±0g0±0e0±0f0±0f0±0f
T125.63±3.17f2.71±0.36f1.19±0.04c10.61±1.59f25.81±2.52d132.11±12.15e881.41±52.44d316.62±4.57c
T279.27±1.92a8.16±0.63c3.11±0.22a63.06±2.05a39.21±0.36b179.11±16.57d963.25±78.67cd330.41±25.21bc
T344.82±3.41e5.42±0.45e1.56±0.06b32.39±1.61d34.44±1.69c236.09±14.38c1049.55±32.11abc376.26±28.51a
T474.34±3.38b9.55±0.48b3.18±0.39a54.15±2.62b45.89±1.79a288.98±27.10ab1111.80±92.79ab389.07±44.19a
T553.83±3.52d9.31±0.50b1.74±0.17b34.77±1.64d39.60±0.43b322.51±31.54a863.10±22.52d273.68±11.99d
T642.71±2.18e7.45±0.55c0.80±0.02d20.82±1.2e36.15±2.48c270.89±29.79b1030.78±56.76bc386.48±30.76a
T727.06±1.47f6.52±0.12d0.45±0.13d11.85±1.31f34.18±0.77c206.54±15.79cd1143.05±67.35a368.22±20.64ab
CK66.85±1.65a11.03±0.49a1.86±0.41a38.88±2.82a35.96±0.79a124.32±10.26d637.8±41.30c98.21±9.90d
DBS0±0g0±0f0±0d0±0f0±0e0±0e0±0d0±0e
C117.48±1.13e2.64±0.24e0.11±0.01d3.54±0.06e24.58±1.93d777.87±113.72a1036.43±39.68a412.82±45.20a
C218.86±1.65e3.43±0.38d0.18±0.03d5.81±0.15d25.43±0.57d746.66±50.77a986.96±68.21ab333.56±11.87b
C319.14±3.19e3.99±0.45cd0.25±0.03cd6.10±0.57d30.95±1.15c565.64±52.64b980.85±22.64ab310.37±17.15bc
C433.34±2.84c4.35±0.44c0.48±0.04bc13.16±1.45c31.82±1.41c532.87±62.58bc942.72±77.43b289.74±33.35c
C541.71±1.60b5.37±0.44b0.63±0.04b17.03±0.75b33.78±1.43b528.91±48.48bc998.6±62.37ab312.14±18.00bc
C623.77±1.96d4.26±0.58c0.25±0.01cd6.37±0.26d25.56±0.49d462.28±11.80c956.78±29.90ab405.75±24.50a
C713.57±1.96f2.46±0.11e0.14±0.01d3.59±0.34e24.15±1.00d609.73±30.61b940.59±40.06b415.17±12.75a
), ArticleFig(id=1241057232234803601, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表6, caption=

不同配比下龙葵生长指标

, figureFileSmall=null, figureFileBig=null, tableContent=
组别株高(cm)根长(cm)生物量(g)叶面积(cm2叶绿素(SPAD)CAT(U/g)SOD(U/g)POD(U/g)
CK66.85±1.65c11.03±0.49a1.86±0.41b38.88±2.82c35.96±0.79c124.32±10.26e637.80±41.3e98.21±9.9e
DBS0±0g0±0g0±0e0±0g0±0e0±0f0±0f0±0f
T125.63±3.17f2.71±0.36f1.19±0.04c10.61±1.59f25.81±2.52d132.11±12.15e881.41±52.44d316.62±4.57c
T279.27±1.92a8.16±0.63c3.11±0.22a63.06±2.05a39.21±0.36b179.11±16.57d963.25±78.67cd330.41±25.21bc
T344.82±3.41e5.42±0.45e1.56±0.06b32.39±1.61d34.44±1.69c236.09±14.38c1049.55±32.11abc376.26±28.51a
T474.34±3.38b9.55±0.48b3.18±0.39a54.15±2.62b45.89±1.79a288.98±27.10ab1111.80±92.79ab389.07±44.19a
T553.83±3.52d9.31±0.50b1.74±0.17b34.77±1.64d39.60±0.43b322.51±31.54a863.10±22.52d273.68±11.99d
T642.71±2.18e7.45±0.55c0.80±0.02d20.82±1.2e36.15±2.48c270.89±29.79b1030.78±56.76bc386.48±30.76a
T727.06±1.47f6.52±0.12d0.45±0.13d11.85±1.31f34.18±0.77c206.54±15.79cd1143.05±67.35a368.22±20.64ab
CK66.85±1.65a11.03±0.49a1.86±0.41a38.88±2.82a35.96±0.79a124.32±10.26d637.8±41.30c98.21±9.90d
DBS0±0g0±0f0±0d0±0f0±0e0±0e0±0d0±0e
C117.48±1.13e2.64±0.24e0.11±0.01d3.54±0.06e24.58±1.93d777.87±113.72a1036.43±39.68a412.82±45.20a
C218.86±1.65e3.43±0.38d0.18±0.03d5.81±0.15d25.43±0.57d746.66±50.77a986.96±68.21ab333.56±11.87b
C319.14±3.19e3.99±0.45cd0.25±0.03cd6.10±0.57d30.95±1.15c565.64±52.64b980.85±22.64ab310.37±17.15bc
C433.34±2.84c4.35±0.44c0.48±0.04bc13.16±1.45c31.82±1.41c532.87±62.58bc942.72±77.43b289.74±33.35c
C541.71±1.60b5.37±0.44b0.63±0.04b17.03±0.75b33.78±1.43b528.91±48.48bc998.6±62.37ab312.14±18.00bc
C623.77±1.96d4.26±0.58c0.25±0.01cd6.37±0.26d25.56±0.49d462.28±11.80c956.78±29.90ab405.75±24.50a
C713.57±1.96f2.46±0.11e0.14±0.01d3.59±0.34e24.15±1.00d609.73±30.61b940.59±40.06b415.17±12.75a
), ArticleFig(id=1241057232389992871, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 7, caption=

MDS and weight determination

, figureFileSmall=null, figureFileBig=null, tableContent=
指标组别主成分Norm值最小数据集熵值权重
1234
叶绿素10.9250.262-0.1110.1442.995进入0.9700.023
有机质10.923-0.1890.160-0.0372.950
水解氮10.9110.169-0.327-0.0732.939
毛管持水量10.819-0.4930.2100.0012.896
饱和含水率10.852-0.3460.340-0.0102.871
SOD10.829-0.349-0.3460.0782.809
根长10.6600.679-0.0140.1262.734
容重1-0.6250.6960.227-0.0342.703
速效钾10.6550.6400.152-0.1182.667
0.2~0.5mm1-0.815-0.1620.1140.2222.61
生物量10.6120.5610.3820.2722.504
>5mm10.727-0.2370.465-0.3582.497
株高20.6940.6240.1560.2372.747进入0.9270.493
2~5mm20.525-0.7730.1650.0962.627
POD20.655-0.591-0.2390.1652.606
叶面积20.6230.5940.3220.3112.567
渗透性20.0090.921-0.314-0.1042.465
1~2mm2-0.140-0.8700.235-0.0372.35
有效磷2-0.0190.813-0.4950.1002.263
pH值30.743-0.319-0.527-0.0382.605进入0.9620.258
CAT30.046-0.587-0.6770.2841.877
0.5~1mm4-0.520-0.3290.2670.6652.010进入0.9930.046
特征值10.1306.4712.3931.044
方差贡献率(%)46.04629.41210.8764.744
累计贡献率(%)46.04675.45886.33591.078
), ArticleFig(id=1241057232570347965, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表7, caption=

MDS及权重确定

, figureFileSmall=null, figureFileBig=null, tableContent=
指标组别主成分Norm值最小数据集熵值权重
1234
叶绿素10.9250.262-0.1110.1442.995进入0.9700.023
有机质10.923-0.1890.160-0.0372.950
水解氮10.9110.169-0.327-0.0732.939
毛管持水量10.819-0.4930.2100.0012.896
饱和含水率10.852-0.3460.340-0.0102.871
SOD10.829-0.349-0.3460.0782.809
根长10.6600.679-0.0140.1262.734
容重1-0.6250.6960.227-0.0342.703
速效钾10.6550.6400.152-0.1182.667
0.2~0.5mm1-0.815-0.1620.1140.2222.61
生物量10.6120.5610.3820.2722.504
>5mm10.727-0.2370.465-0.3582.497
株高20.6940.6240.1560.2372.747进入0.9270.493
2~5mm20.525-0.7730.1650.0962.627
POD20.655-0.591-0.2390.1652.606
叶面积20.6230.5940.3220.3112.567
渗透性20.0090.921-0.314-0.1042.465
1~2mm2-0.140-0.8700.235-0.0372.35
有效磷2-0.0190.813-0.4950.1002.263
pH值30.743-0.319-0.527-0.0382.605进入0.9620.258
CAT30.046-0.587-0.6770.2841.877
0.5~1mm4-0.520-0.3290.2670.6652.010进入0.9930.046
特征值10.1306.4712.3931.044
方差贡献率(%)46.04629.41210.8764.744
累计贡献率(%)46.04675.45886.33591.078
), ArticleFig(id=1241057232746508751, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=EN, label=Table 8, caption=

Evaluation results of reconfigured soil program with different ratios

, figureFileSmall=null, figureFileBig=null, tableContent=
组别正理想解距离D+负理想解距离D-相对接近度Si排序
T10.1690.1030.37910
T20.0340.2520.8811
T30.1070.1620.6015
T40.0490.2370.8283
T50.0880.1810.6724
T60.1180.1520.5636
T70.1640.110.4019
C10.1940.0810.29413
C20.1950.0770.28214
C30.1840.0960.34212
C40.1480.1210.4498
C50.1190.150.5597
C60.1740.0990.36211
C70.2080.0680.24615
CK0.040.2320.8522
DBS0.2670.0090.03116
), ArticleFig(id=1241057232901698017, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057217760260165, language=CN, label=表8, caption=

不同配比下重构土壤方案评价结果

, figureFileSmall=null, figureFileBig=null, tableContent=
组别正理想解距离D+负理想解距离D-相对接近度Si排序
T10.1690.1030.37910
T20.0340.2520.8811
T30.1070.1620.6015
T40.0490.2370.8283
T50.0880.1810.6724
T60.1180.1520.5636
T70.1640.110.4019
C10.1940.0810.29413
C20.1950.0770.28214
C30.1840.0960.34212
C40.1480.1210.4498
C50.1190.150.5597
C60.1740.0990.36211
C70.2080.0680.24615
CK0.040.2320.8522
DBS0.2670.0090.03116
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全固废材料土壤重构对土壤质量和龙葵生长的影响
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梅振然 1 , 赵中秋 1, 2, 3, * , 杨侨 2, 4 , 贺莹 1 , 柏航 1 , 史孟超 1
中国环境科学 | 土壤污染与控制 2025,45(5): 2608-2619
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中国环境科学 | 土壤污染与控制 2025, 45(5): 2608-2619
全固废材料土壤重构对土壤质量和龙葵生长的影响
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梅振然1 , 赵中秋1, 2, 3, * , 杨侨2, 4, 贺莹1, 柏航1, 史孟超1
作者信息
  • 1.中国地质大学(北京)土地科学技术学院,北京 100083
  • 2.自然资源部土地整治重点实验室,北京 100035
  • 3.自然资源部矿区生态修复工程技术创新中心,北京 100035
  • 4.自然资源部国土整治中心,北京 100035
  • 梅振然(1999-),男,安徽亳州人,中国地质大学(北京)博士研究生,主要研究方向为矿山生态修复.发表论文2篇..

通讯作者:

* 责任作者,教授,
Research on soil reconstruction and growth response of Solanum nigrum based on fully solid waste materials
Zhen-ran MEI1 , Zhong-qiu ZHAO1, 2, 3, * , Qiao YANG2, 4, Ying HE1, Hang BAI1, Meng-chao SHI1
Affiliations
  • 1.School of Land Science and Technology, China University of Geosciences(Beijing), Beijing 100083, China
  • 2.Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China
  • 3.Technology Innovation Center for Ecological Restoration in Mining Areas, Ministry of Natural Resources, Beijing 100035, China
  • 4.Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, Beijing 100035, China
出版时间: 2025-05-20
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以粉煤灰、高炉渣、脱硫石膏、污泥、稻草秸秆、锯末为原材料,按照不同配比混匀后选用龙葵为试验材料进行室内盆栽试验.以农田土壤和某金属矿区废弃地污染土壤为对照,采用方差分析和Mantel检验,分析不同配比下龙葵生长特性、重构土壤理化性质及不同基质材料对其影响关系,并通过土壤质量评价最小数据集和熵权TOPSIS综合评价法确定最优配比方案.结果表明:不同固废材料配比形成的重构土壤质地疏松,持水保墒能力强;有机质含量高,范围介于39.01~70.03g/kg之间;不同固废基重构土壤均能适应龙葵生长,生物量介于0.11~3.18g/pot;基于叶绿素含量、株高、pH值及0.5~1mm水稳性团聚体四项关键指标,构建了用于评价固废基重构土壤质量的最小数据集并通过熵权TOPSIS综合评价模型,对重构土壤的综合质量进行了系统分析,筛选出最佳固废组合配比方案,即粉煤灰、高炉渣、脱硫石膏、污泥和秸秆按4:2:1:1:2的质量比为最优组合.

废弃地生态修复  /  固体废弃物综合利用  /  土壤重构  /  综合评价体系

In this study, fly ash, blast furnace slag, desulfurization gypsum, sludge, straw, and sawdust were utilized as raw materials. These materials were mixed at varying ratios, and Solanum nigrum was selected as the experimental plant for indoor pot trials. Farmland soil and contaminated soil from a metal mining wasteland were employed as controls. Variance analysis and Mantel tests were employed to analyze the effects of substrate ratios on Solanum nigrum growth characteristics, physicochemical properties of reconstructed soil, and relationships between substrate materials. A minimum dataset(MDS)for soil quality evaluation and entropy-weighted TOPSIS were applied to identify optimal substrate ratios. The results demonstrated that reconstructed soils formed by different solid waste ratios exhibited loose textures and enhanced water retention. Organic matter content was measured within a range of 39.01~70.03g/kg. All solid waste-based reconstructed soils were found to support Solanum nigrum growth, with biomass ranging from 0.11 to 3.18g/pot. A minimum dataset for soil quality assessment was established based on four critical indicators: chlorophyll content, plant height, pH, and water stability of 0.5~1mm aggregates. Subsequently, the entropy-weighted TOPSIS model was applied to systematically evaluate the comprehensive quality of the reconstructed soils. The optimal combination ratio, identified as fly ash: blast furnace slag : desulfurization gypsum : sludge : straw at a mass ratio of 4:2:1:1:2, demonstrated superior performance in both plant growth and soil functionality.

ecological restoration of waste land  /  comprehensive utilization of solid waste  /  soil reconstruction  /  comprehensive evaluation system
梅振然, 赵中秋, 杨侨, 贺莹, 柏航, 史孟超. 全固废材料土壤重构对土壤质量和龙葵生长的影响. 中国环境科学, 2025 , 45 (5) : 2608 -2619 .
Zhen-ran MEI, Zhong-qiu ZHAO, Qiao YANG, Ying HE, Hang BAI, Meng-chao SHI. Research on soil reconstruction and growth response of Solanum nigrum based on fully solid waste materials[J]. China Environmental Science, 2025 , 45 (5) : 2608 -2619 .
土壤重构是土地复垦的核心,重构土壤质量直接决定土地复垦状况[1].表土是土壤重构过程中的首要选择,但矿区土壤发育不良等自然因素及采矿活动造成的排土场等废弃地导致许多矿区表土稀缺问题严重[2-3].我国矿区多位于山区,普遍存在表土资源短缺、生长基质贫瘠恶劣的问题,在表土稀缺矿区的土地复垦过程中,土壤重构问题最不容易解决,因此对于表土稀缺矿区土壤重构的实质在于人工构造并改良表层土壤,为植物定植提供先决条件.土壤重构过程中所用到的材料主要是开采前剥离的表土,但在没有足够的表土时,也会使用各类成土母质或固体废弃物,也称为“表土替代材料”或“新土源”等[4-6].近年来,随着固体废物产量的持续增加,高效、清洁的固体废物处置技术逐渐成为研究的热点领域.许多固体废弃物因具有良好的物理性质或富含养分及有机质而广泛用于土壤改良,如粉煤灰、污泥、秸秆等多元固废的定向配比可通过协同增效作用实现土壤理化性质与生态功能的同步优化[7-9].其作用机制包括通过有机-无机复合体形成改善土壤孔隙结构,增强保水保肥能力[10-11];利用碱性材料(如粉煤灰)中和酸性土壤,促进pH值中性化[12].在土壤重金属污染治理方面,粉煤灰、钢渣、污泥和秸秆等固体废弃物因具有丰富的孔隙结构和吸附特性也被广泛应用[13].此外也有研究表明利用矿山和其他废弃物制备土壤(Technosol)进行矿山生态修复,能抵消高达60%的二氧化碳排放[14].尽管已有研究证实了大宗固废如粉煤灰、污泥和秸秆等材料对土壤理化性质的改善作用,并在矿山废弃地的植被恢复和生态系统固碳中展现出显著成效,但目前大部分研究侧重于固废的土壤改良功能,在实际应用中仍面临成本高、效果不稳定等问题,而且对于固废基重构土壤的效果和机制研究仍显不足,特别是在重构土壤的改良效果与植物生长的相关性方面缺乏细致的分析和标准化评价.这种不足使得固废基重构土壤的生态修复潜力未能得到系统验证,也制约了其在更大范围内的推广应用.
因此本文针对矿山废弃地生态修复过程中表土严重破坏扰动、生长基质极端贫瘠恶劣等影响植物生长的主要限制因素,从大宗固体废弃物资源化利用出发,充分利用固体废弃物的成本低廉性、资源价值可利用性,根据自然土壤的理化性质,研究不同固体废物的搭配组合在土壤理化性质以及先锋植物的生物量、抗逆性等生物指标上与自然土壤的拟合度,探索不同基质材料对重构土壤理化性质和植物生长的相关性,并通过主成分分析、相关性分析筛选土壤质量评价最小数据集,通过熵权TOPSIS综合评价法确定最优配比方案.本文旨在降低矿区废弃地生态修复的经济和时间成本,同时解决粉煤灰、秸秆等工农业大宗固体废弃物堆置造成的环境问题,为如何将安全高效处理处置固体废弃物和低成本环境友好型解决表土稀缺问题提供更多新的选择.
试验材料包括粉煤灰(FA)、高炉渣(BFS)、脱硫石膏(DG)、杨树锯末(SA)、城市污泥(SS)和稻草秸秆(ST),其中粉煤灰、高炉渣和脱硫石膏来自略图精细化工(河北)有限公司;杨树锯末、稻草秸秆(以下简称锯末、秸秆)来自鱼台县佳垚农产品有限公司,经风干后用大型磨粉机磨碎至2mm粉末状备用;污泥来自北京某污泥处置分公司,经过50~60℃条件下条垛式堆肥处理后自然脱水,约25~30d有效去除病原体、寄生虫卵和杂草种子后腐熟成为干污泥.不同材料的重金属含量和理化性质见表1.试供土壤样本中,农用土壤(CK)采集自北京市顺义区某农用地0~20cm的耕层土壤,土壤质地为壤土;金属尾矿废弃地土壤(DBS)采集自广东省某金属矿区尾矿废弃地0~20cm土壤,土壤质地为黏土,其中As含量为1910.85mg/kg,Pb含量5080.5mg/kg,有机质含量较低,为8.75g/kg.土壤样本采集回来后自然风干,然后磨碎,过2mm筛备用.
龙葵种子选用山东寿光欣欣然园艺公司生产的紫黑色龙葵种子,其纯度≥98.0%,发芽率≥85%,水分≤7.0%.龙葵种子先经过10%H2O2溶液消毒20min,之后用去离子水冲洗3遍,然后温水浸泡12h,最后用湿毛巾包起来置于25℃以上催芽,待种子发芽后播种至重构土壤中.
试验于中国地质大学(北京)校内温室花房(109°47′05.04′E,39°32′59.21′N)内进行,整个试验周期为150d.按照不同配比进行盆栽实验,试验共14个处理,每个处理重复3次,配比如表2所示.选择内径为15cm,底径11.5cm,高度18cm的花盆,每个花盆共计装1kg材料,百分比按照质量换算.试验过程中,为确保配比的均匀度,采用的混合方式为:将各个材料依次称量倒在铺好的塑料布上,之后将材料自下而上翻动,重复多次使得材料混合均匀.选用农用土壤(CK)和金属矿废弃地土壤(DBS)进行对照实验.每个处理均设置3个重复,在每个盆在上进行编号处理,随机区组排列.混合均匀装盆后,定期浇水,经过干湿交替,老化培养.
选择龙葵作为实验植物,重构土壤老化60d后,开展龙葵盆栽试验.每盆放5粒催芽萌发种子,选择长势较好的1株幼苗进行培育.采用称重法进行水分管理,保证田间持水量的25%左右,龙葵生长周期为90d.
重构土壤土样利用100cm3体积的环刀采取,用于测定土壤容重、饱和含水量、毛管持水量及田间持水量.另分别采集两份土样,一部分土样风干后剔除杂物过2mm筛,用于分析重构土壤有机质、碱解氮、有效磷、速效钾;另一部分土样用于分析土壤颗粒组成和pH值.土壤颗粒组成采用MicrotracS3500激光粒度分析仪测定,土壤容重、饱和含水量、毛管持水量及渗透性采用环刀法测定,土壤水稳性团聚体采用湿筛法测定[15].重构土壤有机质采用重铬酸钾容量法测定,碱解氮采用碱解扩散法测定,有效磷采用NaHCO3浸提-钼锑抗比色法测定,速效钾采用NH4OAc浸提-火焰光度计法测定,土壤pH值采用pH计(水土比2.5:1)测定[16].
叶片的SPAD值采用SPAD-502型便携式叶绿素仪测定;株高采用直尺测量其自然高度;90d收获时用剪刀将出土点剪断,分为地上部和地下部.地上部和地下部取出后,用清水洗净表面,而后用去离子水冲洗,并用吸水纸吸干表面水分,测定鲜重.随后将植株样本放入烘箱,65℃烘干,室温下回潮,105℃杀青30min,调温至70℃,烘干至恒重,获得地上部分生物量.根系及叶片用水洗净后先扫描成TIF图像文件,然后用WinRHIZO软件处理,分析叶面积、根长等指标.采用试剂盒(南京建成生物工程研究所,南京,中国)测定植物超氧化物歧化酶(SOD)活性、过氧化物酶(POD)活性和过氧化氢酶活性(CAT).
对选取的指标进行主成分分析,选取特征值大于1的主成分,将在同一主成分上因子载荷大于0.5的指标归为一组.如果某种指标的因子载荷在不同的主成分中都大于0.5,则需对其进行相关性分析,将其归并到与其它指标相关性较低的一组.分组后,确定每组中指标之间的相关性,如果某种指标与该组中其它指标之间的相关系数都小于0.3,说明其它指标均不能代表该指标中所包含的土壤质量信息,将该指标从该组中分离出来独立形成一组.各组Norm值在最高总分值10%范围内的指标被选中,进一步对选中的指标进行相关分析,指标之间的相关系数大于0.5,选择Norm值最高的指标进入最小数据集(MDS),指标之间的相关系数小于0.3,将这些指标都选入MDS[17].
其中,Norm值越大,表示该指标对所有主成分的综合载荷越大,该指标承载的土壤质量信息就越大.Norm值的计算公式如下:
式中:Nik为第i个指标在特征值大于1的前k个主成分的Norm值;uik为第i个指标在第k个主成分上的因子载荷;ek为第k个主成分的特征值.
熵权法能够消除主观因素的影响,是一种根据评价指标反馈的信息量来确定指标权重的方法,熵值越小权重越大.TOPSIS模型是C.L.Hwang和K.Yoon于1981年首次提出,又叫做“逼近理想解排序法”其根据评价对象与理想化目标的接近程度进行排序,是一种距离综合评价方法[18].本研究运用熵权TOPSIS法对不同材料配比的重构土壤进行综合评价研究,具体步骤如表3.
试验数据利用Microsoft Excel 2021软件进行数据归纳整理和作图,采用SPSS软件进行主成分分析和单因素方差分析,不同处理间采用Duncan法检验各处理平均数在P<0.05水平的差异显著性,利用Pearson相关分析检验生物量与土壤性质指标间的相关性,用R 4.3.3做Mantel检验并制图.
不同重构土壤物理性质见表4.其中各材料配比处理容重在0.82~1.00g /cm3,与对照处理的农用地土壤(CK)和金属矿废弃地土壤(DBS)相比,不同材料配比下重构土壤的容重显著降低,其中C6处理容重最小,较CK处理下降了41.84%,但各组间土壤容重差异不显著.不同配比处理下重构土壤的饱和含水量和毛管持水量较CK组显著提高,分别提高98.88%~196.93%和147.56%~266.81%,其中T4处理的饱和含水量和T5处理的毛管持水量最高,较CK组分别提高196.93%和266.81%.当脱硫石膏质量比为10%和20%时,C组饱和含水量差异均不显著且当脱硫石膏质量比为10%,T组毛管持水量差异不显著.在土壤渗透性方面,重构土壤渗透性显著低于CK,但组内不同配比无显著差异.由此可见,以全固废材料重构土壤使得土壤容重显著降低,保水储水能力显著提高,能够为龙葵生长发育提供良好环境.
土壤团聚体作为土壤结构的基本单元,常被作为评价土壤抗蚀能力的重要指标,对土壤的孔隙性、持水性、渗透性和抗蚀性有极大影响,其稳定性是决定土壤抗侵蚀能力和退化速率的重要因素.不同配比的重构土壤水稳性团聚体含量显著高于对照组,其中1~2、2~5、>5mm的水稳性团聚体含量较对照组最为显著.同时,T、C组内>5mm的水稳性团聚体含量差异也较为显著,当脱硫石膏添加10%时,T组>5mm含量随高炉渣增加和粉煤灰的减少而显著降低,C组则呈相应增加趋势;当脱硫石膏添加20%时,T、C组>5mm含量随高炉渣增加和粉煤灰的减少而增加.此外,当脱硫石膏的比例为20%时,T组重构土壤0.5~1、1~2、2~5mm以及当脱硫石膏的比例为10%时,T组2~5mm和C组0.5~1mm含量差异均不显著.
通过分析不同配比下重构土壤的颗粒组成(表5)可知,除T5、C5外重构土壤基本以粉(砂)壤土为主,与农田土壤(CK)相比,0.05~0.002mm和<0.002mm的颗粒显著提高.这可能是因为重构土壤老化时间不足,秸秆、锯末未充分与其他无机材料反应,使得重构土壤样本过2mm筛时,秸秆、锯末和其他无机材料分离而造成的现象.T组中当脱硫石膏占比分别为10%和20%时,不同配比的重构土壤在各颗粒组成间均无显著差异.C组中,当脱硫石膏占比分别为10%和20%时,重构土壤的0.05~0.002和<0.002的颗粒占比分别随着高炉渣减少、粉煤灰的增加而对应的呈现出增加和减少的趋势;当脱硫石膏占比为20%时,则对应呈现减少和增加的趋势.
不同材料配比的重构土壤化学性质如图1所示.不同重构土壤的pH值在8.5~9.32之间,呈弱碱性,较对照组显著提高但各组间差异不显著.
在土壤养分方面,重构土壤养分含量显著优于尾矿库土壤(DBS);且T、C组配比的有机质均显著优于农田土壤(CK),其中T5组的有机质含量最高,相较于CK处理增加了133.98%,但在有效磷、碱解氮和速效钾含量上低于对照组CK.此外,T2、T3、T4处理在水解氮含量方面与CK无显著差异.T、C组内养分含量差异显著,当脱硫石膏占比分别为10%时,有机质、水解氮、有效磷、速效钾含量在各组内均呈现出随着高炉渣增加、粉煤灰的减少而呈现出增加的趋势;当脱硫石膏占比20%时,则相应呈现减少的趋势.
结果表明,以金属矿废弃地土壤为对照的处理(DBS)不能为龙葵生长提供必要条件,但不同固废材料配比的重构土壤均能够适应龙葵的生长,通过分析不同重构土壤对龙葵生长指标的影响(表6)可知,T2、T4处理的株高、叶面积和生物量指标显著优于CK处理,其中T2处理的株高和叶面积、T4处理的生物量达到最大值,较CK分别提高了18.58%、62.19%和41.51%.C组重构土壤龙葵的根长、株高、生物量、叶面积和叶绿素指标值均随着高炉渣的增加和粉煤灰的降低而增加,龙葵的抗逆性指标除C5、C6、C7的SOD指标差异不显著外,但CAT和POD指标随着高炉渣的增加和粉煤灰的降低而降低.此外,T组T1-T4的CAT、SOD、POD活性均随高炉渣比例增加而提高,这可能是高炉渣通过提供钙镁离子改善了土壤结构和矿物养分供给,从而减轻了污泥所带来的盐胁迫对植物的影响[19-20].这说明利用粉煤灰、高炉渣、脱硫石膏、污泥、秸秆或锯末6种材料混合得到的重构土壤能够优化土壤质量,增强植物抗氧化能力,但要求这些材料以一定的比例进行混合,从方差分析结果来看,重构土壤中的秸秆和脱硫石膏用量是影响龙葵生长状况的关键变量.从植物生物量来看,当粉煤灰、高炉渣、脱硫石膏、污泥、秸秆按4(2):2(4):1:1:2混合得到的重构土壤,较为适合龙葵生长.
将重构土壤材料按基质划分为无机材料(粉煤灰、高炉渣和脱硫石膏)和有机材料(污泥、锯末和秸秆)分别与重构土壤理化性质和植物生长因子进行Mantel检验,分析了重构土壤材料矩阵与土壤、植物因子矩阵的相关性,明确了影响土壤理化性质和植物生长的材料因子(图2).相关系数越大,Mantel检验的P值越小,说明材料对土壤理化性质和植物生长的影响越大.
图2所示,有机材料对重构土壤理化性质和植物生长的影响相较于无机材料更为显著,在重构土壤理化性质方面,有机材料对水解氮、有机质、容重、饱和含水量、毛管持水量、渗透性和>5mm的水稳性团聚体含量均显著相关;在植物生长指标方面,有机材料对植物生物量,CAT,根长和叶面积呈显著相关.土壤理化性质与植物生长指标相关性分析表明,在本项研究中重构土壤pH值、容重和2~5mm水稳性团聚体含量与植物生长的株高、根长和叶面积无显著性关系;同时,重构土壤、pH值、容重、2~5mm和0.5~1mm的水稳性团聚体重量与植物生物量无显著关系.
在进行主成分分析前进行KMO抽样Bartlett球形度检验,其中KMO=0.803>0.5,sig<0.01,说明可以基于选定的指标进行主成分分析.特征值大于1的4个主成分累积方差解释率为91.293%,方差解释率分别是44.829%,31.266%,10.416%,4.782%.证明在本次分析选取的主成分可解释原始理化指标的大部分信息,用于不同材料配比下重构土壤综合评价的结果是可行的.
依照前述方法,将22个土壤和植物指标分为4组,如表7所示,叶绿素、有机质、水解氮、毛管持水量、饱和含水率、SOD、根长、容重、速效钾、0.2~0.5mm、生物量、>5mm为第一组,株高、2~5mm、POD、叶面积、渗透性、1~2mm、有效磷为第二组,pH和CAT为第三组,0.5~1mm独立为第四组,进一步依照上述方法,第一组叶绿素、第二组株高、第三组pH值和第四组0.5~1mm指标进入MDS.这些指标中,叶绿素和株高是植物生长的重要指标,其中叶绿素是植物进行光合作用必要的催化剂,对植物抗氧化活性等具有重要影响;pH值和粒径0.5~1mm的水稳性大团聚体是评价土壤质量的重要指标,能够直接影响植物生长以及土壤结构、形状和肥力.
基于最小数据集筛选的结果,计算每个指标与正理想解和负理想解之间的欧式距离D+D-,以及与最优解的接近度Si,并按Si进行排序得到各配比方案的最终得分和排序(表8).在不同固废配比的重构土壤中,T组得分在0.379~0.881之间整体上高于C组0.246~0.559,其中T2、T4以及CK处理得分均大于0.8,T2得分略高于CK,T4次之,DBS处理分值最低仅为0.031.对于不同配比的重构土壤,当粉煤灰、高炉渣和脱硫石膏比例一定时,“污泥+秸秆”组合效果通常优于“污泥+锯末”,这表明秸秆在重构土壤结构形成,肥力释放和持水供水能力上更有效.同时,综合评价得分也从侧面验证了利用固体废弃物资源特性,按照不同比例配置重构土壤用于表土稀缺区生态修复具有一定可行性.结合重构土壤理化指标、龙葵生长数据以及不同配比方案的综合评价,结果表明T2处理能够形成稳定的土壤结构,为植物定植建立良好的土壤环境.
利用不同固体废弃物配比重构土壤的关键是研究不同配比下的土壤理化性质与自然土壤的拟合度从而寻找最佳配比.由于质地、结构、养分含量和矿物特征等方面的差异,粉煤灰、高炉渣、脱硫石膏、污泥、秸秆和锯末在土壤养分和水土保持方面具有不同的特性.已有研究表明粉煤灰、高炉渣和脱硫石膏作为土壤改良材料,能够通过提供矿物养分、调节土壤酸碱性、改善结构和保水性等方式促进植物生长和改善土壤质量[2125].已有研究表明粉煤灰、高炉渣和石膏的协同作用能显著提高基质的抗压强度,其中高炉渣通过钙化作用增强了土壤的结构稳定性,粉煤灰则通过促进硅酸盐凝胶的快速形成增强土壤强度[26].此外,上述无机材料均具有活性吸附表面,能够通过表面吸附的方式固化水体或土壤中的重金属[27-29].但也有研究指出粉煤灰等无机材料中可能含有潜在的有毒污染物,可能会对土壤健康和植物生长产生有害影响,因此确定粉煤灰等无机材料中固有污染物的水平对于评估其作为土壤改良剂的适用性至关重要[30].污泥、秸秆和锯末作为有机废弃物,含有丰富的有机质和养分,可改善土壤的结构和保水性,提高土壤的肥力;同时秸秆和锯末具有较高的孔隙率,与无机材料的混合有助于改善土壤的通气性和水分保持能力[31-32].因此,基于不同固体废弃物之间相补的特性,如将粉煤灰与污泥混合应用可以兼顾土壤的无机成分和有机质含量并降低金属溶解度进一步降低植物体内的金属含量[33];秸秆和锯末的添加则可以提高土壤的有机质含量,改善土壤的通透性和保水性[34].本研究通过对不同固废的合理搭配和混合利用,形成了更为综合有效的重构土壤基质,为矿区废弃地的生态修复提供了可行性和新思路.
本研究中基于不同材料配制的重构土壤均能够促进植物生长,但在土壤理化性质和植物生长指标方面差异显著.有机质以及氮、磷、钾等矿物质元素是植物生长的必要条件,本研究中重构土壤有机质和速效氮含量均达到较高水平,这可能是由于秸秆和锯末的分解使重构土壤富集有机质[35].试验结果中T组有机质含量高于C组,这种差异可能与秸秆和锯末中纤维素和木质素的分解特性密切相关.秸秆中较高的纤维素含量更易被霉菌和放线菌分解,释放养分较快,从而促进有机质积累;而锯末中的木质素分解较慢,主要依赖白腐真菌等真菌作用,导致养分释放速率较低[36].
有研究认为在土壤中使用秸秆是改善土壤结构、土壤有机碳和作物产量的最佳策略[37],这与本研究结论一致,尤其在水稳性团聚体含量方面显著优于对照组,不过从试验过程来看这也有可能是因为重构土壤老化时间不够长,秸秆中的纤维素和锯末中的木质素未能充分降解,在重构土壤水稳性大团聚体颗粒上呈现出粉煤灰等无机材料充填在秸秆或锯末的混合结构中.但Guan等[38]的研究表明即使有机物中的不稳定有机化合物被部分分解,大团聚体中仍含有较高含量的SOC.此外,本研究中大团聚体(>1mm)显示出更高的有机质含量,这与之前的研究一致,这些研究表明大团聚体比微团聚体含有更多的有机碳[38-39],而且不易分解的有机物会缓慢且持久地促进团聚体稳定使得重构土壤在较长时间内保持较高的有机质含量[40].
土壤pH值是土壤酸度的重要参数,通常作为矿山土壤修复的质量指标.一些研究人员发现向土壤中添加粉煤灰可以逐渐增加酸性土壤的pH值[41],这与本研究结果类似,并且本研究中无机材料的比例变化并不会对重构土壤pH值产生显著影响.已有研究表明,粉煤灰等无机材料用于土壤改良时能够会改善土壤容重、质地和持水能力[42],但本研究中重构土壤渗透性低于对照组,一方面可能是因为无机材料的质量比高、比表面积大多孔性结构等,改变了重构土壤的微观孔径分布,堵塞了基质的毛孔,从而降低了渗透性,这与Wang等[43]的研究结果一致,另一方面可能是因为秸秆和锯末的体积占比高,在增加重构土壤持水能力的同时也降低了其渗透性[44].重构土壤的低容重是粉煤灰等无无机材料和秸秆等有机材料共同作用的结果[45-46].
植物生长(株高、根长、叶面积和干重)的变化能够反应表明植物生长的环境和养分的变化.本研究中,T组的植物生长显著优于C组,这可能是因为秸秆处理的土壤微生物较为活跃,对土壤有机质的分解程度更高,能够在较短时间内释放营养[47].在植物抗氧化酶活性表现中,研究发现龙葵重构土壤中的抗氧化酶活性高于对照组.这可能是因为无机材料的使用,使得基质中微量元素过高,植物在收到逆境胁迫后,会引起它对其它胁迫的抗性增强.在以锯末充填的基质组中龙葵CAT活性显著高于以秸秆为充填的基质组,除秸秆和锯末材料的改变,可以推断污泥用量的增加是这一变化的重要原因.通常,污泥的盐度远远高于土壤或常规基质中的盐度,已有研究表明污泥回收到土壤中会随着土壤盐度的增加而显着抑制植物生长[19],Cheng等[48]人的研究也证实污泥中高浓度的可溶性盐对植物生长产生了有害的渗透胁迫.因此在植物体中,盐胁迫引发的离子胁迫和渗透胁迫会导致代谢失衡和ROS毒性积累,诱发氧化损伤并引起植物抗氧化酶基因表达的改变[49].植物抗氧化酶活性的变化表明,高炉渣、粉煤灰与污泥的合理配比能够有效改善土壤质量,为植物提供更稳定的生长环境,但需要控制污泥比例以避免盐胁迫过高.
本研究结果均来自室内盆栽试验,应当开展野外小范围修复试验,以研究最佳方案在野外是否适用.另外本研究并未研究重构土壤微生物群落结构、土壤酶活性等指标,在野外实验可以设置更长的时间跨度和更多的指标来反映重构土壤的理化性质及养分保持能力,如测定不同提取态素以反映磷素流失情况.
4.1 本研究结果表明利用大宗廉价易得固废:粉煤灰、高炉渣、脱硫石膏、污泥、锯末和秸秆六种材料复合成不同配比的重构土壤的理化性质和养分含量能够适应植物生长,具有作为表土稀缺矿区生态修复表土替代物的可行性.
4.2 Mantel检验表明有机材料(污泥、锯末和秸秆)对重构土壤理化性质和植物生长的影响相较于无机材料(粉煤灰、高炉渣和脱硫石膏)更为显著.
4.3 根据熵权TOPSIS综合评价结果,综合指数Si主要为0.264~0.881.通过重要性值与模型评分排名相结合,确定粉煤灰、高炉渣、脱硫石膏、污泥和秸秆施用质量比为4:2:1:1:2是本研究的最佳方案.
  • 国家重点研发计划项目(2020YFC1807604)
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  • 接收时间:2024-10-11
  • 首发时间:2026-03-18
  • 出版时间:2025-05-20
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  • 收稿日期:2024-10-11
基金
国家重点研发计划项目(2020YFC1807604)
作者信息
    1.中国地质大学(北京)土地科学技术学院,北京 100083
    2.自然资源部土地整治重点实验室,北京 100035
    3.自然资源部矿区生态修复工程技术创新中心,北京 100035
    4.自然资源部国土整治中心,北京 100035

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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