An investigation of the leaf retention capacity, efficiency and mechanism for atmospheric particulate matter of five greening tree species in Beijing, China.
Identifieur interne : 000830 ( Main/Exploration ); précédent : 000829; suivant : 000831An investigation of the leaf retention capacity, efficiency and mechanism for atmospheric particulate matter of five greening tree species in Beijing, China.
Auteurs : Jinqiang Liu [République populaire de Chine] ; Zhiguo Cao [République populaire de Chine] ; Songyan Zou [République populaire de Chine] ; Huanhuan Liu [République populaire de Chine] ; Xiao Hai [République populaire de Chine] ; Shihua Wang [République populaire de Chine] ; Jie Duan [République populaire de Chine] ; Benye Xi [République populaire de Chine] ; Guangxuan Yan [République populaire de Chine] ; Shaowei Zhang [République populaire de Chine] ; Zhongkui Jia [République populaire de Chine]Source :
- The Science of the total environment [ 1879-1026 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical : Air Pollutants, Particulate Matter.
- physiology : Plant Leaves, Trees.
- Beijing, Environmental Monitoring, Particle Size.
Abstract
Urban trees have the potential to reduce air pollution, but the retention capacity and efficiency of different tree species for atmospheric particulate matter (PM) accumulation and the underlying mechanism hasn't been well understood. To select tree species with high air purification abilities, the supplementing ultrasonic cleaning (UC) procedure was first introduced into the conventional leaf cleaning methods [single water cleaning (WC) or plus brush cleaning (BC)] for eluting the leaf-retained PM. Further updates to the methodology were applied to investigate the retention capacity, efficiency, and mechanism for PM of five typical greening tree species in Beijing, China. Meanwhile, the particle size distribution of PM on the leaves, the PM retention efficiencies of easily removable (ERP), difficult-to-remove (DRP) and totally removable (TRP) particles on the leaf (AEleaf), and the individual tree scales were estimated. The experimental leaf samples were collected from trees with similar sizes 4 (SDR) and 14days (LDR) after rainfall. When the leaves were cleaned by WC+BC, there was, on average, 29%-46% of the PM remaining on the leaves of different species, which could be removed almost completely if UC was supplemented. From SDR to LDR, the mass of the leaf-retained PM increased greatly, and the particle size distribution changed markedly for all species except for Sophorajaponica. Pinus tabuliformis retains particles with the largest average diameter (34.2μm), followed by Ginkgo biloba (20.5μm), Sabina chinensis (16.4μm), Salix babylonica (16.0μm), and S. japonica (13.1μm). S. japonica and S. chinensis had the highest AEleaf to retain the TRP and ERP of both PM1 and PM1-2.5, respectively. Conversely, S. babylonica and P. tabuliformis could retain both TRP and ERP of PM2.5-5 and PM5-10, and PM>10 and TSP with the highest AEleaf, respectively. In conclusion, our results could be useful in selecting greening tree species with high air purification abilities.
DOI: 10.1016/j.scitotenv.2017.10.314
PubMed: 29127795
Affiliations:
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Electronic address: duanjiebfu@vip.qq.com.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>National Energy R&D Center for Non-food Biomass, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Xi, Benye" sort="Xi, Benye" uniqKey="Xi B" first="Benye" last="Xi">Benye Xi</name><affiliation wicri:level="1"><nlm:affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China. Electronic address: benyexi@bjfu.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yan, Guangxuan" sort="Yan, Guangxuan" uniqKey="Yan G" first="Guangxuan" last="Yan">Guangxuan Yan</name><affiliation wicri:level="1"><nlm:affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and 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retention capacity, efficiency and mechanism for atmospheric particulate matter of five greening tree species in Beijing, China.</title><author><name sortKey="Liu, Jinqiang" sort="Liu, Jinqiang" uniqKey="Liu J" first="Jinqiang" last="Liu">Jinqiang Liu</name><affiliation wicri:level="1"><nlm:affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Cao, Zhiguo" sort="Cao, Zhiguo" uniqKey="Cao Z" first="Zhiguo" last="Cao">Zhiguo Cao</name><affiliation wicri:level="1"><nlm:affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007</wicri:regionArea><wicri:noRegion>Henan 453007</wicri:noRegion></affiliation></author><author><name sortKey="Zou, Songyan" sort="Zou, Songyan" uniqKey="Zou S" first="Songyan" last="Zou">Songyan Zou</name><affiliation wicri:level="1"><nlm:affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory of 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Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007</wicri:regionArea><wicri:noRegion>Henan 453007</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Shihua" sort="Wang, Shihua" uniqKey="Wang S" first="Shihua" last="Wang">Shihua Wang</name><affiliation wicri:level="1"><nlm:affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007</wicri:regionArea><wicri:noRegion>Henan 453007</wicri:noRegion></affiliation></author><author><name sortKey="Duan, Jie" sort="Duan, Jie" uniqKey="Duan J" first="Jie" last="Duan">Jie Duan</name><affiliation wicri:level="1"><nlm:affiliation>National Energy R&D Center for Non-food Biomass, Beijing 100083, China. Electronic address: duanjiebfu@vip.qq.com.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>National Energy R&D Center for Non-food Biomass, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Xi, Benye" sort="Xi, Benye" uniqKey="Xi B" first="Benye" last="Xi">Benye Xi</name><affiliation wicri:level="1"><nlm:affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China. Electronic address: benyexi@bjfu.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yan, Guangxuan" sort="Yan, Guangxuan" uniqKey="Yan G" first="Guangxuan" last="Yan">Guangxuan Yan</name><affiliation wicri:level="1"><nlm:affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007</wicri:regionArea><wicri:noRegion>Henan 453007</wicri:noRegion></affiliation></author><author><name sortKey="Zhang, Shaowei" sort="Zhang, Shaowei" uniqKey="Zhang S" first="Shaowei" last="Zhang">Shaowei Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Henan Vocational College of Agriculture, Zhengzhou, Henan 451450, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Henan Vocational College of Agriculture, Zhengzhou, Henan 451450</wicri:regionArea><wicri:noRegion>Henan 451450</wicri:noRegion></affiliation></author><author><name sortKey="Jia, Zhongkui" sort="Jia, Zhongkui" uniqKey="Jia Z" first="Zhongkui" last="Jia">Zhongkui Jia</name><affiliation wicri:level="1"><nlm:affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j">The Science of the total environment</title><idno type="eISSN">1879-1026</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Air Pollutants (MeSH)</term><term>Beijing (MeSH)</term><term>Environmental Monitoring (MeSH)</term><term>Particle Size (MeSH)</term><term>Particulate Matter (MeSH)</term><term>Plant Leaves (physiology)</term><term>Trees (physiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Arbres (physiologie)</term><term>Feuilles de plante (physiologie)</term><term>Matière particulaire (MeSH)</term><term>Polluants atmosphériques (MeSH)</term><term>Pékin (MeSH)</term><term>Surveillance de l'environnement (MeSH)</term><term>Taille de particule (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>Air Pollutants</term><term>Particulate Matter</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Arbres</term><term>Feuilles de plante</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Plant Leaves</term><term>Trees</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Beijing</term><term>Environmental Monitoring</term><term>Particle Size</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Matière particulaire</term><term>Polluants atmosphériques</term><term>Pékin</term><term>Surveillance de l'environnement</term><term>Taille de particule</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Urban trees have the potential to reduce air pollution, but the retention capacity and efficiency of different tree species for atmospheric particulate matter (PM) accumulation and the underlying mechanism hasn't been well understood. To select tree species with high air purification abilities, the supplementing ultrasonic cleaning (UC) procedure was first introduced into the conventional leaf cleaning methods [single water cleaning (WC) or plus brush cleaning (BC)] for eluting the leaf-retained PM. Further updates to the methodology were applied to investigate the retention capacity, efficiency, and mechanism for PM of five typical greening tree species in Beijing, China. Meanwhile, the particle size distribution of PM on the leaves, the PM retention efficiencies of easily removable (ERP), difficult-to-remove (DRP) and totally removable (TRP) particles on the leaf (AE<sub>leaf</sub>), and the individual tree scales were estimated. The experimental leaf samples were collected from trees with similar sizes 4 (SDR) and 14days (LDR) after rainfall. When the leaves were cleaned by WC+BC, there was, on average, 29%-46% of the PM remaining on the leaves of different species, which could be removed almost completely if UC was supplemented. From SDR to LDR, the mass of the leaf-retained PM increased greatly, and the particle size distribution changed markedly for all species except for Sophorajaponica. Pinus tabuliformis retains particles with the largest average diameter (34.2μm), followed by Ginkgo biloba (20.5μm), Sabina chinensis (16.4μm), Salix babylonica (16.0μm), and S. japonica (13.1μm). S. japonica and S. chinensis had the highest AE<sub>leaf</sub> to retain the TRP and ERP of both PM<sub>1</sub> and PM<sub>1-2.5</sub>, respectively. Conversely, S. babylonica and P. tabuliformis could retain both TRP and ERP of PM<sub>2.5-5</sub> and PM<sub>5-10</sub>, and PM<sub>>10</sub> and TSP with the highest AE<sub>leaf</sub>, respectively. In conclusion, our results could be useful in selecting greening tree species with high air purification abilities.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">29127795</PMID><DateCompleted><Year>2018</Year><Month>05</Month><Day>15</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-1026</ISSN><JournalIssue CitedMedium="Internet"><Volume>616-617</Volume><PubDate><Year>2018</Year><Month>Mar</Month></PubDate></JournalIssue><Title>The Science of the total environment</Title><ISOAbbreviation>Sci Total Environ</ISOAbbreviation></Journal><ArticleTitle>An investigation of the leaf retention capacity, efficiency and mechanism for atmospheric particulate matter of five greening tree species in Beijing, China.</ArticleTitle><Pagination><MedlinePgn>417-426</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0048-9697(17)33032-2</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.scitotenv.2017.10.314</ELocationID><Abstract><AbstractText>Urban trees have the potential to reduce air pollution, but the retention capacity and efficiency of different tree species for atmospheric particulate matter (PM) accumulation and the underlying mechanism hasn't been well understood. To select tree species with high air purification abilities, the supplementing ultrasonic cleaning (UC) procedure was first introduced into the conventional leaf cleaning methods [single water cleaning (WC) or plus brush cleaning (BC)] for eluting the leaf-retained PM. Further updates to the methodology were applied to investigate the retention capacity, efficiency, and mechanism for PM of five typical greening tree species in Beijing, China. Meanwhile, the particle size distribution of PM on the leaves, the PM retention efficiencies of easily removable (ERP), difficult-to-remove (DRP) and totally removable (TRP) particles on the leaf (AE<sub>leaf</sub>), and the individual tree scales were estimated. The experimental leaf samples were collected from trees with similar sizes 4 (SDR) and 14days (LDR) after rainfall. When the leaves were cleaned by WC+BC, there was, on average, 29%-46% of the PM remaining on the leaves of different species, which could be removed almost completely if UC was supplemented. From SDR to LDR, the mass of the leaf-retained PM increased greatly, and the particle size distribution changed markedly for all species except for Sophorajaponica. Pinus tabuliformis retains particles with the largest average diameter (34.2μm), followed by Ginkgo biloba (20.5μm), Sabina chinensis (16.4μm), Salix babylonica (16.0μm), and S. japonica (13.1μm). S. japonica and S. chinensis had the highest AE<sub>leaf</sub> to retain the TRP and ERP of both PM<sub>1</sub> and PM<sub>1-2.5</sub>, respectively. Conversely, S. babylonica and P. tabuliformis could retain both TRP and ERP of PM<sub>2.5-5</sub> and PM<sub>5-10</sub>, and PM<sub>>10</sub> and TSP with the highest AE<sub>leaf</sub>, respectively. In conclusion, our results could be useful in selecting greening tree species with high air purification abilities.</AbstractText><CopyrightInformation>Copyright © 2017 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Jinqiang</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cao</LastName><ForeName>Zhiguo</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zou</LastName><ForeName>Songyan</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Huanhuan</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hai</LastName><ForeName>Xiao</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Shihua</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Duan</LastName><ForeName>Jie</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>National Energy R&D Center for Non-food Biomass, Beijing 100083, China. Electronic address: duanjiebfu@vip.qq.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Xi</LastName><ForeName>Benye</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China. Electronic address: benyexi@bjfu.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yan</LastName><ForeName>Guangxuan</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>School of Environment, Henan Normal University, Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, Xinxiang, Henan 453007, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Shaowei</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Henan Vocational College of Agriculture, Zhengzhou, Henan 451450, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jia</LastName><ForeName>Zhongkui</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University, Beijing 100083, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>11</Month><Day>08</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Sci Total Environ</MedlineTA><NlmUniqueID>0330500</NlmUniqueID><ISSNLinking>0048-9697</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D000393">Air Pollutants</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D052638">Particulate Matter</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000393" MajorTopicYN="Y">Air Pollutants</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000068476" MajorTopicYN="N">Beijing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004784" MajorTopicYN="N">Environmental Monitoring</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010316" MajorTopicYN="N">Particle Size</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D052638" MajorTopicYN="Y">Particulate Matter</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014197" MajorTopicYN="N">Trees</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Particle diameter distribution</Keyword><Keyword MajorTopicYN="N">Particulate matter</Keyword><Keyword MajorTopicYN="N">Retention efficiency</Keyword><Keyword MajorTopicYN="N">Ultrasonic cleaning</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>08</Month><Day>04</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2017</Year><Month>10</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>10</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>11</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>5</Month><Day>16</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>11</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">29127795</ArticleId><ArticleId IdType="pii">S0048-9697(17)33032-2</ArticleId><ArticleId IdType="doi">10.1016/j.scitotenv.2017.10.314</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Liu, Jinqiang" sort="Liu, Jinqiang" uniqKey="Liu J" first="Jinqiang" last="Liu">Jinqiang Liu</name></noRegion><name sortKey="Cao, Zhiguo" sort="Cao, Zhiguo" uniqKey="Cao Z" first="Zhiguo" last="Cao">Zhiguo Cao</name><name sortKey="Duan, Jie" sort="Duan, Jie" uniqKey="Duan J" first="Jie" last="Duan">Jie Duan</name><name sortKey="Hai, Xiao" sort="Hai, Xiao" uniqKey="Hai X" first="Xiao" last="Hai">Xiao Hai</name><name sortKey="Jia, Zhongkui" sort="Jia, Zhongkui" uniqKey="Jia Z" first="Zhongkui" last="Jia">Zhongkui Jia</name><name sortKey="Liu, Huanhuan" sort="Liu, Huanhuan" uniqKey="Liu H" first="Huanhuan" last="Liu">Huanhuan Liu</name><name sortKey="Wang, Shihua" sort="Wang, Shihua" uniqKey="Wang S" first="Shihua" last="Wang">Shihua Wang</name><name sortKey="Xi, Benye" sort="Xi, Benye" uniqKey="Xi B" first="Benye" last="Xi">Benye Xi</name><name sortKey="Yan, Guangxuan" sort="Yan, Guangxuan" uniqKey="Yan G" first="Guangxuan" last="Yan">Guangxuan Yan</name><name sortKey="Zhang, Shaowei" sort="Zhang, Shaowei" uniqKey="Zhang S" first="Shaowei" last="Zhang">Shaowei Zhang</name><name sortKey="Zou, Songyan" sort="Zou, Songyan" uniqKey="Zou S" first="Songyan" last="Zou">Songyan Zou</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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