Article(id=1276897078227890610, tenantId=1146029695717560320, journalId=1273696621738037261, issueId=1276896822652174534, articleNumber=null, orderNo=null, doi=10.13205/j.hjgc.202603010, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1767024000000, receivedDateStr=2025-12-30, revisedDate=1768579200000, revisedDateStr=2026-01-17, acceptedDate=1768838400000, acceptedDateStr=2026-01-20, onlineDate=1782365587049, onlineDateStr=2026-06-25, pubDate=1774108800000, pubDateStr=2026-03-22, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782365587049, onlineIssueDateStr=2026-06-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782365587049, creator=13701087609, updateTime=1782365587049, updator=13701087609, issue=Issue{id=1276896822652174534, tenantId=1146029695717560320, journalId=1273696621738037261, year='2026', volume='44', issue='3', pageStart='1', pageEnd='206', issueExtLink='null', onlineDate='null', pubDate='1774108800000', pubDateStr='2026-03-22', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1782365526116, creator='13701087609', updateTime=1782722557449, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1278394320713589676, tenantId=1146029695717560320, journalId=1273696621738037261, issueId=1276896822652174534, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1278394320713589677, tenantId=1146029695717560320, journalId=1273696621738037261, issueId=1276896822652174534, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=112, endPage=124, ext={EN=ArticleExt(id=1276897078425022900, articleId=1276897078227890610, tenantId=1146029695717560320, journalId=1273696621738037261, language=EN, title=Pollution characteristics and priority substance screening of PFASs in typical drinking water systems of the lower Yangtze River, columnId=null, journalTitle=Environmental Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Per- and polyfluoroalkyl substances (PFASs) are frequently detected at elevated concentrations in water bodies of the lower Yangtze River, posing risks to drinking water safety and human health. This study investigated the occurrence of 23 typical PFASs in source water, treated water, and tap water from eight drinking water treatment plants (DWTPs) in the lower reaches of the Yangtze River. The removal efficiency of PFASs by the treatment processes and their priority for control were also assessed. The results revealed the presence of 19 PFASs across the eight DWTPs, with total concentrations ranging from 32.02 to 167.68 ng/L and an average of 85.86 ng/L. Among these, 14 long-chain and 5 short-chain PFASs were identified, contributing 35.7% and 64.3% to the total concentration, respectively, indicating that short-chain PFASs were the predominant pollutants. The major contaminant monomers were perfluorooctanoic acid (PFOA), perfluorobutanoic acid (PFBA), perfluorobutanesulfonic acid (PFBS), and perfluorohexanoic acid (PFHxA). The overall removal efficiency of PFASs by the drinking water treatment processes was 17.8%, with a removal efficiency of 22.2% for long-chain and 15.1% for short-chain congeners. Notably, concentrations of 14 PFASs increased during distribution from the treatment plant to the tap, resulting in an overall rebound rate of 39.6%. PFBA, PFOA, and PFBS were the primary contributors, accounting for over 92.8% of this concentration increase. Modeling assessment identified PFOA, perfluorononanoic acid (PFNA), perfluorododecanoic acid (PFDoA), and perfluorooctanesulfonic acid (PFOS) as priority PFASs requiring enhanced monitoring and control measures.

, authors=null, authorsList=Wei YOU, Dingxin LIU, Weiliang ZHANG, Zhichen MA, Lü ZHOU, Jingyang LUO, Jianchao LIU, authorCompany=null, correspAuthors=null, 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, fund=null), CN=ArticleExt(id=1276897079884640706, articleId=1276897078227890610, tenantId=1146029695717560320, journalId=1273696621738037261, language=CN, title=长江下游典型饮用水系统中全氟化合物的污染特征与优控物质筛查, columnId=1276896823583310025, journalTitle=环境工程, columnName=水环境与水生态, runingTitle=null, highlight=null, articleAbstract=

全氟化合物(PFASs)在长江下游水体中被频繁检出,且赋存水平偏高,影响饮用水安全与人体健康。针对23种典型的PFASs,在长江下游8座饮用水处理厂开展了水源水、出厂水和龙头水中PFASs的赋存特征调查研究,评估了PFASs在饮用水处理厂中的去除效能和优先控制等级。结果表明:在8座饮用水处理系统中共检出19种PFASs,总浓度为32.02~167.68 ng/L,平均浓度为85.86 ng/L。其中,长链PFASs检出14种,浓度占比35.7%;短链PFASs共检出5种,浓度占比64.3%,短链PFASs是饮用水处理系统中主要污染物。全氟辛酸(PFOA)、全氟丁酸(PFBA)、全氟丁烷磺酸(PFBS)和全氟己酸(PFHxA)是饮用水系统中主要的污染单体。此外,饮用水处理工艺对于PFASs的总去除率为17.8%,其中长链和短链PFASs的去除率分别为22.2%和15.1%。从出厂水至龙头水的输配过程中,共有14种PFASs出现再增加现象,PFASs检出浓度整体回升率达到39.6%,主要为PFBA、PFOA和PFBS,三者对浓度回升的合计贡献率超过92.8%。模型评估发现,全氟辛酸(PFOA)、全氟壬酸(PFNA)、全氟十二酸(PFDoA)和全氟辛烷磺酸(PFOS)是需要重点关注的PFASs,应加大监测力度并优先管控。

, authors=

尤为(1986—),男,工程师,主要研究方向为水质监测。

, authorsList=尤为, 刘丁心, 张炜亮, 马智宸, 周率, 罗景阳, 刘建超, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=
刘建超(1985—),男,教授,主要研究方向为新污染物环境行为及治理。
罗景阳(1989—),男,教授,主要研究方向为有机固废资源化与新污染物环境影响行为。
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尤为(1986—),男,工程师,主要研究方向为水质监测。

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尤为(1986—),男,工程师,主要研究方向为水质监测。

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Information of target compounds

, figureFileSmall=null, figureFileBig=null, tableContent=
编号英文缩写全称CAS号链长类别
1PFBA全氟丁酸375-22-44全氟羧酸
2PFBS全氟丁烷磺酸375-73-54全氟磺酸
3PFPeA全氟戊酸2706-90-35全氟羧酸
4PFPeS全氟戊基磺酸2706-91-45全氟磺酸
5PFHxA全氟己酸307-24-46全氟羧酸
6PFHxS全氟己烷磺酸355-46-46全氟磺酸
7PFHpA全氟庚酸375-85-97全氟羧酸
8PFHpS全氟庚烷磺酸375-92-87全氟磺酸
9ADONA卡络磺钠51460-26-57全氟羧酸
10PFOA全氟辛酸335-67-18全氟羧酸
11PFOS全氟辛烷磺酸1763-23-18全氟磺酸
129Cl-PF3ONS9-氯十六氟-3-氧烷酮-1-磺酸钾73606-19-68全氟磺酸
13PFNA全氟壬酸375-95-19全氟羧酸
14PFNS全氟壬磺酸钠98789-57-29全氟磺酸
15PFDA全氟癸酸335-76-210全氟羧酸
16PFDS全氟癸烷磺酸钠盐335-77-310全氟磺酸
1711-Cl-PF3OUdS11-氯二十氟-3-氧代十二烷-1-磺酸钾73606-19-610全氟磺酸
18PFUdA全氟十一酸2058-94-811全氟羧酸
19PFDoA全氟十二酸307-55-112全氟羧酸
20PFTrDA全氟十三酸72629-94-813全氟羧酸
21PFTeDA全氟十四酸376-06-714全氟羧酸
22PFHxDA全氟十六酸67905-19-515全氟羧酸
23PFODA全氟十八酸16517-11-616全氟羧酸
), ArticleFig(id=1277266651007553692, tenantId=1146029695717560320, journalId=1273696621738037261, articleId=1276897078227890610, language=CN, label=表1, caption=

目标化合物信息

, figureFileSmall=null, figureFileBig=null, tableContent=
编号英文缩写全称CAS号链长类别
1PFBA全氟丁酸375-22-44全氟羧酸
2PFBS全氟丁烷磺酸375-73-54全氟磺酸
3PFPeA全氟戊酸2706-90-35全氟羧酸
4PFPeS全氟戊基磺酸2706-91-45全氟磺酸
5PFHxA全氟己酸307-24-46全氟羧酸
6PFHxS全氟己烷磺酸355-46-46全氟磺酸
7PFHpA全氟庚酸375-85-97全氟羧酸
8PFHpS全氟庚烷磺酸375-92-87全氟磺酸
9ADONA卡络磺钠51460-26-57全氟羧酸
10PFOA全氟辛酸335-67-18全氟羧酸
11PFOS全氟辛烷磺酸1763-23-18全氟磺酸
129Cl-PF3ONS9-氯十六氟-3-氧烷酮-1-磺酸钾73606-19-68全氟磺酸
13PFNA全氟壬酸375-95-19全氟羧酸
14PFNS全氟壬磺酸钠98789-57-29全氟磺酸
15PFDA全氟癸酸335-76-210全氟羧酸
16PFDS全氟癸烷磺酸钠盐335-77-310全氟磺酸
1711-Cl-PF3OUdS11-氯二十氟-3-氧代十二烷-1-磺酸钾73606-19-610全氟磺酸
18PFUdA全氟十一酸2058-94-811全氟羧酸
19PFDoA全氟十二酸307-55-112全氟羧酸
20PFTrDA全氟十三酸72629-94-813全氟羧酸
21PFTeDA全氟十四酸376-06-714全氟羧酸
22PFHxDA全氟十六酸67905-19-515全氟羧酸
23PFODA全氟十八酸16517-11-616全氟羧酸
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Optimized mass spectrometry parameters for 23 PFASs

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化合物保留时间/min母离子m/z子离子m/z驻留时间/s锥孔电压/V碰撞能/V
PFBA3.2213169.00/119.000.0223016/12
PFPeA3.6263219.00/169.000.0223218/14
PFHxA4.1313269.00/169.000.0213420/16
PFHpA4.6363319.00/169.000.0213220/16
ADONA4.8377333.00/169.000.0213018/14
PFOA5413369.00/169.000.0213422/18
PFNA5.5463419.00/169.000.0223422/18
PFDA6513469.00/169.000.0223624/18
PFUdA6.5563519.00/169.000.0223624/18
PFDoA7613569.00/169.000.0233626/20
PFTrDA7.5663619.00/169.000.0233828/22
PFTeDA8713669.00/169.000.0233828/22
PFHxDA8.5813769.00/169.000.0244030/24
PFODA9913869.00/169.000.0244230/24
PFBS2.829980.00/99.000.0212818/14
PFPeS3.334980.00/99.000.0213020/16
PFHxS3.839980.00/99.000.0213222/16
PFHpS4.244980.00/99.000.0213222/16
PFOS4.649980.00/99.000.0223424/18
9Cl-PF3ONS5.2530.9421.90/99.000.0223624/18
PFNS4.8449169.00/99.000.0223422/16
PFDS5.559980.00/99.000.0223626/20
11Cl-PF3OUdS6630.9530.90/99.000.0233828/22
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23种PFASs的质谱优化参数

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化合物保留时间/min母离子m/z子离子m/z驻留时间/s锥孔电压/V碰撞能/V
PFBA3.2213169.00/119.000.0223016/12
PFPeA3.6263219.00/169.000.0223218/14
PFHxA4.1313269.00/169.000.0213420/16
PFHpA4.6363319.00/169.000.0213220/16
ADONA4.8377333.00/169.000.0213018/14
PFOA5413369.00/169.000.0213422/18
PFNA5.5463419.00/169.000.0223422/18
PFDA6513469.00/169.000.0223624/18
PFUdA6.5563519.00/169.000.0223624/18
PFDoA7613569.00/169.000.0233626/20
PFTrDA7.5663619.00/169.000.0233828/22
PFTeDA8713669.00/169.000.0233828/22
PFHxDA8.5813769.00/169.000.0244030/24
PFODA9913869.00/169.000.0244230/24
PFBS2.829980.00/99.000.0212818/14
PFPeS3.334980.00/99.000.0213020/16
PFHxS3.839980.00/99.000.0213222/16
PFHpS4.244980.00/99.000.0213222/16
PFOS4.649980.00/99.000.0223424/18
9Cl-PF3ONS5.2530.9421.90/99.000.0223624/18
PFNS4.8449169.00/99.000.0223422/16
PFDS5.559980.00/99.000.0223626/20
11Cl-PF3OUdS6630.9530.90/99.000.0233828/22
), ArticleFig(id=1277266651259211935, tenantId=1146029695717560320, journalId=1273696621738037261, articleId=1276897078227890610, language=EN, label=Tab.3, caption=

Classification of grade score coefficients based on geometric interval classification and the 2/3 cumulative rank method

, figureFileSmall=null, figureFileBig=null, tableContent=
区间等级秩排序累计秩排序(2/3)^COR得分系数/%
1001.0000100.00
2110.666766.67
3230.296329.63
4360.08788.78
54100.01731.73
), ArticleFig(id=1277266651322126496, tenantId=1146029695717560320, journalId=1273696621738037261, articleId=1276897078227890610, language=CN, label=表3, caption=

基于等比分组与2/3累计秩法的等级得分系数划分

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区间等级秩排序累计秩排序(2/3)^COR得分系数/%
1001.0000100.00
2110.666766.67
3230.296329.63
4360.08788.78
54100.01731.73
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长江下游典型饮用水系统中全氟化合物的污染特征与优控物质筛查
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尤为 1 , 刘丁心 1 , 张炜亮 2 , 马智宸 3 , 周率 3 , 罗景阳 2 , 刘建超 2
环境工程 | 水环境与水生态 2026,44(3): 112-124
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环境工程 |水环境与水生态 2026 , 44 (3) : 112 -124
长江下游典型饮用水系统中全氟化合物的污染特征与优控物质筛查
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尤为1 , 刘丁心1, 张炜亮2, 马智宸3, 周率3, 罗景阳2 , 刘建超2
作者信息
  • 1江苏城镇给排水监测有限公司,南京 210036
  • 2河海大学 环境学院 浅水湖泊综合治理与资源开发;教育部重点实验室,南京 210098
  • 3南京市供水节水指导中心,南京 210004
通讯作者:
刘建超(1985—),男,教授,主要研究方向为新污染物环境行为及治理。
罗景阳(1989—),男,教授,主要研究方向为有机固废资源化与新污染物环境影响行为。
Pollution characteristics and priority substance screening of PFASs in typical drinking water systems of the lower Yangtze River
Wei YOU1 , Dingxin LIU1, Weiliang ZHANG2, Zhichen MA3, Lü ZHOU3, Jingyang LUO2 , Jianchao LIU2
Affiliations
  • 1Jiangsu Urban Water Supply and Drainage Monitoring Co.,Ltd.,Nanjing 210036,China
  • 2Key Laboratory for Integrated Regulation and Resources Development on Shallow Lakes,Ministry of Education,College of Environment,Hohai University,Nanjing 210098,China
  • 3Nanjing Water Supply and Water Conservation Guidance Center,Nanjing 210004,China
出版时间: 2026-03-22 doi: 10.13205/j.hjgc.202603010
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全氟化合物(PFASs)在长江下游水体中被频繁检出,且赋存水平偏高,影响饮用水安全与人体健康。针对23种典型的PFASs,在长江下游8座饮用水处理厂开展了水源水、出厂水和龙头水中PFASs的赋存特征调查研究,评估了PFASs在饮用水处理厂中的去除效能和优先控制等级。结果表明:在8座饮用水处理系统中共检出19种PFASs,总浓度为32.02~167.68 ng/L,平均浓度为85.86 ng/L。其中,长链PFASs检出14种,浓度占比35.7%;短链PFASs共检出5种,浓度占比64.3%,短链PFASs是饮用水处理系统中主要污染物。全氟辛酸(PFOA)、全氟丁酸(PFBA)、全氟丁烷磺酸(PFBS)和全氟己酸(PFHxA)是饮用水系统中主要的污染单体。此外,饮用水处理工艺对于PFASs的总去除率为17.8%,其中长链和短链PFASs的去除率分别为22.2%和15.1%。从出厂水至龙头水的输配过程中,共有14种PFASs出现再增加现象,PFASs检出浓度整体回升率达到39.6%,主要为PFBA、PFOA和PFBS,三者对浓度回升的合计贡献率超过92.8%。模型评估发现,全氟辛酸(PFOA)、全氟壬酸(PFNA)、全氟十二酸(PFDoA)和全氟辛烷磺酸(PFOS)是需要重点关注的PFASs,应加大监测力度并优先管控。

长江水体  /  饮用水系统  /  全氟化合物(PFASs)  /  去除效能  /  优控物质

Per- and polyfluoroalkyl substances (PFASs) are frequently detected at elevated concentrations in water bodies of the lower Yangtze River, posing risks to drinking water safety and human health. This study investigated the occurrence of 23 typical PFASs in source water, treated water, and tap water from eight drinking water treatment plants (DWTPs) in the lower reaches of the Yangtze River. The removal efficiency of PFASs by the treatment processes and their priority for control were also assessed. The results revealed the presence of 19 PFASs across the eight DWTPs, with total concentrations ranging from 32.02 to 167.68 ng/L and an average of 85.86 ng/L. Among these, 14 long-chain and 5 short-chain PFASs were identified, contributing 35.7% and 64.3% to the total concentration, respectively, indicating that short-chain PFASs were the predominant pollutants. The major contaminant monomers were perfluorooctanoic acid (PFOA), perfluorobutanoic acid (PFBA), perfluorobutanesulfonic acid (PFBS), and perfluorohexanoic acid (PFHxA). The overall removal efficiency of PFASs by the drinking water treatment processes was 17.8%, with a removal efficiency of 22.2% for long-chain and 15.1% for short-chain congeners. Notably, concentrations of 14 PFASs increased during distribution from the treatment plant to the tap, resulting in an overall rebound rate of 39.6%. PFBA, PFOA, and PFBS were the primary contributors, accounting for over 92.8% of this concentration increase. Modeling assessment identified PFOA, perfluorononanoic acid (PFNA), perfluorododecanoic acid (PFDoA), and perfluorooctanesulfonic acid (PFOS) as priority PFASs requiring enhanced monitoring and control measures.

Yangtze River water bodies  /  drinking water system  /  per- and polyfluoroalkyl substances (PFASs)  /  removal efficiency  /  priority substances
尤为, 刘丁心, 张炜亮, 马智宸, 周率, 罗景阳, 刘建超. 长江下游典型饮用水系统中全氟化合物的污染特征与优控物质筛查. 环境工程, 2026 , 44 (3) : 112 -124 . DOI: 10.13205/j.hjgc.202603010
Wei YOU, Dingxin LIU, Weiliang ZHANG, Zhichen MA, Lü ZHOU, Jingyang LUO, Jianchao LIU. Pollution characteristics and priority substance screening of PFASs in typical drinking water systems of the lower Yangtze River[J]. Environmental Engineering, 2026 , 44 (3) : 112 -124 . DOI: 10.13205/j.hjgc.202603010
全氟烷基与多氟烷基化合物(perfluoroalkyl and polyfluoroalkyl substances,PFASs)是一类合成有机化合物,其碳主链上的氢原子被氟原子完全或部分取代1。碳氟键是自然界中最强的单键之一,这种极高的键能赋予PFASs极高的化学和热稳定性,使其能够抵抗水解、光解或微生物降解等自然过程的分解23。同时,PFASs分子通常具有亲水性的末端官能团(如羧基或磺酸基),并与疏水、抗油的氟化碳链相连,这种两亲性结构使其成为高效表面活性剂,能显著降低水的表面张力45。此外,PFASs强韧的碳氟键使其更易与生物体内的蛋白质(如血清蛋白)结合,而非像传统疏水性污染物(如多氯联苯)在脂肪组织中富集。其独特的生物积累机制使PFASs能通过食物链在生物体内持续富集,并在人体长期滞留,引发免疫系统功能受损、内分泌紊乱以及癌症风险上升6
在PFASs中,碳链≥7的全氟羧酸(PFCAs)和碳链≥6的全氟磺酸(PFSAs)统称为长链PFASs,反之则为短链PFASs7。长链PFASs具有环境持久性高、生物积累性强等特点,但其迁移性低,易吸附在排放点附近的土壤、沉积物中89。长链PFASs具有肝毒性、发育毒性、免疫毒性、致癌性等特性,高暴露PFASs如PFOS和PFOA已被列入《关于持久性有机污染物的斯德哥尔摩公约》管控清单,其已经在全球范围内被严格限制及淘汰1011。虽然短链PFASs生物积累性相对偏低,但其迁移性和环境持久性强,能够穿透土壤层,在地表水和地下水进行长距离输移、扩散1213
长江是我国最重要的饮用水供给水源,是沿江数亿人民的生命线,也是跨流域调水的重要供给区,但长江流域水质安全面临着工业废水、农业面源污染、生活污水、航运污染等多重风险威胁14。典型持久性有机物PFASs赋存水平高,暴露风险明显,在2025年在太湖流域饮用水源水中检测了20种PFASs,总浓度范围为7.17~377 ng/L,其中PFOA检出浓度最高,复合污染现状明显15。中国2022年实施的GB 5749—2022《生活饮用水卫生标准》已将PFOA与PFOS列入扩展指标并设定限值(分别为80,40 ng/L)10,但长江流域内水源水中PFASs的监测体系、管控措施、健康风险等相关研究仍十分匮乏。
在饮用水厂的实际运行中,水源水、出厂水与龙头水共同构成了PFASs从环境到人体的关键暴露路径。现有研究表明,水源水普遍受到工农业排放及城市活动的直接影响,是PFASs进入供水系统的初始来源。在常规饮用水处理工艺(如混凝、沉淀、过滤、消毒)过程中,PFASs因其极高的化学稳定性难以被有效去除,导致部分污染物穿透处理屏障进入出厂水。值得注意的是,在出厂水经管网输送至用户端的过程中,管网材料释放、二次供水设施污染或残留污染物的解吸可能导致龙头水中PFASs种类与浓度的显著变化,甚至出现浓度“回升”现象,进一步增加了终端饮用水的健康风险。目前,针对同一供水系统中3类水样的系统监测与对比研究仍较为缺乏,难以全面揭示PFASs在“水源—水厂—管网”全流程中的迁移转化规律与暴露风险,制约饮用水系统中PFASs的全过程精准管控。
本研究在长江下游流域选择了8座饮用水处理系统,开展了水源水、出厂水及龙头水中23种PFASs污染物的分析测定,解析了PFASs在饮用水系统中的赋存特征、去除效能及综合风险,明确了该区域饮用水系统中重点管控的PFASs对象,为饮用水系统中PFASs污染的科学认知和精准管控提供支持。
氯甲烷、乙腈、甲醇均为色谱纯试剂,购自Merck公司(美国);实验用水为优普超纯水制造系统(四川优普超纯科技有限公司);WAX固相萃取柱 (200 mg,6 mL)、HLB固相萃取柱(200 mg,6 mL),购自Waters公司(美国);聚碳酸酯滤膜(5 μm),购自Millipore(美国)公司;无菌注射器(1 mL),购自南京荣华科学器材有限公司;有机相针式滤器(0.22 μm, 尼龙66),购自南京荣华科学器材有限公司;23种PFASs标准品购于Sigma-Aldrich(Flanders, USA),纯度均≥99%,目标化合物信息见表1
以长江干流南京至上海段为研究区域,共选取8家饮用水处理厂(S1—S8),位置如图1所示。在每座水厂的取水口、出水口和管网末梢分别取水源水、出厂水以及龙头水。采集水样使用预先清洗和消毒过的高密度聚乙烯(HDPE)采样瓶盛放,每个样点的采样量为5 L,采集后立即将样品置于低温(0~4 ℃)条件下避光保存,低温状态运输至实验室,48 h内完成样品前处理。
水样经0.45 μm孔径聚碳酸酯滤膜过滤去除颗粒物,得到的水相样品用Waters Oasis WAX固相萃取小柱(200 mg, 6 mL)富集。萃取前,固相萃取柱先用5 mL 0.1% (体积分数)氨-甲醇溶液、5 mL甲醇和5 mL超纯水依次活化,保持小柱浸润;活化完成后以3~5 mL/min的速率过滤水样,之后真空抽干20 min,去除残留水分。然后用5 mL 0.1%(体积分数)氨-甲醇溶液和5 mL甲醇对小柱进行洗脱,速度保持在1 mL/min。洗脱液氮吹至近干后,用甲醇定容至1 mL,然后过0.22 μm有机相针式滤膜,盛放于2 mL进样瓶中,于-20 ℃条件下保存待测。
色谱条件:目标化合物的定量分析采用超高效液相色谱-串联质谱仪(UPLC-MS/MS)进行,色谱部分使用Waters ACQUITY UPLC系统(美国Waters公司),配备ACQUITY BEH C18色谱柱(2.1 mm × 100 mm,1.7 μm,美国Waters公司)。色谱条件为柱温40 ℃,样品室温度10 ℃,进样量为5 μL,流速为0.3 mL/min,使用梯度洗脱方法对不同目标化合物进行分离。针对PFASs,采用2 mmol/L醋酸铵溶液(pH值为7.5)为流动相A,乙腈为流动相B;具体流动相梯度和洗脱参数为:在0~1 min内,保持流动相A∶B比例为80∶20(等度洗脱);随后在1~3.5 min内,将流动相A的比例从80%线性降低至20%(即流动相B从20%升至80%);紧接着在3.5~4.5 min内,将流动相A进一步线性降至5%(流动相B升至95%),并维持此比例至5 min;之后在5~5.5 min内,迅速将流动相A的比例线性恢复至初始的80%;最后,在5.5~6 min内以80∶20的比例进行柱平衡。
质谱部分采用Waters Acquity Xevo TQ三重四级杆串联质谱仪,搭载电喷雾离子源(ESI),结合多反应监测(MRM)模式进行目标化合物的定量分析。质谱检测条件为毛细管电压2.5 kV,碰撞气体流速0.16 mL/min,离子源温度150 ℃,锥孔反吹气流量50 L/h,脱溶剂气温度500 ℃,脱溶剂气流量800 L/h。检测模式根据目标物的化学性质采用正负离子模式。PFASs以负离子模式检测。目标化合物的母离子、子离子及碰撞能等具体质谱参数记录见表2
为了确保饮用水中PFASs的测定结果准确可靠,本研究在样品分析过程中,通过设置空白对照和基质加标实验以验证方法的准确性和可靠性。饮用水样品的加标浓度设置为10,100 ng/L,并进行3次平行样测定,计算加标回收率和方法的相对标准偏差(RSD)。结果表明:所有目标化合物的加标回收率为86.1%~97.1%,相对标准偏差(RSD)均低于6%,表明分析方法具有良好的准确性和重复性。
检测方法的灵敏性通过检出限(LODs)和定量限(LOQs)进行评估。LODs定义为3倍信噪比(S/N)的浓度,LOQs定义为10倍信噪比浓度。目标全氟化合物的LODs为0.010~0.030 ng/L,LOQs为0.033~0.083 ng/L。样品基质的LODs和LOQs通过方法检出限与定量限除以相应的基质体积计算得出。
PFASs的持久性通过生物降解系数(BioWIN)来衡量,该数据取自美国环保署的EPI Suite 软件,BioWIN的值越小时,污染物的持久性越强。生物积累性用正辛醇/水分配系数(Kow)来评估,本研究使用pH=7时的正辛醇/水分配系数(lgKow)校正化学形态对生物积累性的影响,数据取自SciFinder数据库(https://scifinder-n.cas.org)。
采用欧盟技术导则中的风险熵值法(RQ)作为量化表征的手段,评估水体中有机微污染物对水生生物系统造成的负面影响16,计算式为:
RQwater=MECPNECwater
式中:RQwater为污染物的生态风险熵,无量纲;MEC为水环境中污染物的实测浓度,ng/L;PNECwater为污染物在水体中的预测无效应浓度,ng/L。
为了更好地反映污染物在生态系统水平的负面效应,使用单因子评价法计算PNEC,计算式为:
PNECwater=LC50AF
式中:LC50为半致死浓度;AF为评估因子。
在人类健康风险评价的过程中,通常以个体在不同暴露途径下接触污染物时所存在的危害水平为评价目标。采用风险熵值法(RQ)作为量化表征的手段评估水体中有机微污染物对人体健康造成的负面影响,计算公式为:
RQhum=MECPNEChum
式中:RQhum为污染物的人体风险熵,无量纲;MEC为水环境中污染物的实测浓度,ng/L;PNEChum为污染物针对人类的预测无效应浓度,ng/L。
为了更准确地表征有机微污染物的人类健康效应,选用具有代表性暴露途径的PNEChum17,计算见式(4)。
PNEChum=1000×ADI×BW×AT(IngRDW+BCF×IngRF)×EF×ED
式中:1000为转换因子;BW为体重,中国成年人平均体重为63 kg;AT为成年人平均暴露时间,10950 d;IngRDW为成人饮水摄取量,2 L/(人·d);BCF为鱼类生物富集系数,从美国环保署Chemistry Dashboard数据库获得;lngRF为人均水产品消费量,用于估算食用水产品可能造成的健康风险,取92.6 g/d;EF为暴露频率,取350 d/a;ED为暴露时间,取30 a;ADI为每日可允许摄入量,数据来源于国标、数据库、文献或模型模拟。
1)指标归类:暴露风险(EP)(包括检出浓度和检出率)和危险风险(HP)(包括持久性、生物积累、生态风险和人类健康风险)。
2)评分:根据已有研究1618,借鉴US EPA用于确定污染物毒性得分的需通报量法,本研究采用综合评估法进行赋分,涵盖EP与HP 2个维度(各100分)。EP包括检出浓度和检出率(各50分),HP包括持久性、生物积累性、生态风险和人类健康风险(各25分)。各指标基于实测数据范围,通过等比级数法划分为5个等级,并依据2/3累计秩法确定等级标准得分(表3)。其中,检出浓度、检出率、生物积累性、生态风险和人类健康风险属于正向计分,持久性属于负向计分。
3)等级划分:如多项已有研究所述1920,为避免主观判断带来的差异,在计算中各项指标均被赋予相应的权重,最终得分等于EP得分与HP得分之和。排序使用计算总分组的四分位数,最大值与较大四分位数(由大到小排序后第25%的分值)之间的被列为高优先级污染物,即优控污染物21
在8座饮用水系统中共检出19种PFASs,总浓度达为32.02~167.68 ng/L,平均浓度为85.86 ng/L,主要污染单体包括PFBA、PFOA、PFBS、PFHxA、PFHpA、PFPeA等(见图2a),其中ADONA、PFNS、PFHxDA和PFODA 4种PFASs未检出。在检出的19种PFASs中,长链和短链PFASs单体数量占比分别为73.7%和26.3%,而二者浓度占比分别为35.5%和64.5%,短链PFASs是长江下游水源地中PFASs的主要贡献者。从PFASs单体检出浓度来看,PFBA、PFBS、PFHxA和PFOA这4种PFASs是饮用水系统中最主要的污染单体,均值浓度分别为28.29,14.02,11.23,22.90 ng/L,4种污染物浓度占PFASs总浓度的89.0%以上,表明长江流域下游水体中PFASs污染种类多样,但主要污染物种类相对清晰22。相较于传统PFASs,饮用水系统中还检出了9Cl-PF3ONS和11Cl-PF3OUdS 新型PFASs,这2种新型PFASs是我国电镀行业中常用的铬酸雾抑制剂的主要成分,具有强持久性、生物积累性和毒性,可通过水循环、大气颗粒物等途径进行长距离迁移,导致区域性污染,是重点关注的新型污染物723
与国内外其他区域(图2b)相比,长江下游水体中PFASs的污染水平与淮河相当,淮河水体中PFASs的平均浓度为75.8 ng/L,二者均显著高于国外区域,表明长江下游和淮河水体中PFASs的污染程度及环境累积效应更为严重24。长江下游水体中PFASs的污染水平为瑞典(36.41 ng/L)25、美国(16.15 ng/L)26、乌干达(5.12 ng/L)8、挪威(4.65 ng/L)27和加拿大(0.80 ng/L)28的3~100倍。PFASs污染类型方面,主要呈现共性与特性并存的特征。在区域共性方面,所有区域均存在传统长链PFASs(PFOA、PFOS)的普遍遗留及短链替代物(如PFBS、PFBA、PFHxA)的广泛检出。在区域特性方面,主要分为3类:第1类以全氟磺酸类(PFSA)为主导,以挪威(PFOS突出)、瑞典(PFOS与PFHxS并存)及美国大湖区(PFHxA高,但PFSA背景显著)为代表,体现了明显的点源污染特征。第2类以全氟羧酸类(PFCA)为主导,以乌干达(PFHxA/PFOA主导)和加拿大魁北克(多种短链PFCAs并存)为典型,其主要由于短链PFCA及其前体物经转化与迁移后的扩散面源模式,反映了PFAS替代品使用的普遍影响。第3类以中国长江下游及淮河流域为代表的高度复杂混合特征区域,其表现为短链PFASs(如PFBA、PFPeA)浓度贡献突出,同时叠加显著的长链残留(PFOA)及本地特色工业排放(如长江中检出氯代PFASs等新型污染物),表明该区域正处于产业结构转型期,新旧污染物交织,点源与面源污染并存的复杂环境现状。这主要与不同国家的PFASs生产、使用及管控政策密切相关:北欧国家(瑞典、挪威)和加拿大早于全球多数地区实施PFASs限制法规,对PFASs设定了严格的限值标准29;美国作为PFASs生产大国,近年来也加强了PFASs污染的管控与治理30;而乌干达作为发展中国家,工业活动强度较低,PFASs人为输入量有限,因此污染水平普遍较低8
在水源水中共检出的19种PFASs,总浓度为58.76~167.68 ng/L,平均总浓度为86.76 ng/L(图3a),其中PFOA、PFBA、PFBS和PFHxA平均浓度分别达到24.96,24.03,14.95,12.55 ng/L,4种物质对PFASs总浓度的贡献率达到88.2%。检出的19种PFASs中,长链PFASs有14种,其中PFOA、PFNA、PFOS和PFDA等9种长链PFASs检出率达100%,∑14PFASs浓度为19.66~64.08 ng/L,均值总浓度为33.08 ng/L,贡献率超过38.1%。检出的19种PFASs中,短链PFASs有5种,分别为PFBA、PFPeA、PFBS、PFHxA和PFPeS,检出率均为100%,其总浓度范围(∑5PFASs)为20.71~121.78 ng/L,平均总浓度达到53.68 ng/L,贡献占比达到61.9%,短链PFASs的污染贡献显著高于长链。2024年太湖流域饮用水源地调查发现,水源水中检出38种PFASs,总浓度为100~747 ng/L,平均总浓度为147 ng/L,其中,主要污染物为PFBA(中位数浓度为28.07 ng/L)、PFHxA(23.45 ng/L)、PFOA(22.04 ng/L)和PFBS(16.39 ng/L)1531。在淮河流域共检出的14种PFASs总浓度达到29.83~217.96 ng/L,平均总浓度为75.82 ng/L,其中PFPeA、PFOA和PFBA的贡献率超过82.5%24,太湖和淮河中PFASs的污染特征与长江相似。短链PFASs在水源水中广泛检出,不仅与长链PFASs在全球范围内限制使用相关3233,还受短链PFASs的高水溶性和强迁移能力的影响3435,短链PFASs在水中更易溶解和扩散,进入饮用水源地,影响水质安全。
PFOA是过去几十年中使用最为广泛的长链PFASs,虽然已被严格限制使用,但其在现存的化工产品中仍然大量存在15,且同时是部分长链PFASs的降解产物10。PFBA和PFHxA作为PFOA的短链替代品,在纺织、皮革、造纸、包装材料等领域广泛应用,而PFBS在电镀、消防泡沫、半导体行业大量使用36。此外,9Cl-PF3ONS和11Cl-PF3OUdS作为新型PFASs在水源水中被检出,均值浓度分别为0.25,0.04 ng/L,检出率分别为100%和25%,表明这2种PFASs已在工业生产中逐渐应用,需持续关注7
从水源地的空间分布(图3b)来看,S7点位水源地中PFASs的浓度最高,平均浓度为167.68 ng/L,为其他点位的2倍以上,呈明显的污染物源排放热点。首先,S7点位临近经济技术开发区及沿江化工、电镀等潜在排放企业,工业废水中的PFASs可以通过直接或间接途径进入水体。其次,S7点上游有河道汇入,该河道途经工业与城镇区域,是污染物入江的重要通道。从PFASs单体组成(图3c)来看,PFHxA是导致S7号点位PFASs显著增高的主要原因,贡献率从S6点的8.0%,增加到了S7点的40.5%。PFHxA是全氟己酸(C6)基氟化工厂(如C6防水防油剂)在生产或使用过程中降解或排放的典型标志,常见于纺织印染、化工合成及造纸等行业,而这些产业恰是该点位上游长江沿岸经济开发区的支柱企业类型,S7点位PFASs污染的来源,需要在化工园区点源排放和通江河道输入方面开展进一步解析。
此外,上游S1点位以PFOA为绝对主导组分(占比62.2%),反映出该区域仍受历史遗留长链PFASs工业排放的持续影响。S2点位虽仍以PFOA为主(35.8%),但PFBS等短链组分占比显著上升至28.4%,表明短链替代品排放已逐步显现。中游S3点位为污染组分结构转型的关键节点,PFBA占比骤升至47.5%,PFOA占比则下降至19.0%,提示短链PFASs排放源(如纺织、印染等行业)的影响显著增强。位于下游的污染热点S7点位中,PFHxA占比急剧升高至40.5%,结合其毗邻工业园区的区位特征,进一步印证了C6基氟化工相关产业的排放贡献;该点位同时持续检出PFBA(23.8%)与PFOA(19.5%),说明其受到历史遗留污染与新兴短链输入的双重叠加。至最下游S8点位,污染格局呈多元短链混合特征,PFOA占比进一步降至26.7%,而PFHxA(24.8%)、PFBA(23.7%)等短链组分占比显著提升,各类物质分布趋于均衡。总体呈现上游传统长链工业污染,向下游多元短链替代品混合影响的演变格局。
在8座饮用水处理厂出厂水中共检出19种PFASs,总浓度(∑19PFASs)为32.53~97.48 ng/L,平均浓度为71.29 ng/L,其中PFBA、PFPeA、PFBS、PFHxA和PFOA等14种检出率为100%。相对于水源地原水中PFASs的平均总浓度(86.76 ng/L),出厂水中PFASs的平均总浓度降低了17.8%。在检出的19种PFASs中,长链PFASs占14种,其总浓度(∑14PFASs)为7.75~41.37 ng/L,平均浓度为25.74 ng/L,对PFASs总浓度贡献率仅有36.1%,其中PFOA、PFHpA、PFNA和PFOS等9种检出率为100%。此外,检出的5种短链PFASs,其总浓度(∑5PFASs)为24.79~63.23 ng/L,平均浓度为45.56 ng/L,平均总浓度贡献率高达63.9%,PFBA、PFPeA、PFBS、PFHxA和PFPeS等5种短链PFASs在所有出厂水中检出率均为100%,短链PFASs水溶性更强,与活性炭的亲和力更弱,在水处理工艺单元具有更强的穿透性37
PFBA、PFOA、PFBS和PFHxA是出厂水中检出浓度最高的4种PFASs,平均浓度分别为22.30,19.16,14.00,7.85 ng/L,且检出率均达到100%(图4a)。与原水相比,PFBA和PFOA的污染水平排序发生了变化,PFOA的检出浓度从原水的24.96 ng/L降至出厂水的19.16 ng/L,去除率为23.2%;而PFBA的检出浓度从原水的24.03 ng/L降至出厂水的22.30 ng/L,仅降低了7.2%。基于水源水和出厂水数据(图4b)计算,发现PFASs的去除率为-38.2%~93.9%,其中PFTrDA的去除率最高,为93.9%,其次是11Cl-PF3OUdS和PFDA。短链PFASs的平均去除率为15.1%,显著低于长链PFASs的去除率(22.2%)。对于PFBA、PFOA、PFBS和PFHxA检出浓度较高的PFASs,其去除率范围在-11.6%~47.5%,平均去除率仅为16.6%,其中PFHxA的去除率最高,达到47.5%,其次是PFOA(23.2%)、PFBA(7.2%)和PFBS(-11.6%)。PFBS浓度在饮用水处理过程中不降反升,主要归因于其短链PFAS亲水性强,去除效能低,同时处理过程中的前体转化生成与工艺单元内的竞争性解吸附,共同导致了其净增长3839
在8个供水系统龙头水中同样检出19种PFASs,其总浓度范围(∑19PFASs)为32.02~160.47 ng/L,平均浓度为99.54 ng/L(图5a)。PFBA、PFOA、PFBS和PFHxA等13种PFASs检出率为100%。14种长链PFASs的总浓度为9.93~72.29 ng/L,平均总浓度为32.67 ng/L,占龙头水中PFASs总浓度的32.8%;而5种短链PFASs的总浓度为16.64~108.21 ng/L,平均浓度达到66.86 ng/L,占比为67.2%。在龙头水中,PFBA、PFOA、PFBS和PFHxA仍然是最主要的污染物,4种物质单体浓度>10 ng/L,总浓度占比为90.0%。
对比水源水、出厂水和龙头水中PFASs的组分和浓度(图5b),发现饮用水处理过程中PFASs总浓度未发生显著衰减变化。在饮用水输配过程中,PFASs平均总浓度由71.29 ng/L回升至99.54 ng/L,整体回升率达到39.6%,出现了出厂水到龙头水PFASs污染水平增高的趋势。此外,PFASs的组分构成改变,短链PFASs的浓度贡献不断增加,从63.9%增加到了67.2%。相对于出厂水,对于龙头水中PFASs总浓度增加,贡献率最高的主要单体是PFBA(均值浓度:22.30→38.54 ng/L)、PFOA(均值浓度:19.16→24.58 ng/L)、PFBS(均值浓度:14.00→15.52 ng/L)和PFHxA(均值浓度:7.85→10.89 ng/L),其对增加浓度的总贡献率达到92.8%,其中PFBA增高趋势最为明显,占总浓度回升量的57.5%。经过输配水管网后,龙头水中全氟和多氟烷基物质(PFASs)浓度出现回升,主要缘于3个相互关联的机制共同作用:首先,出厂水中携带的PFASs前体物在管网输送过程中与余氯发生氧化转化,生成以短链为主的常见PFASs25;其次,管网系统广泛使用的塑料管道材料(如高密度聚乙烯)及其内衬、密封部件可能含有PFASs或其前体物,在长期水力冲刷和余氯化学作用下持续释放40;此外,管道内壁附着的松散沉积物作为PFASs的蓄积点,在液压扰动或水质条件变化时再悬浮,导致吸附的PFASs重新进入水体41。在此过程中,PFBA、PFOA、PFBS和PFHxA对浓度回升的贡献率最为突出,这主要与其物理化学特性和环境行为密切相关。短链的PFBA、PFBS和PFHxA因碳链较短、疏水性弱,在水相中溶解度高且迁移性强,不易被管壁吸附,同时与溶解性有机碳(DOC)的相互作用进一步增强了其在水中的稳定性;而长链PFOA虽易被沉积物吸附,但在管网中蓄积量较大,水力扰动下更易解吸释放42。此外,上述化合物在工业生产和消费品中应用广泛,其对应前体物在出厂水中丰度较高,在管网氧化环境中转化效率显著,且与常见管材的交互作用促进了释放过程。因此,龙头水PFAS浓度上升本质上是化学转化、材料释放和水力扰动协同驱动的结果,凸显了在饮用水输配全过程控制PFAS二次污染的重要性43
根据多指标综合风险赋分方法,对饮用水系统中检出的19种PFASs进行了优控排序,其计算过程中PFASs的检出浓度及检出率是综合了饮用水系统中水源水、出厂水及龙头水等所有采样样品的PFASs数据,生态风险是基于水源水中PFASs的水生态风险进行综合赋分,人类健康风险是基于龙头水中PFASs对人类健康风险进行综合赋分。计算结果见图6
结果表明:19种PFASs经过综合风险赋分后的得分为51.24~168.86,得分均值为106.38,其中得分最高的是PFOA,得分最低的为11Cl-PF3OUdS。根据PFASs的得分分布,采用四分位数法将19种物质划分为低优先级Q1(51.24~84.02)、中间优先级Q2(89.39~105.63)、中高优先级Q3(110.47~125.35)和高优先级Q4(133.64~168.86)共4组。
高优先级PFASs主要包括PFOA、PFNA、PFDoA和PFOS共4种,全部属于长链PFASs(图6b)。PFOA(168.86)的得分较高的主要原因是其高的检出浓度和检出频率,二者贡献率达到59.2%,而生态风险和人体健康风险贡献占比达到29.6%,呈环境暴露与多重风险并发的特征。PFNA(151.24)得分的主要贡献是由检出率(33.1%)、人体健康风险(16.5%)和生物积累性(16.5%)共同驱动,表明其高频检出和较强的生物蓄积潜力是需要关注的重点。PFDoA(136.77)的风险主要来源于其强的环境持久性(18.3%)、生物积累性(18.3%)和生态风险(18.3%),属于典型的高环境持久性与高生态风险型物质。PFOS(133.64)与PFNA相似,高检出率(37.4%)和人体健康风险(18.7%)是其优控的核心贡献因子。2023年世界卫生组织WHO下属国际癌症研究机构(IARC)将PFOA归类为对人类致癌物,体现了PFOA极强的人体健康风险。此外,PFOA和PFOS已被列入《关于持久性有机污染物的斯德哥尔摩公约》管控清单,其已经在全球范围内被严格限制及淘汰。GB 5749—2022《生活饮用水卫生标准》也首次将PFOA和PFOS列入扩展指标,并设定限值80, 40 ng/L。此外,Yu等44发现PFNA可通过饮用水在人体内大量累积,且在人体内的半衰期约3.5 a,难以快速清除,带来长期健康风险。
基于优先控制评估结果,为切实管控长江下游饮用水中的PFASs风险,需建立从源头到龙头的全过程防控体系。管理上应对PFOA、PFNA、PFDoA和PFOS这4种高优先级物质实施重点监管,严格控制工业排放。技术层面,水厂需强化深度处理工艺,针对长链PFASs,推广活性炭吸附、膜技术等高效截留工艺,针对难去除的短链物质,研发高级氧化等组合工艺。同时,必须重视输配过程中PFASs浓度回升的问题,加强对管网与二次供水设施的排查与管理,积极推动典型高风险PFASs标准化监管,建立覆盖水源、水厂和管网的全过程监测网络,实现PFASs的精准、高效管控。
本研究针对长江下游段8处饮用水处理系统中的水源水、出厂水和龙头水靶向检测了23种PFASs,共检出19种污染物,其中13种PFASs检出率为100%,检出PFASs总浓度为32.02~167.68 ng/L,平均浓度为85.86 ng/L。PFOA、PFBA、PFBS和PFHxA是饮用水系统中最主要的PFAS污染物,4种物质对PFASs总浓度的贡献率在89.0%以上。在污染空间上来看,水源水中PFAS的污染受典型化工园区污染影响较大,污染组分从上游单一物质主导向多种物质均衡贡献演化。现有的饮用水处理工艺对PFASs的整体去除效能较低(平均去除率为17.8%),尤其是短链PFASs去除率仅为15.1%。在饮用水输配过程中,PFASs平均总浓度由71.29 ng/L回升至99.54 ng/L,整体回升率达到39.6%,有14种PFASs浓度出现不同程度的增高,其中PFBA增高趋势最为明显,占总浓度回升量的57.5%。此外,通过优控排序计算,发现PFOA、PFNA、PFDoA和PFOS是需要重点管控的PFASs物质,应进一步加强饮用水处理工艺的升级改造,并强化饮用水输配过程中PFASs的污染控制。

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2026年第44卷第3期
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doi: 10.13205/j.hjgc.202603010
  • 接收时间:2025-12-30
  • 首发时间:2026-06-25
  • 出版时间:2026-03-22
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  • 收稿日期:2025-12-30
  • 修回日期:2026-01-17
  • 录用日期:2026-01-20
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    1江苏城镇给排水监测有限公司,南京 210036
    2河海大学 环境学院 浅水湖泊综合治理与资源开发;教育部重点实验室,南京 210098
    3南京市供水节水指导中心,南京 210004

通讯作者:

刘建超(1985—),男,教授,主要研究方向为新污染物环境行为及治理。
罗景阳(1989—),男,教授,主要研究方向为有机固废资源化与新污染物环境影响行为。
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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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