Article(id=1149773883139645532, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2406119, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723651200000, receivedDateStr=2024-08-15, revisedDate=1736352000000, revisedDateStr=2025-01-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1752057055505, onlineDateStr=2025-07-09, pubDate=1746633600000, pubDateStr=2025-05-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752057055505, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752057055505, creator=13701087609, updateTime=1752057055505, updator=13701087609, issue=Issue{id=1149773869357167407, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='13', pageStart='5273', pageEnd='5704', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752057052207, creator=13701087609, updateTime=1768456769392, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218559268744253990, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218559268744253991, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149773869357167407, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=5285, endPage=5296, ext={EN=ArticleExt(id=1149773883433246817, articleId=1149773883139645532, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Review on the Impact of Coal Fly Ash Stockpiling on Water Environment Based on CiteSpace Visualization Analysis, columnId=1175113754401456498, journalTitle=Science Technology and Engineering, columnName=Surveies·Environmental and Safe Science, runingTitle=null, highlight=null, articleAbstract=

Long-term stockpiling of coal fly ash releases a large amount of toxic and hazardous substances, posing a threat to the soil and water environment. In order to have a comprehensive understanding of the research progress in this field, a bibliometric method was conducted to systematically and deeply visualize and analyze the relevant literature in CNKI and Web of Science databases from the period of database construction to 2023. The results show that the annual total number of publications in this field is generally on the rise. Among them, Chinese scientists have conducted a substantial amount of research in this field, accounting for the highest publication volume, which makes up 18.87% of the total, providing important scientific foundation for subsequent studies. The betweenness centrality of publications from the United States (0.51) is significantly higher than that of other countries, and its research results have greater international influence. The research hotspots focus on contaminants like heavy metals in coal fly ash, investigating their leaching and release patterns under various conditions, and revealing the environmental impacts of contaminants migration from coal fly ash landfills. Based on high-frequency keyword analysis, the composition of contaminants in coal fly ash and the types of contaminants potentially released into the water environment were examined. A systematic review and analysis of contaminants release mechanisms, release regularity, key influencing factors, and the migration regularity of mechanisms in environmental media were conducted. Future research should further focus on the release of heavy metals such as Pb, Cr, and Hg, trace elements like As, Se, and Mo, and specific mechanisms such as F-, Cl-, and $\mathrm{SO^{2-}_{4}}$, $\mathrm{PO^{3-}_{4}}$ during the coal fly ash stockpiling. Studies should explore the release characteristics of these mechanisms under complex environmental conditions, investigate whether synergistic or inhibitory mechanisms exist between various factors, and establish quantitative relationships between mechanisms indicators in the solid phase of coal fly ash and their release into water environment. This will provide a theoretical basis for scientifically evaluating the environmental impacts of coal fly ash and effectively preventing potential threats to water environment.

, correspAuthors=Qing-qi DIE, 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=Yu-fei YANG, Yong-qi LU, Ting-ting LIU, Si-qi XU, Rui-xiao HUANG, Qing-qi DIE), CN=ArticleExt(id=1149773906296398647, articleId=1149773883139645532, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于CiteSpace可视化分析粉煤灰堆存对水环境影响研究进展, columnId=1175113754757972339, journalTitle=科学技术与工程, columnName=综述·环境科学、安全科学, runingTitle=null, highlight=null, articleAbstract=

粉煤灰长期堆存会释放大量有毒有害物质,并对水环境构成威胁。为全面了解该领域的研究进展,采用文献计量学方法,系统并深入地对CNKI和Web of Science数据库中从建库至2023年间的相关文献进行了可视化分析。结果表明:该领域的年总发文量整体呈上升趋势,其中:中国科学家在该领域进行了大量研究工作,发文量最多,占总发文量的18.87%,为后续研究提供了重要科学依据,美国发文的中介中心性(0.51)明显高于其他国家,研究成果更具国际影响力;研究热点主要围绕粉煤灰中重金属等污染物,探究其在不同条件下的浸出、淋溶释放规律,揭示粉煤灰堆场污染物迁移带来的环境影响。基于高频关键词分析,探讨了粉煤灰污染物组成特征和可能释放到水环境中的污染物类型,系统梳理和分析了污染物的释放机制、规律和关键影响因素,以及污染物在环境介质中的迁移规律研究进展。未来研究应进一步关注粉煤灰堆存过程中Pb、Cr、Hg等重金属,As、Se、Mo等微量元素和F-、Cl-、$\mathrm{SO^{2-}_{4}}$、$\mathrm{PO^{3-}_{4}}$等特征污染物的释放问题,探究复杂环境影响下特征污染物的释放特性,并明确不同因素是否存在协同或抑制机制,建立粉煤灰固相中污染物指标与其释放进入水环境的指标间的定量关系,为科学评价粉煤灰环境影响提供理论基础,进而有效防范粉煤灰中污染物对水环境的潜在威胁。

, correspAuthors=迭庆杞, authorNote=null, correspAuthorsNote=
* 迭庆杞(1988—),男,汉族,河南南阳人,博士,副研究员。研究方向:固体废物环境管理和风险评估。E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=W/mr4P7cF2sS/PCfpzs0oA==, magXml=Ca2k1ECZaa1QLqVuwidfwg==, pdfUrl=null, pdf=aq+uho8/P3L/EQcppCRn8A==, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=vazUUkMd25ZTBopaVZ1LLw==, mapNumber=null, authorCompany=null, fund=null, authors=

杨玉飞(1977—),男,汉族,江西上饶人,博士,研究员。研究方向:危险废物环境风险控制和固体废物资源化环境安全性评价。E-mail:

, authorsList=杨玉飞, 卢永琦, 刘婷婷, 徐思琪, 黄瑞潇, 迭庆杞)}, authors=[Author(id=1176918236072391144, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=yangyf@craes.org.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1176918236168860139, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, authorId=1176918236072391144, language=EN, stringName=Yu-fei YANG, firstName=Yu-fei, middleName=null, lastName=YANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 Institute of Solid Waste Pollution Control Technology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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2 国家黄河流域生态保护和高质量发展联合研究中心, 北京 100012, bio={"content":"

杨玉飞(1977—),男,汉族,江西上饶人,博士,研究员。研究方向:危险废物环境风险控制和固体废物资源化环境安全性评价。E-mail:

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杨玉飞(1977—),男,汉族,江西上饶人,博士,研究员。研究方向:危险废物环境风险控制和固体废物资源化环境安全性评价。E-mail:

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Water Practice Technology, 2023, 18(5): 1255-1272., articleTitle=Groundwater contaminant transport modeling using MODFLOW and MT3DMS: a case study in Rajshahi City, refAbstract=null), Reference(id=1176918248177152674, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, doi=null, pmid=null, pmcid=null, year=2023, volume=42, issue=12, pageStart=4278, pageEnd=4291, url=null, language=null, rfNumber=[79], rfOrder=116, authorNames=戎艳青, 王林芳, 党晋华, journalName=环境化学, refType=null, unstructuredReference=戎艳青, 王林芳, 党晋华. 山西典型焦化场地特征污染物在非饱和带迁移规律及影响因素[J]. 环境化学, 2023, 42(12): 4278-4291., articleTitle=山西典型焦化场地特征污染物在非饱和带迁移规律及影响因素, refAbstract=null), Reference(id=1176918248244261539, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, doi=null, pmid=null, pmcid=null, year=2023, volume=42, issue=12, pageStart=4278, pageEnd=4291, url=null, language=null, rfNumber=[79], rfOrder=117, authorNames=Rong Yanqing, Wang Linfang, Dang Jinhua, journalName=Environmental Chemistry, refType=null, unstructuredReference=Rong Yanqing, Wang Linfang, Dang Jinhua. Study on the migration law and influencing factors of characteristic pollutants in the unsaturated zone of typical coking sites in Shanxi[J]. Environmental Chemistry, 2023, 42(12): 4278-4291., articleTitle=Study on the migration law and influencing factors of characteristic pollutants in the unsaturated zone of typical coking sites in Shanxi, refAbstract=null), Reference(id=1176918248315564708, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, doi=null, pmid=null, pmcid=null, year=2024, volume=45, issue=2, pageStart=48, pageEnd=52, url=null, language=null, rfNumber=[80], rfOrder=118, authorNames=王蓉, 梁雨蕾, 陈忠清, journalName=上海国土资源, refType=null, unstructuredReference=王蓉, 梁雨蕾, 陈忠清. 长三角地区环境水文地质特征及其对重金属污染物迁移的影响[J]. 上海国土资源, 2024, 45(2): 48-52., articleTitle=长三角地区环境水文地质特征及其对重金属污染物迁移的影响, refAbstract=null), Reference(id=1176918248395256485, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, doi=null, pmid=null, pmcid=null, year=2024, volume=45, issue=2, pageStart=48, pageEnd=52, url=null, language=null, rfNumber=[80], rfOrder=119, authorNames=Wang Rong, Liang Yulei, Chen Zhongqing, journalName=Shanghai Land & Resources, refType=null, unstructuredReference=Wang Rong, Liang Yulei, Chen Zhongqing. Study on environmental hydrogeological characteristics of the Yangtze River Delta and their impact on the transport of heavy metal contaminants[J]. Shanghai Land & Resources, 2024, 45(2): 48-52., articleTitle=Study on environmental hydrogeological characteristics of the Yangtze River Delta and their impact on the transport of heavy metal contaminants, refAbstract=null), Reference(id=1176918248453976742, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, doi=null, pmid=null, pmcid=null, year=2013, volume=49, issue=6, pageStart=3071, pageEnd=3092, url=null, language=null, rfNumber=[81], rfOrder=120, authorNames=Beven K, Germann P R R, journalName=Water Resources Research, refType=null, unstructuredReference=Beven K, Germann P R R. Macropores and water flow in soils revisited[J]. Water Resources Research, 2013, 49(6): 3071-3092., articleTitle=Macropores and water flow in soils revisited, refAbstract=null)], funds=[Fund(id=1176918239666909740, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, awardId=2023YSKY-40, language=CN, fundingSource=中央级公益性科研院所基本科研业务费专项(2023YSKY-40), fundOrder=null, country=null), Fund(id=1176918239792738861, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, awardId=2022-YRUC-01-0301, language=CN, fundingSource=黄河流域生态保护和高质量发展联合研究项目(2022-YRUC-01-0301), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1176918235816538590, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, xref=1, ext=[AuthorCompanyExt(id=1176918235824927199, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, companyId=1176918235816538590, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Institute of Solid Waste Pollution Control Technology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China), AuthorCompanyExt(id=1176918235833315808, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, companyId=1176918235816538590, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 中国环境科学研究院固体废物污染控制技术研究所, 北京 100012)]), AuthorCompany(id=1176918235887841761, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, xref=2, ext=[AuthorCompanyExt(id=1176918235892036066, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, companyId=1176918235887841761, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 National Joint Research Center for Ecological Conservation and 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articleId=1149773883139645532, companyId=1176918235980116452, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 北京师范大学水科学研究院, 北京 100085)])], figs=[ArticleFig(id=1176918238219874838, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Fig.1, caption=Statistics on the number of published literature, figureFileSmall=0C0Gld+1GKtSdFl0z+Ab+A==, figureFileBig=Y8KRmK/mwApM37SN2swrzg==, tableContent=null), ArticleFig(id=1176918238274400791, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=图1, caption=发文量统计, figureFileSmall=0C0Gld+1GKtSdFl0z+Ab+A==, figureFileBig=Y8KRmK/mwApM37SN2swrzg==, tableContent=null), ArticleFig(id=1176918238345703960, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Fig.2, caption=National cooperation co-occurrence network, 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caption=作者合作网络(CNKI), figureFileSmall=mjOrCV0JHKUaxUFkKz78Fg==, figureFileBig=tIiY1Lg1fyntcbD5gGokhg==, tableContent=null), ArticleFig(id=1176918238811271712, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Fig.6, caption=Author cooperation network(WOS), figureFileSmall=JKZh6Cxdu4V5ykZ8x+q8nQ==, figureFileBig=oWNs7BuJAcPw3HKpu1myag==, tableContent=null), ArticleFig(id=1176918238874186273, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=图6, caption=作者合作网络(WOS), figureFileSmall=JKZh6Cxdu4V5ykZ8x+q8nQ==, figureFileBig=oWNs7BuJAcPw3HKpu1myag==, tableContent=null), ArticleFig(id=1176918238928712226, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Table 1, caption=

Top 10 countries with the most published literature in the WOS database

, figureFileSmall=null, figureFileBig=null, tableContent=
国家 发文量/篇 中介中
心性
发文量
占比/%
总被引
频次
均篇被
引频次
中国 144 0.14 18.87 3 292 22.86
美国 118 0.51 15.47 3 165 26.82
印度 118 0.26 15.47 2 990 25.34
澳大利亚 22 0.10 2.88 789 35.86
加拿大 20 0.08 2.62 332 16.60
南非 19 0.19 2.49 359 18.89
波兰 18 0.02 2.36 174 9.67
土耳其 17 0.01 2.23 566 33.29
英国 16 0.37 2.10 643 40.19
韩国 14 0.15 1.83 205 14.64
), ArticleFig(id=1176918238995821091, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=表1, caption=

WOS数据库中发文量排名前十国家

, figureFileSmall=null, figureFileBig=null, tableContent=
国家 发文量/篇 中介中
心性
发文量
占比/%
总被引
频次
均篇被
引频次
中国 144 0.14 18.87 3 292 22.86
美国 118 0.51 15.47 3 165 26.82
印度 118 0.26 15.47 2 990 25.34
澳大利亚 22 0.10 2.88 789 35.86
加拿大 20 0.08 2.62 332 16.60
南非 19 0.19 2.49 359 18.89
波兰 18 0.02 2.36 174 9.67
土耳其 17 0.01 2.23 566 33.29
英国 16 0.37 2.10 643 40.19
韩国 14 0.15 1.83 205 14.64
), ArticleFig(id=1176918239058735652, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Table 2, caption=

Frequency of the top 10 keywords

, figureFileSmall=null, figureFileBig=null, tableContent=
CNKI数据库 WOS数据库
关键词 词频 中介中心性 关键词 词频 中介中心性
粉煤灰 44 1.11 coal fly ash 404 0.15
地下水 12 0.10 heavy metal 130 0.23
淋滤 7 0.06 removal 70 0.16
土壤 5 0.04 aqueous solution 70 0.09
重金属 4 0.04 adsorption 69 0.12
综合利用 3 0 trace element 66 0.10
贮灰场 3 0.05 groundwater 58 0.13
水环境 3 0 soil 47 0.20
氟化物 3 0.03 water 47 0.08
灰水 2 0.08 behavior 40 0.12
), ArticleFig(id=1176918239109067301, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=表2, caption=

出现频次前十名的关键词

, figureFileSmall=null, figureFileBig=null, tableContent=
CNKI数据库 WOS数据库
关键词 词频 中介中心性 关键词 词频 中介中心性
粉煤灰 44 1.11 coal fly ash 404 0.15
地下水 12 0.10 heavy metal 130 0.23
淋滤 7 0.06 removal 70 0.16
土壤 5 0.04 aqueous solution 70 0.09
重金属 4 0.04 adsorption 69 0.12
综合利用 3 0 trace element 66 0.10
贮灰场 3 0.05 groundwater 58 0.13
水环境 3 0 soil 47 0.20
氟化物 3 0.03 water 47 0.08
灰水 2 0.08 behavior 40 0.12
), ArticleFig(id=1176918239176176166, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Table 3, caption=

Distribution of coal fly ash contaminants content

, figureFileSmall=null, figureFileBig=null, tableContent=
污染物 含量/(mg·kg-1) 污染物 含量/(mg·kg-1)
Pb 28~119.57 P 1 300~2 800
Cr 5~950 S 1 000~1 500
Hg 0.133~1.26 Cl 990~1 310
Se 0.46~25.15 F 47.4~900
As 3~33.18 PCBs 0.011~0.032
N 100~300 PAHs 0~0.940
), ArticleFig(id=1176918239234896423, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=表3, caption=

粉煤灰污染物含量分布

, figureFileSmall=null, figureFileBig=null, tableContent=
污染物 含量/(mg·kg-1) 污染物 含量/(mg·kg-1)
Pb 28~119.57 P 1 300~2 800
Cr 5~950 S 1 000~1 500
Hg 0.133~1.26 Cl 990~1 310
Se 0.46~25.15 F 47.4~900
As 3~33.18 PCBs 0.011~0.032
N 100~300 PAHs 0~0.940
), ArticleFig(id=1176918239306199592, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Table 4, caption=

Coal fly ash contaminants release potential

, figureFileSmall=null, figureFileBig=null, tableContent=
粉煤灰来源 水环境指标 水环境影响 参考文献
一般化学指标 毒理学指标
中国陕西省 pH、 SO 4 2 -、Cl-
NH3-N、
F- NO 3 - NO 2 -
Cr6+
pH超标1.25倍, SO 4 2 -超标4倍,Cr6+超标135倍 [48]
中国安徽淮北某火力发电厂的贮灰场 Al3+ SO 4 2 - Cr6+、Se、 NO 3 -
NO 2 -、F-
浸出液超标:Al3+为5.55倍, SO 4 2 -为1.7倍,Cr6+为2.22倍,Se为9.75倍, NO 3 -为1.28倍, NO 2 -为9.17倍,F-为7.16倍 [52]
中国四座燃煤发电厂 pH、Mn Hg、As、Cr、Cd、
Ba、Pb
浸出液超标:pH超标1.32~1.44倍,其中三座电厂Cr分别超标1.76~2.57倍,其中一座电厂Ba超标1.98倍 [47]
中国大唐国际某煤气化项目 pH、Cu、Zn B、Cr6+、Ni、Cd、
Ba、Pb、As、Hg
浸出液超标:不同粒径As分别超标4.89~12.03倍,不同pH浸提剂浸出后的浸出液均为碱性,pH分别超标0.99~1.18倍 [53]
中国内蒙古、广西、云南省五座燃煤电厂 Cu、Zn Cd、Cr、Pb、Ni 浸出液超标:Cr最高超标1.65倍 [54]
河北省邯郸市某燃煤发电厂 pH、Cu、Zn Be、B、Co、Ni、Se、
Mo、Cd、Sb、Ba、
Hg、Tl、Pb
浸出液超标:pH最高超标1.49倍,As、Se最高超标300倍以上,B、Tl、Mo、Ba最高分别超标44、31、39、3.3倍 [49]
), ArticleFig(id=1176918239377502761, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=表4, caption=

粉煤灰污染物释放潜力

, figureFileSmall=null, figureFileBig=null, tableContent=
粉煤灰来源 水环境指标 水环境影响 参考文献
一般化学指标 毒理学指标
中国陕西省 pH、 SO 4 2 -、Cl-
NH3-N、
F- NO 3 - NO 2 -
Cr6+
pH超标1.25倍, SO 4 2 -超标4倍,Cr6+超标135倍 [48]
中国安徽淮北某火力发电厂的贮灰场 Al3+ SO 4 2 - Cr6+、Se、 NO 3 -
NO 2 -、F-
浸出液超标:Al3+为5.55倍, SO 4 2 -为1.7倍,Cr6+为2.22倍,Se为9.75倍, NO 3 -为1.28倍, NO 2 -为9.17倍,F-为7.16倍 [52]
中国四座燃煤发电厂 pH、Mn Hg、As、Cr、Cd、
Ba、Pb
浸出液超标:pH超标1.32~1.44倍,其中三座电厂Cr分别超标1.76~2.57倍,其中一座电厂Ba超标1.98倍 [47]
中国大唐国际某煤气化项目 pH、Cu、Zn B、Cr6+、Ni、Cd、
Ba、Pb、As、Hg
浸出液超标:不同粒径As分别超标4.89~12.03倍,不同pH浸提剂浸出后的浸出液均为碱性,pH分别超标0.99~1.18倍 [53]
中国内蒙古、广西、云南省五座燃煤电厂 Cu、Zn Cd、Cr、Pb、Ni 浸出液超标:Cr最高超标1.65倍 [54]
河北省邯郸市某燃煤发电厂 pH、Cu、Zn Be、B、Co、Ni、Se、
Mo、Cd、Sb、Ba、
Hg、Tl、Pb
浸出液超标:pH最高超标1.49倍,As、Se最高超标300倍以上,B、Tl、Mo、Ba最高分别超标44、31、39、3.3倍 [49]
), ArticleFig(id=1176918239444611626, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=EN, label=Table 5, caption=

The current situation of coal fly ash-induced water pollution in different regions around the world

, figureFileSmall=null, figureFileBig=null, tableContent=
粉煤灰来源 水环境指标 水环境影响 参考
文献
一般化学指标 毒理学指标
印度阿里加尔哈尔杜阿甘杰热电厂 pH、Ca2+、硬度、
Cl-、Na+ SO 4 2 -
NO 3 - 附近地下水理化参数大多超过WHO(2011)和BIS(2012)的建议浓度限值 [55]
印度本德尔坎德州占西县帕里恰热电站 Fe、Mn、Al Ni、Pb、Cr 距灰池5 km范围内重金属呈重度污染,7 km范围内呈中度污染,15 km范围内呈极低污染 [51]
中国安徽省淮南市某粉煤灰堆场 TN、TP、Cl- SO 4 2 -
COD、NH3-N、Ca2+
Na+、Mg2+ HCO 3 -
F- NO 3 - 粉煤灰堆场对周边地表水中TN、TP、F-、Cl- SO 4 2 - NO 3 -浓度,周边地下水中COD、NH3-N、TP、Ca2+、Na+、Mg2+ HCO 3 - SO 4 2 -浓度存在一定影响 [56]
土耳其亚塔甘火电厂 Cu、Fe、Mn、Zn、 SO 4 2 - As、Hg、Cd、
Co、Pb
部分地下水样品中Fe、Pb、Cd和Mn含量高于欧共体和世卫组织的指导值 [57]
), ArticleFig(id=1176918239507526187, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1149773883139645532, language=CN, label=表5, caption=

世界各地粉煤灰对水环境污染现状

, figureFileSmall=null, figureFileBig=null, tableContent=
粉煤灰来源 水环境指标 水环境影响 参考
文献
一般化学指标 毒理学指标
印度阿里加尔哈尔杜阿甘杰热电厂 pH、Ca2+、硬度、
Cl-、Na+ SO 4 2 -
NO 3 - 附近地下水理化参数大多超过WHO(2011)和BIS(2012)的建议浓度限值 [55]
印度本德尔坎德州占西县帕里恰热电站 Fe、Mn、Al Ni、Pb、Cr 距灰池5 km范围内重金属呈重度污染,7 km范围内呈中度污染,15 km范围内呈极低污染 [51]
中国安徽省淮南市某粉煤灰堆场 TN、TP、Cl- SO 4 2 -
COD、NH3-N、Ca2+
Na+、Mg2+ HCO 3 -
F- NO 3 - 粉煤灰堆场对周边地表水中TN、TP、F-、Cl- SO 4 2 - NO 3 -浓度,周边地下水中COD、NH3-N、TP、Ca2+、Na+、Mg2+ HCO 3 - SO 4 2 -浓度存在一定影响 [56]
土耳其亚塔甘火电厂 Cu、Fe、Mn、Zn、 SO 4 2 - As、Hg、Cd、
Co、Pb
部分地下水样品中Fe、Pb、Cd和Mn含量高于欧共体和世卫组织的指导值 [57]
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基于CiteSpace可视化分析粉煤灰堆存对水环境影响研究进展
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杨玉飞 1, 2 , 卢永琦 1, 2 , 刘婷婷 1, 2 , 徐思琪 1, 2, 3 , 黄瑞潇 1, 2 , 迭庆杞 1, 2, *
科学技术与工程 | 综述·环境科学、安全科学 2025,25(13): 5285-5296
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科学技术与工程 | 综述·环境科学、安全科学 2025, 25(13): 5285-5296
基于CiteSpace可视化分析粉煤灰堆存对水环境影响研究进展
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杨玉飞1, 2 , 卢永琦1, 2, 刘婷婷1, 2, 徐思琪1, 2, 3, 黄瑞潇1, 2, 迭庆杞1, 2, *
作者信息
  • 1 中国环境科学研究院固体废物污染控制技术研究所, 北京 100012
  • 2 国家黄河流域生态保护和高质量发展联合研究中心, 北京 100012
  • 3 北京师范大学水科学研究院, 北京 100085
  • 杨玉飞(1977—),男,汉族,江西上饶人,博士,研究员。研究方向:危险废物环境风险控制和固体废物资源化环境安全性评价。E-mail:

通讯作者:

* 迭庆杞(1988—),男,汉族,河南南阳人,博士,副研究员。研究方向:固体废物环境管理和风险评估。E-mail:
Review on the Impact of Coal Fly Ash Stockpiling on Water Environment Based on CiteSpace Visualization Analysis
Yu-fei YANG1, 2 , Yong-qi LU1, 2, Ting-ting LIU1, 2, Si-qi XU1, 2, 3, Rui-xiao HUANG1, 2, Qing-qi DIE1, 2, *
Affiliations
  • 1 Institute of Solid Waste Pollution Control Technology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
  • 2 National Joint Research Center for Ecological Conservation and High Quality Development of the Yellow River Basin, Beijing 100012, China
  • 3 College of Water Sciences, Beijing Normal University, Beijing 100085, China
出版时间: 2025-05-08 doi: 10.12404/j.issn.1671-1815.2406119
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粉煤灰长期堆存会释放大量有毒有害物质,并对水环境构成威胁。为全面了解该领域的研究进展,采用文献计量学方法,系统并深入地对CNKI和Web of Science数据库中从建库至2023年间的相关文献进行了可视化分析。结果表明:该领域的年总发文量整体呈上升趋势,其中:中国科学家在该领域进行了大量研究工作,发文量最多,占总发文量的18.87%,为后续研究提供了重要科学依据,美国发文的中介中心性(0.51)明显高于其他国家,研究成果更具国际影响力;研究热点主要围绕粉煤灰中重金属等污染物,探究其在不同条件下的浸出、淋溶释放规律,揭示粉煤灰堆场污染物迁移带来的环境影响。基于高频关键词分析,探讨了粉煤灰污染物组成特征和可能释放到水环境中的污染物类型,系统梳理和分析了污染物的释放机制、规律和关键影响因素,以及污染物在环境介质中的迁移规律研究进展。未来研究应进一步关注粉煤灰堆存过程中Pb、Cr、Hg等重金属,As、Se、Mo等微量元素和F-、Cl-、$\mathrm{SO^{2-}_{4}}$、$\mathrm{PO^{3-}_{4}}$等特征污染物的释放问题,探究复杂环境影响下特征污染物的释放特性,并明确不同因素是否存在协同或抑制机制,建立粉煤灰固相中污染物指标与其释放进入水环境的指标间的定量关系,为科学评价粉煤灰环境影响提供理论基础,进而有效防范粉煤灰中污染物对水环境的潜在威胁。

CiteSpace  /  粉煤灰  /  水环境  /  文献计量学  /  可视化

Long-term stockpiling of coal fly ash releases a large amount of toxic and hazardous substances, posing a threat to the soil and water environment. In order to have a comprehensive understanding of the research progress in this field, a bibliometric method was conducted to systematically and deeply visualize and analyze the relevant literature in CNKI and Web of Science databases from the period of database construction to 2023. The results show that the annual total number of publications in this field is generally on the rise. Among them, Chinese scientists have conducted a substantial amount of research in this field, accounting for the highest publication volume, which makes up 18.87% of the total, providing important scientific foundation for subsequent studies. The betweenness centrality of publications from the United States (0.51) is significantly higher than that of other countries, and its research results have greater international influence. The research hotspots focus on contaminants like heavy metals in coal fly ash, investigating their leaching and release patterns under various conditions, and revealing the environmental impacts of contaminants migration from coal fly ash landfills. Based on high-frequency keyword analysis, the composition of contaminants in coal fly ash and the types of contaminants potentially released into the water environment were examined. A systematic review and analysis of contaminants release mechanisms, release regularity, key influencing factors, and the migration regularity of mechanisms in environmental media were conducted. Future research should further focus on the release of heavy metals such as Pb, Cr, and Hg, trace elements like As, Se, and Mo, and specific mechanisms such as F-, Cl-, and $\mathrm{SO^{2-}_{4}}$, $\mathrm{PO^{3-}_{4}}$ during the coal fly ash stockpiling. Studies should explore the release characteristics of these mechanisms under complex environmental conditions, investigate whether synergistic or inhibitory mechanisms exist between various factors, and establish quantitative relationships between mechanisms indicators in the solid phase of coal fly ash and their release into water environment. This will provide a theoretical basis for scientifically evaluating the environmental impacts of coal fly ash and effectively preventing potential threats to water environment.

CiteSpace  /  coal fly ash  /  water environment  /  bibliometrics  /  visualization
杨玉飞, 卢永琦, 刘婷婷, 徐思琪, 黄瑞潇, 迭庆杞. 基于CiteSpace可视化分析粉煤灰堆存对水环境影响研究进展. 科学技术与工程, 2025 , 25 (13) : 5285 -5296 . DOI: 10.12404/j.issn.1671-1815.2406119
Yu-fei YANG, Yong-qi LU, Ting-ting LIU, Si-qi XU, Rui-xiao HUANG, Qing-qi DIE. Review on the Impact of Coal Fly Ash Stockpiling on Water Environment Based on CiteSpace Visualization Analysis[J]. Science Technology and Engineering, 2025 , 25 (13) : 5285 -5296 . DOI: 10.12404/j.issn.1671-1815.2406119
粉煤灰是燃煤电厂在生产过程中产生的一种主要大宗工业固废[1],2022年中国粉煤灰产量达8.31亿t[2],综合利用率约为70%[3],剩余部分主要以露天堆存、填埋等方式处置。粉煤灰中含有多种无机污染物,如重金属、氟化物、氮化物及氯化物等[4]。在自然风化、雨水淋滤等环境影响下,污染物会不断释放,并经大气沉降、地表径流及纵向渗透等途径进入土壤和地下水,对周边环境造成影响。此外,部分粉煤灰堆场位于生态脆弱区,一旦管控不当,极易对当地生态环境造成严重威胁[5-6]
随着人们对堆存粉煤灰引起的水环境污染问题的日益关注,相关研究文献逐渐增加。近年来,国内外学者在粉煤灰理化性质[7-8]、浸出毒性特性[9]及污染物淋溶释放规律[10]等方面开展了大量研究工作。王雅男等[11]通过室内模拟实验探究了粉煤灰中氮素($\mathrm{NO}_{3}^{-}-\mathrm{N}$、$\mathrm{NO}_{2}^{-}-\mathrm{N}$、$\mathrm{NH}_{4}^{+}-\mathrm{N}$)的淋滤释放规律,并发现$\mathrm{NO}_{2}^{-}-\mathrm{N}$浓度超过《地下水质量标准》(GB/T 14848—2017)中Ⅲ类水体标准。袁霄梅等[12]利用同位素示踪技术并结合堆场水文地质状况研究发现:粉煤灰的长期堆存一定程度上导致附近地下水中Cr6+、F-等污染物浓度升高,对其周围地下水造成影响。Lange等[13]通过模拟降雨淋溶作用,提出粉煤灰中As、Cd、Mo和Zn可长期释放,并对土壤和地下水存在潜在风险。Szatylowicz等[14]通过对不同颗粒尺寸煤燃烧获得的粉煤灰进行浸出,发现在所有粉煤灰浸出液中均发现了多环芳烃(polycyclic aromatic hydrocarbons,PAHs)。Wang等[15]系统综述了粉煤灰的颗粒外观、晶体组成、化学成分、比表面积和粒径分布等理化性质对污染物浸出能力的影响,并提出需要在实际自然条件下更加深入地探究粉煤灰中污染物浸出规律及控制机制。由上述研究可以发现:粉煤灰堆场是重金属、氟化物和氮素、有机污染物等的重要释放源,会通过释放和迁移过程对周边水环境质量造成严重影响,因此识别堆存场景下粉煤灰中污染物的释放迁移规律和环境影响机制是防控其环境风险的关键。然而,当前针对该环境问题的研究较为分散,亟须从宏观尺度上深入并系统地分析该领域的研究现状及发展趋势,阐明破解粉煤灰环境污染的关键科学问题和技术方向。
文献计量学分析是一种以应用数学和统计学为基础来获取不同研究领域动态的方法,可帮助研究人员迅速掌握该领域的研究现状、趋势及热点[16]。目前,文献计量学方法已经广泛应用于自然科学,社会科学与人文科学等领域[17-18]。现利用CiteSpace软件,从文献发表数量、发文国家、发文机构、发文作者和文章关键词等方面,对粉煤灰堆场对水环境质量影响研究方向的发展态势进行可视化分析,梳理该领域研究人员关注的重点和研究热点。在此基础上,研究从水环境质量安全和风险防控的角度出发,剖析粉煤灰堆存过程中的污染物释放迁移规律和关键影响因素,探讨相关研究中尚未解决的关键问题。以期为后续研究人员快速了解该领域研究现状和未来发展趋势提供参考与借鉴。
以全面掌握长期堆存的粉煤灰对水环境质量影响为目标,系统分析国内外在该领域的研究现状及进展。数据来源于CNKI数据库和Web of Science(WOS)核心合集,时间设置为建库以来至2023年12月31日;利用CNKI数据库的高级检索功能,以“粉煤灰”OR“粉煤灰堆场”OR“堆存粉煤灰”AND“影响”OR“污染”OR“恶化”OR“破坏”AND“水环境”OR“水体”OR“地下水”OR“地表水”OR“水质”OR“水资源”为关键词,文献类型限定为学术期刊与学术论文,筛选出95篇中文文献(包括24篇学位论文);利用WOS数据库高级检索功能,检索式:TS = (“fly ash” or “coal fly ash” or “Coal-fired fly ash”) AND TS = (influence or effect or impact or pollut* or contaminat*) AND TS = (“water environment” or “water quality” or “water body”),研究方向确定为Environmental Sciences Ecology、Engineering、Water Resources、Energy Fuels、Toxicology、Geochemistry Geophysics、Public Environmental Occupational Health,筛选出594篇英文文献。
运用CiteSpace软件对所收集的大量文献数据信息进行可视化输出,参数设置:时间切片单位为1年,节点间关系强度选择Cosine算法,阈值选择标准为g指数(g-index),比例因子k=10,对于较为复杂网络,选择pruning sliced networks进行简化。
年度文献数量的统计分布在一定程度上能够直观地反映出特定领域研究的动态变化[19]。与“粉煤灰堆存对水环境质量影响”这一主题相关的文章的发文量如图1所示,可见其整体呈逐年上升的趋势,并且英文文献的发文量明显高于中文。其中,2014—2019年发文量增长速度较快,可能归因于在此期间世界各地发生的多起粉煤灰环境污染问题,例如:2018年,山西忻州某煤电厂违反政府和环保法的规定,在忻府区内多个乡镇肆意倾倒粉煤灰,污染了当地环境,对居民生活造成危害;2014年,美国北卡洛来纳州发生粉煤灰泄漏事件,该事件导致50 000~82 000 t的煤灰流入了北卡罗来纳州伊甸附近的丹河[20]。此外,美国国家环境保护局(U.S. Environmental Protection Agency,EPA)在2015年颁布了美国联邦政府的煤灰管理规定(Coal Ash Rule),旨在规范粉煤灰的管理和处置,以保护公共健康和环境。
以“Country”为研究对象对WOS核心合集数据库文献进行分析,评估各国在该领域的研究贡献。分析发现共有72个国家在该领域发表过文章,根据发文量筛选出了居于前十名的国家,如表1所示。其中,中国以144篇发文量居于首位,占总发文量的18.87%。中国科学家在粉煤灰污染领域进行了大量研究工作,Wang等[21]的研究表明,Pb、Cr、Cd、Hg等重金属在粉煤灰中普遍存在,并且具有较高的环境风险。在对粉煤灰中高危险性重金属(Cr、Cd、Hg)迁移规律进行研究时发现,其浸出率随粉煤灰粒径的增大而降低。同时,实验数据和迁移模拟结果均表明,重金属离子会通过渗透作用向土壤深层和地下水迁移。此外,Huang等[22]的研究中同样揭示了粉煤灰中的Cr具有较大的释放潜力,需重点关注其长期环境影响,在其另一篇文章中,Huang等[23]进一步研究了粉煤灰中Hg的释放,发现尽管Hg浸出率较低(<0.110%),但在某些利用过程中(如涉及加热的制砖工艺)可能会导致汞的跨介质排放,这一潜在风险还需进一步评估。上述科学家的研究为粉煤灰污染评估与防控提供了重要科学依据。
除中国外,美国和印度以118篇发文量分别位列第二和第三。美国的中介中心性为0.51,远高于其他国家,表明其研究成果在国际上更具影响力。各个国家合作网络如图2所示,可以看出在该领域世界各国间的研究关系较为密切。
以“Institution”为研究对象进行分析,能够体现各研究机构在该领域的协作关系。CNKI数据库和WOS核心合集数据库中该领域的研究机构合作网络分别如图3图4所示。
图3分析可见,CNKI数据库文献的网络节点数量(N)为85,连线(E)为33,密度为0.009 2,各个节点连线之间相对稀疏,表明各研究机构间合作相对较少;而WOS核心合集数据库文献的网络节点数量(N)为442,连线(E)为321,密度为0.003 3(图4)。具体来看,中国科学院与国际上其他机构之间的合作最为密切,其次是以印度矿业学院(Indian Sch Mines)、杜克大学(Duke Univ)、印度理工学院(Indian Inst Technol)为中心的协作网络。以上分析发现:在粉煤灰堆存对水环境质量影响的研究领域,国际各研究机构之间的合作关系更为密切,而国内机构间的合作有待加强。
以“Author”为研究对象进行分析,得出该研究领域的文献作者合作共现网络,分别如图5图6所示。图5为CNKI数据库文献作者合作网络共现图,共涉及187名作者,其中发表文献最多的作者是尹国勋(发表6篇),其次是张永波、时红、郭慧霞,分别发表3篇文章;图6为WOS核心合集数据库文献作者合作网络共现图,共有623名作者在该领域发表文章,发文量最高的作者是Aydilek Ahmet H,共发表6篇文章,其次发文量较高的作者是Vengosh Avner、Hart Megan L、Kevern John T、Holmes Ryan R,分别发表5篇文章。值得注意的是,Aydilek等在其被引频次最高的文章中研究了高碳粉煤灰制路基材料技术,揭示了粉煤灰资源化产品中元素Ba、B、Cu和Zn的浸出规律及其对地下水的影响,并指出粉煤灰掺量的增加和石灰掺量的减少促进了Ba、B和Cu的浸出,而Zn的浸出主要受粉煤灰掺量的影响,且金属浸出到地下水的浓度会根据场地条件发生变化[24]
关键词作为对一篇文章的高度凝练与概括,通过系统分析可揭示该领域的研究现状与热点[25]。用CiteSpace对CNKI数据库文献与WOS数据库文献的关键词进行分析,得到出现频次排在前十名的关键词,如表2所示。
CNKI文献中出现频次最高的关键词除“粉煤灰”外,分别是“地下水”“淋滤”“土壤”“重金属”等,说明中国研究比较关注粉煤灰对地下水环境的影响,且其主要途径为降水淋滤[26]。粉煤灰被雨水淋溶后,释放的污染物会首先在土壤中迁移,而后通过包气带进一步向下入渗,长期滞存的灰水会降低土壤环境容量,并向下进一步迁移到地下水,造成地下水污染[9]。重金属作为高频关键词出现表明其在粉煤灰中的普遍存在性,是粉煤灰中对水环境影响的特征污染物[27-28]。WOS数据库文献出现频次最高的关键词是“coal fly ash”,其次是“heavy metal”“removal”“aqueous solution”“adsorption”“trace element”“groundwater”“soil”等。与CNKI文献的发现结果具有高度一致性,表明国内外的研究均重点关注了粉煤灰中重金属、微量元素等对土壤及水环境产生的影响。结合高频关键词,研究从以下几个方面对粉煤灰堆场影响水环境质量的环境问题进行分析。
粉煤灰中几种典型污染物的含量分布如表3所示。Pb、Cr、Hg等重金属元素及Se、As等微量元素是粉煤灰中主要的重金属类污染物,这类物质含量约占粉煤灰成分的0.16%~0.22%[29]。粉煤灰中的N、P、S、Cl、F等无机元素含量呈现出Cl(0.099%~0.131%)[30]>P(0.13%~0.28%)[31]>S(0.02%~0.11%)[32]>F(0.005%~0.09%)[33-34]>N(0.01~0.03%)[35]的特征。此外,部分粉煤灰还含有微量有机污染物,如多氯联苯(polychlorinated biphenyls,PCBs)、多环芳烃(PAHs)等,这是由于煤的不完全燃烧导致有机物残留在粉煤灰中,其中PAHs和PCBs主要以2环和3环PAHs、2~4环PCBs等低分子质量的同系物为主[36]
不同粉煤灰中污染物种类及含量存在显著差异,主要取决于发电厂燃煤的类型、使用的煤清洗技术以及化学元素自身性质[32]。例如,循环流化床粉煤灰和煤粉锅炉粉煤灰中Pb、As、Cr等元素含量相对其他物质更高,主要是由于煤高温燃烧时,Pb、As、Cr等中等挥发性元素在炉内蒸发后,随烟气冷却凝结于细小粉煤灰中,而Hg、Cd等为高挥发性元素,主要以气态形式逸出[37]。对于褐煤与烟煤粉煤灰,褐煤粉煤灰中重金属元素富集程度依次为Cd>Pb>Zn>As>Cu,烟煤粉煤灰中则依次为As>Cd>Zn>Pb>Cu,该现象主要与粉煤灰粒径与元素化学性质有关[38]。此外,粉煤灰中污染物含量也表现出地区性差异,有研究将内蒙古上都、广西来宾、广西南宁、云南威信地区的粉煤灰污染物含量进行对比时发现,不同粉煤灰中B含量相差范围在32~1 445 mg/kg,V在141~1 378 mg/kg[39]
粉煤灰对水环境的影响主要通过污染物释放到浸出液然后迁移至水环境中。部分粉煤灰中污染物的浸出潜力和粉煤灰堆场周边地下水中污染物的浓度分布情况分别如表4表5所示。
粉煤灰中的污染物可能会影响地下水的感官性状和一般化学指标。如粉煤灰浸出液通常呈碱性,可能会影响地下水pH;浸出液中还含有硫酸盐、氯化物、氨氮等一般化学指标类污染物,耿方方等[48]对粉煤灰浸出液中上述污染物含量进行检测时发现 SO 4 2 -浓度高达999 mg/L;此外,粉煤灰中的氟化物、Cr6+、As、Se、Ba、Mo等毒性指标在粉煤灰浸出过程中也表现出较高的浸出潜力,有研究指出粉煤灰浸出液中Cr6+浓度可达6.75 mg/L,为地下水Ⅲ类水体标准的135倍[48],As、Se在浸出液中浓度可达3 mg/L以上,超出标准的300倍[49]。与重金属类指标相比较,现有研究较少关注粉煤灰浸出液中F-、Cl- SO 4 2 - PO 4 3 -、硝酸盐等指标对水环境的潜在影响,但根据粉煤灰中污染物含量和浸出浓度结果,未来研究应更加重视这些污染物对水环境的潜在危害。
现有部分研究已表明,粉煤灰堆存场已对周边水环境质量造成实际影响,且可能对周边生态系统造成长期危害。Wang[50]对粉煤灰堆存场周边的20口监测井采集的480份水样进行分析,根据水质指数(water quality index,WQI)分析结果得出灰场周围水质均不适合饮用,根据危险商数(hazard quotient,HQ)和危险指数(hazard index,HI)进行健康风险评估得出,煤灰周围16种元素中,As、Sb、Cd、Pb、V和Cr是最大的健康风险因子。Verma等[51]曾对堆场附近地下水进行重金属污染指数(heavy metal pollution index,HEI)计算,HEI结果表明在距灰池5 km范围内地下水表现为重度污染,在距灰池7 km范围内表现为中度污染,在距灰池15 km范围内表现为极低污染。这些研究结果充分证明,粉煤灰堆存场会导致附近水体中出现重金属及其他类型污染物(如Cl- SO 4 2 -等)超标、理化参数异常等问题,并且这些污染均表现出距离效应。
溶解、扩散、吸附、沉淀等是粉煤灰中重金属类污染物释放的主要机制,污染物的赋存形态则是控制其释放的关键因素。
煤高温燃烧会导致粉煤灰中微量元素如:As、Se、Cr、V、Mo分别主要以As(Ⅴ)、Se(Ⅳ)、Cr(Ⅲ)、V(Ⅳ)、Mo(Ⅵ)形式存在于粉煤灰中[58]。As元素通常赋存在粉煤灰颗粒的表面,且As(Ⅴ)易溶,有研究表明As在粉煤灰中的可溶性状态约占总量的29.08%,As与铁矿物具有较高的亲和力,因此Fe的存在也会影响其释放行为;Cr在粉煤灰中10%以上以可溶态存在,且酸性越强,浸出浓度越高[59],通常以Cr(Ⅲ)形式进入水体;Mo主要以MoO3形式沉积在粉煤灰颗粒表面,在碱性条件下具有较高的迁移率;部分Se元素可能以亚硒酸盐(Na2SeO3、CaSeO3)的形式在粉煤灰中赋存,Na2SeO3物质易溶于水,CaSeO3可溶于酸;V主要以氧化物和硅酸盐形式存在,以氧化物(VO2)形式存在的V,极易溶解在酸性或碱性溶液中[58]。Hg是煤中常见的有毒元素,会在煤燃烧过程中挥发成烟气,一部分以HgCl2和HgS形式吸附在粉煤灰表面[60],吸附在粉煤灰表面的HgCl2可直接溶于水,HgS可微溶于酸。
F元素在粉煤灰中可能以NaFSiO4、KFSiO4和MgFSiO4等硅酸盐形式存在,以硅酸盐形式存在的F性质相对稳定,但在酸性条件下仍会部分溶解;Cl元素可能以金属氯化物(如KCl、NaCl)的形式存在[61],在雨水淋溶与浸出作用下,Cl-可直接溶于水;S元素在粉煤灰中会以CaSO4,磁黄铁矿[Fe(1-x)S]等形式存在[62],硫酸盐是其主要存在形式,占粉煤灰中总硫含量的80%以上[63],进入水体后会以 SO 4 2 -形式存在;N元素可能以铵盐形式沉积于粉煤灰表面[64],铵盐的溶解性通常较高,进入水体后可转化为氨氮或硝态氮。P元素主要以磷酸盐形式存在于硅酸盐矿物中,只有在较低pH条件下其浸出量会显著增加,并以 PO 4 3 -形式进入水体[58]
粉煤灰中的有机污染物(PCBs、PAHs等)属于疏水性化合物,主要吸附在粉煤灰表层,在水中溶解度较低,在降雨淋溶作用下,携带PCBs和PAHs的细小颗粒从粉煤灰表面解吸悬浮于水中,随水流进入地表水或地下水。此外,降雨和水流的持续扰动也可使其微量溶于水体,并以乳化态形式存在[9]
关于固体废物中污染物释放机制的研究还可通过耦合释放规律和理论模型进行分析。一般而言,重金属类污染物的释放规律通常符合一维扩散方程、抛物线方程、零级动力学方程、一级动力学方程、二级动力学方程、Elovich方程和Freundlich方程等动力学模型[65],简单的Elovich模型和拟二级动力学模型最适合预测粉煤灰中Zn和Pb等重金属元素的浸出速率[66]。粉煤灰中氮的累积释放量随时间的变化符合对数规律[11]。柱淋溶实验中淋溶液的pH、Cd浓度呈多项式曲线形式分布,Cr6+浓度呈对数曲线形式分布,F-浓度呈直线形式分布[67]。PAHs从粉煤灰中的溶出规律基本呈现先增后减,最终稳定的趋势[68]。这些结果表明不同类型污染物的释放规律存在显著差异,主要是由于污染物的性质及其在粉煤灰中的赋存形态不同,导致其释放机制不同[13]。此外,不同实验条件也是影响污染物释放的关键因素。
粉煤灰向水体释放污染物过程受多种因素影响,主要包括降雨pH、降雨量(液固比)、淋溶频率与粉煤灰自身物理化学性质等。
pH是影响粉煤灰中重金属类无机污染物释放的关键因素[69]。通常情况下,Cr、Cu、Co、Ni等重金属类元素在酸性条件下更容易被浸出[39,70];而Mo元素则在碱性条件下更容易浸出[58,71];对于一些两性物质(Al、V、As等),在极酸或极碱性条件下都应有更高的浸出潜力,例如,粉煤灰中As在pH<4及pH>9条件下迁移率较高,而在中性条件下其释放量可忽略不计[72]。目前关于pH对粉煤灰中有机物污染物释放的影响研究较少。
污染物浸出浓度也会随固液比的改变而发生相应变化,Dutta等[73]研究粉煤灰的长期静态浸出过程时发现:当固液比为0.05~0.20时,在接触时间为15 d时,随着固液比的增加,Cr、Pb、As等元素的浸出浓度呈现增加趋势,而Fe元素相反,在固液比为0.05时浸出浓度最高;此外,粉煤灰的物化特性[74]对污染物释放具有直接影响,包括颗粒大小、比表面积以及化学成分等因素,颗粒较小粉煤灰具有更大比表面积,能够更充分地与溶液接触,从而加速污染物的溶解和释放,例如,有研究指出,粉煤灰粒径越小,Al元素的浸出率越高[15],粉煤灰的化学成分也对污染物的释放有显著影响。例如,含有高钙和铝硅酸盐成分的粉煤灰在水中可能会形成稳定的沉淀,从而降低重金属的溶解度和释放速率。
在粉煤灰堆存的实际场景中,污染物释放会受多重因素的复合影响,现有研究主要分析了不同因素对污染物释放的单一影响,而缺乏实际复杂环境条件下的综合模拟,尤其是自然降水变化、温度波动、粉煤灰性质随时间变化等因素对粉煤灰中污染物释放的综合影响,不同因素之间是否存在协同或抑制机制,是未来的研究中应重点考虑的方向。
对于未采取防渗措施的粉煤灰堆场,污染物可能随降雨淋溶进入非饱和带,经对流、弥散、扩散、吸附等作用,一部分被土壤吸附,另一部分通过空气带入含水层,进而随地下水流进行横向迁移,并在地下水中形成羽状体污染晕扩散。
国内外学者对污染物在地下水中的迁移开展了广泛的研究。目前,使用数值模型是模拟预测污染物在环境介质中迁移的常用方法。美国地质调查局开发的三维地下水流动模型(modular three-dimensional finite-difference ground-water flow model,MODFLOW)与美国国家盐土实验室(U.S. Salinity Laboratory)开发的Hydrus模型等成为土壤包气带和地下水中污染物迁移模拟的常用工具[75-77]。不同的数值模型在粉煤灰污染物迁移研究中有各自的适用场景,传统一维模型会将复杂的迁移过程进行简化,因此更适用于模拟降水入渗污染物在环境介质中的垂直迁移,MODFLOW等三维模型更适合模拟复杂地下水流动和污染物的迁移过程。王雪等[77]曾采用Hydrus-1D模型模拟预测了NH3-N在包气带中的迁移动态变化。Chowdhury等[78]使用MODFLOW和MT3DMS模型对Rajshahi含水层的地下水流量和污染物迁移进行了建模,并表明该模型可用作监测特定位置地下水污染物传输的有效决策工具。
污染物在环境介质中的迁移会受污染物性质、场地水文地质参数等多重因素的影响。在相同环境因素下,非饱和带中苯比萘更容易穿透非饱和带污染地下水,苯在重力和淋洗作用下,能够穿过渗透性差的粉土层进入更深的土层;而萘在相同作用下,大部分萘富集表层,只有少量萘不断向深层土壤扩散和迁移[79]。高渗透性土层具有较高的渗透系数、强对流和扩散作用、低有机物和矿物吸附性,重金属易随地下水迁移[80]。在浅埋基岩层中,重金属迁移不仅受包气带岩土层性质的影响,还与基岩的岩性和风化程度相关,基岩破碎较强时,重金属随裂隙水迁移的能力增强。因此,在研究粉煤灰中污染物在土壤和地下水中的迁移时应重点考虑污染物的理化性质和场地的水文地质条件。
现有的数值模型为污染物迁移研究提供了有效工具,但它们在实际应用中仍面临一定的局限性。例如,这些模型在处理实际环境中的复杂水流和污染物迁移时,通常需要对边界条件和反应过程进行简化,可能导致对污染物迁移路径、速度和降解过程的预测不够精确[81]。此外,模型的高数据需求和计算资源消耗也是实际应用中的主要挑战。因此,未来的研究应加强数据收集与模型精度优化,并结合人工智能和机器学习方法,以提高预测的准确性和效率。
(1)在研究时间范围内,CNKI数据库与WOS核心合集中关于粉煤灰堆存对水环境质量影响的文章年发文总量呈整体上升趋势,中国发文量最多,占比为总发文量的18.87%,美国发文量仅次于中国,但其中介中心性最高,研究成果得到广泛认可,中国科学院与国际上的研究机构合作最为密切。
(2)通过对关键词进行分析,粉煤灰污染物成分复杂,包括重金属,微量元素,N、P、S、Cl、F等无机物质及少量有机物,现有研究关注更多的是重金属和微量元素,不同类型粉煤灰中污染元素含量差异显著。污染物的赋存形态是控制其释放的关键因素,且不同污染物释放规律不同,污染物释放会受pH、液固比、污染物自身性质等多重因素影响。粉煤灰堆存场景下可能释放迁移进入水体的特征污染物主要包括Pb、Cr、Hg等重金属、As、Se、Mo等微量元素,以及F-、Cl- SO 4 2 - PO 4 3 -、氮素等水质指标。对于污染物迁移已有较为成熟的模拟方法,在实际模拟污染物迁移过程中应综合考虑污染物的理化性质和污染场地的水文地质条件等复杂因素影响。
(3)基于研究现状及热点分析,首先未来研究可更多关注粉煤灰中除重金属等常规污染物之外的其他指标(如F-、COD、有机物等);其次,目前针对粉煤灰在实际复杂环境条件下污染物释放的综合模拟研究仍处于空白,尤其是在考虑自然降水变化、温度波动、粉煤灰性质随时间变化等因素时,不同因素之间是否存在协同或抑制机制,是未来的研究中应重点考虑的方向。最后,目前粉煤灰中污染物含量,与其在特定环境条件下释放至水体中污染物浓度之间的定量关系尚不明确,因此,建立粉煤灰中污染物含量与其淋溶释放进入水体中污染物指标之间的定量关系(例如:粉煤灰中总N、总S等污染物指标分别与释放到水体中的NH3-N、 SO 4 2 -等指标的定量关系),对今后固废管理具有重要指导意义,但深入研究这一领域亟须克服粉煤灰中污染物的复杂释放迁移机制,以及定量关系构建中多变量耦合作用等难点。
  • 中央级公益性科研院所基本科研业务费专项(2023YSKY-40)
  • 黄河流域生态保护和高质量发展联合研究项目(2022-YRUC-01-0301)
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2025年第25卷第13期
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doi: 10.12404/j.issn.1671-1815.2406119
  • 接收时间:2024-08-15
  • 首发时间:2025-07-09
  • 出版时间:2025-05-08
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  • 收稿日期:2024-08-15
  • 修回日期:2025-01-09
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中央级公益性科研院所基本科研业务费专项(2023YSKY-40)
黄河流域生态保护和高质量发展联合研究项目(2022-YRUC-01-0301)
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    1 中国环境科学研究院固体废物污染控制技术研究所, 北京 100012
    2 国家黄河流域生态保护和高质量发展联合研究中心, 北京 100012
    3 北京师范大学水科学研究院, 北京 100085

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* 迭庆杞(1988—),男,汉族,河南南阳人,博士,副研究员。研究方向:固体废物环境管理和风险评估。E-mail:
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2种不同金属材料的力学参数

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属数
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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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