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| 1 | Could wastewater analysis be a useful tool for China?——A review显示文摘Analysing wastewater samples is an innovative approach that overcomes many limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis(WWA) a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by law enforcement agencies as a device to monitor the temporal and geographical patterns of drug consumption. In the future, the methodology can be extended to other chemicals including biomarkers of population health(e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups) and pollutants that people are exposed to(e.g. polycyclic aromatic hydrocarbons,perfluorinated chemicals, and toxic pesticides). The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining(SCIM) with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China. | Jianfa Gao Jake O'Brien Foon Yin Lai Alexander L.N.van Nuijs Jun He Jochen F.Mueller Jingsha Xu Phong K.Thai | 2015 | Journal of Environmental Sciences2015，27，1： | 4 |
| 2 | Concentrations of organophosphate flame retardants in dust from cars, homes, and offices: An international comparison显示文摘Concentrations of a number of organophosphate flame retardants(PFRs)were measured in floor dust collected from living rooms in Australia(n=42),Canada(n=14),Germany(n=22),and Kazakhstan(n=9);cars from Australia(n=39)and Germany(n=19);and offices from Germany(n=25)and Kazahkstan(n=8).PFR concentrations in these samples were compared with each other and with previously reported data for PFRs in dust from similar microenvironments in the UK.Our data reveal significant between-country differences in both absolute concentrations and the relative abundance of specific PFRs in each of the microenvironments studied.Most notably,concentrations of TCIPP in UK living room dust(median=21 μg g^-1)exceeded significantly(p<0.05)those in all other countries studied here;a substantial number of car dust samples contained elevated concentrations of TDCIPP,and German samples generally contained lower levels of PFRs in all microenvironments studied.In addition,PFRs were determined in dust samples collected from living room couches in both Australia(n=41)and the UK(n=10).The elevated concentrations of TCIPP in UK living room dust are likely attributable to the favoured use of this PFR in UK couch foam.This is indicated by concentrations of TCIPP in UK couch dust(median=610 μg g^-1)exceeding significantly those in Australian couch dust(median=2.9 μg g^-1).Moreover,concentrations of TCIPP in UK couch dust originating from couches 15 years old or less,display a marked relationship with the age of the couch,with concentrations in such samples increasing significantly(p<0.01)with couch age. | Stuart Harrad Sandra Brommer Jochen F.Mueller | 2016 | Emerging Contaminants2016，2，2： | 3 |
| 3 | Measurement of the integrated luminosity of the Phase 2 data of the Belle Ⅱ experiment显示文摘From April to July 2018,a data sample at the peak energy of the T(4 S) resonance was collected with the Belle Ⅱ detector at the SuperKEKB electron-positron collider.This is the first data sample of the Belle Ⅱ experiment.Using Bhabha and digamma events,we measure the integrated luminosity of the data sample to be(496.3±0.3±3.0) pb-1,where the first uncertainty is statistical and the second is systematic.This work provides a basis for future luminosity measurements at Belle Ⅱ. | F.Abudinén I.Adachi P.Ahlburg H.Aihara N.Akopov A.Aloisio F.Ameli L.Andricek N.Anh Ky D.M.Asner H.Atmacan T.Aushev V.Aushev T.Aziz K.Azmi V.Babu S.Baehr S.Bahinipati A.M.Bakich P.Bambade Sw.Banerjee S.Bansal V.Bansal M.Barrett J.Baudot A.Beaulieu J.Becker P.K.Behera J.V.Bennett E.Bernieri F.U.Bernlochner M.Bertemes M.Bessner S.Bettarini V.Bhardwaj F.Bianchi T.Bilka S.Bilokin D.Biswas G.Bonvicini A.Bozek M.Bračko P.Branchini N.Braun T.E.Browder A.Budano S.Bussino M.Campajola L.Cao G.Casarosa C.Cecchi D.Červenkov M.-C.Chang P.Chang R.Cheaib V.Chekelian Y.Q.Chen Y.-T.Chen B.G.Cheon K.Chilikin H.-E.Cho K.Cho S.Cho S.-K.Choi S.Choudhury D.Cinabro L.Corona L.M.Cremaldi S.Cunliffe T.Czank F.Dattola E.De La Cruz-Burelo G.De Nardo M.De Nuccio G.De Pietro R.de Sangro M.Destefanis S.Dey A.De Yta-Hernandez F.Di Capua S.Di Carlo J.Dingfelder Z.Doležal I.Domínguez Jiménez T.V.Dong K.Dort S.Dubey S.Duell S.Eidelman M.Eliachevitch T.Ferber D.Ferlewicz G.Finocchiaro S.Fiore A.Fodor F.Forti A.Frey B.G.Fulsom M.Gabriel E.Ganiev M.Garcia-Hernandez R.Garg A.Garmash V.Gaur A.Gaz U.Gebauer A.Gellrich J.Gemmler T.Geßler R.Giordano A.Giri B.Gobbo R.Godang P.Goldenzweig B.Golob P.Gomis P.Grace W.Gradl E.Graziani D.Greenwald C.Hadjivasiliou S.Halder K.Hara T.Hara O.Hartbrich K.Hayasaka H.Hayashii C.Hearty M.T.Hedges I.Heredia de la Cruz M.Hernández Villanueva A.Hershenhorn T.Higuchi E.C.Hill H.Hirata M.Hoek S.Hollitt T.Hotta C.-L.Hsu Y.Hu K.Huang T.Iijima K.Inami G.Inguglia J.Irakkathil Jabbar A.Ishikawa R.Itoh M.Iwasaki Y.Iwasaki S.Iwata P.Jackson W.W.Jacobs D.E.Jaffe E.-J.Jang H.B.Jeon S.Jia Y.Jin C.Joo J.Kahn H.Kakuno A.B.Kaliyar G.Karyan Y.Kato T.Kawasaki H.Kichimi C.Kiesling B.H.Kim C.-H.Kim D.Y.Kim S.-H.Kim Y.K.Kim Y.Kim T.D.Kimmel K.Kinoshita C.Kleinwort B.Knysh P.Kodyš T.Koga I.Komarov T.Konno S.Korpar D.Kotchetkov N.Kovalchuk T.M.G.Kraetzschmar P.Križan R.Kroeger J.F.Krohn P.Krokovny W.Kuehn T.Kuhr M.Kumar R.Kumar K.Kumara S.Kurz A.Kuzmin Y.-J.Kwon S.Lacaprara Y.-T.Lai C.La Licata K.Lalwani L.Lanceri J.S.Lange K.Lautenbach I.-S.Lee S.C.Lee P.Leitl D.Levit P.M.Lewis C.Li L.K.Li S.X.Li Y.M.Li Y.B.Li J.Libby K.Lieret L.Li Gioi J.Lin Z.Liptak Q.Y.Liu D.Liventsev S.Longo A.Loos F.Luetticke T.Luo C.MacQueen Y.Maeda M.Maggiora S.Maity E.Manoni S.Marcello C.Marinas A.Martini M.Masuda K.Matsuoka D.Matvienko J.McNeil J.C.Mei F.Meier M.Merola F.Metzner M.Milesi C.Miller K.Miyabayashi H.Miyata R.Mizuk G.B.Mohanty H.Moon T.Morii H.-G.Moser F.Mueller F.J.Müller Th.Muller R.Mussa K.R.Nakamura E.Nakano M.Nakao H.Nakayama H.Nakazawa M.Nayak G.Nazaryan D.Neverov M.Niiyama N.K.Nisar S.Nishida K.Nishimura M.Nishimura M.H.A.Nouxman B.Oberhof S.Ogawa Y.Onishchuk H.Ono Y.Onuki P.Oskin H.Ozaki P.Pakhlov G.Pakhlova A.Paladino T.Pang E.Paoloni H.Park S.-H.Park B.Paschen A.Passeri S.Patra S.Paul T.K.Pedlar I.Peruzzi R.Peschke R.Pestotnik M.Piccolo L.E.Piilonen P.L.M.Podesta-Lerma V.Popov C.Praz E.Prencipe M.T.Prim M.V.Purohit P.Rados M.Remnev P.K.Resmi I.Ripp-Baudot M.Ritter M.Ritzert G.Rizzo L.B.Rizzuto S.H.Robertson D.Rodríguez Pérez J.M.Roney C.Rosenfeld A.Rostomyan N.Rout G.Russo D.Sahoo Y.Sakai D.A.Sanders S.Sandilya A.Sangal L.Santelj P.Sartori Y.Sato V.Savinov B.Scavino M.Schram H.Schreeck J.Schueler C.Schwanda A.J.Schwartz B.Schwenker R.M.Seddon Y.Seino A.Selce K.Senyo M.E.Sevior C.Sfienti C.P.Shen H.Shibuya J.-G.Shiu A.Sibidanov F.Simon S.Skambraks R.J.Sobie A.Soffer A.Sokolov E.Solovieva S.Spataro B.Spruck M.Starič S.Stefkova Z.S.Stottler R.Stroili J.Strube M.Sumihama T.Sumiyoshi D.J.Summers W.Sutcliffe M.Tabata M.Takizawa U.Tamponi S.Tanaka K.Tanida H.Tanigawa N.Taniguchi Y.Tao P.Taras F.Tenchini E.Torassa K.Trabelsi T.Tsuboyama N.Tsuzuki M.Uchida I.Ueda S.Uehara T.Uglov K.Unger Y.Unno S.Uno P.Urquijo Y.Ushiroda S.E.Vahsen R.van Tonder G.S.Varner K.E.Varvell A.Vinokurova L.Vitale A.Vossen E.Waheed H.M.Wakeling K.Wan W.Wan Abdullah B.Wang M.-Z.Wang X.L.Wang A.Warburton M.Watanabe S.Watanuki J.Webb S.Wehle N.Wermes C.Wessel J.Wiechczynski P.Wieduwilt H.Windel E.Won S.Yamada W.Yan S.B.Yang H.Ye J.Yelton J.H.Yin M.Yonenaga Y.M.Yook C.Z.Yuan Y.Yusa L.Zani J.Z.Zhang Z.Zhang V.Zhilich Q.D.Zhou X.Y.Zhou V.I.Zhukova V.Zhulanov A.Zupanc | 2020 | Chinese Physics C2020，44，2： | 2 |
| 4 | Efficient photocatalytic destruction of recalcitrant micropollutants using graphitic carbon nitride under simulated sunlight irradiation显示文摘The ubiquity of micropollutants(MPs)in aquatic environments has attracted increasing concern for public health and ecological security.Compared to conventional biological treatment,photocatalytic processes show more efficiency in degrading MPs,but they require expensive materials and complicated synthesis processes.This study developed an economic photocatalytic process to degrade micropollutants.We synthesized urea-based graphitic carbon nitride(g-C_(3)N_(4))by a facile one-step pyrolysis method and evaluated the photocatalytic efficiency of carbamazepine(CBZ).Under simulated solar irradiation,g-C_(3)N_(4) could achieve 100% removal efficiency of 0.1 mg/L CBZ in spiked wastewater effluent within 15 min,and 86.5% removal efficiency in wastewater influent after 20 min of irradiation.The porous structure of g-C_(3)N_(4) promoted effective charge separation and mass transport of CBZ near the catalyst surface,enabling a high kinetic rate(0.3662 min^(-1)).Reactive oxygen species trapping experiments revealed that superoxide radicals(O_(2)^(·-))and holes(h^(+))were the major active radicals.Electron paramagnetic resonance(EPR)further confirmed the presence of O_(2)^(·-),·OH,^(1)O_(2) and holes.The pH,light intensity and initial CBZ concentration were found to have significant impacts on the removal efficiency of CBZ.Possible reaction intermediates were identified and the degradation pathway was proposed.Multiple MPs were selected to further demonstrate photocatalytic efficiency of g-C_(3)N_(4).The facile synthesis,superior efficiency,and versatility of g-C_(3)N_(4) make it a promising catalyst for application in tertiary wastewater treatment processes. | Jiexi Zhong Hui Jiang Zhiliang Wang Zhigang Yu Lianzhou Wang Jochen F.Mueller Jianhua Guo | 2021 | Environmental Science and Ecotechnology2021，，1： | 2 |
| 5 | The Transcriptome of Human Cytotoxic T Cells: Measuring the Burden of CTL‐Associated Transcripts in Human Kidney Transplants显示文摘 | L. G.Hidalgo G.Einecke K.Allanach M.Mengel B.Sis T. F.Mueller P. F.Halloran | 2008 | American Journal of Transplantation2008，，3： | 1 |
| 6 | Temporal trends of per-and polyfluoroalkyl substances(PFAS)in the influent of two of the largest wastewater treatment plants in Australia显示文摘Per-and polyfluoroalkyl substances(PFAS)are found ubiquitously in wastewater treatment plants(WWTPs)due to their multiple sources in industry and consumer products.In Australia,limited spatial data are available on PFAS levels inWWTPs influent,while no temporal data have been reported.The aim of this study was to investigate the occurrence and temporal trend of PFAS in the influent of two large WWTPs in Australia(WWTP A and B)over a four-year period.Daily influent samples were collected over one week at different seasons from 2014 to 2017.Eleven perfluoroalkyl acids(PFAA)(i.e.seven perfluoroalkyl carboxylic acids(PFCAs)and four perfluoroalkyl sulfonic acids(PFSA))were detected with mean S11PFAA concentrations of 57±3.3e94±17 ng/L at WWTP A,and 31±6.1e142±73 ng/L at WWTP B.The highest mean concentrations were observed for perfluorohexanoate(PFHxA)(20±2 ng/L)in WWTP A,and perfluorooctane sulfonate(PFOS)(17±13 ng/L)in WWTP B.The precursor 6:2 fluorotelomer sulfonate was detected over five sampling periods from Aug 2016 to Oct 2017,with mean concentrations of 37±18e138±51 ng/L for WWTP A and 8.8±4.5e29±5.1 ng/L for WWTP B.Higher concentration of 6:2 FTS(1.8e11 folds)than those of PFOA and PFOS in WWTP A indicate a likely substitution of C8 PFAA by fluorotelomer-based PFAS in this catchment.Temporal trends(annual and seasonal)in per-capita mass load were observed for some PFAA,increasing for PFPeA,PFHxA,PFHpA,PFNA,and PFHxS,while decreasing for PFBS and PFOS in either WWTPs.Notably,elevated levels of PFOS in October 2017 were observed at both WWTPs with the highest per capita mass load of up to 67 mg/day/inhabitant.For some PFAS release trends,longer sampling periods would be required to achieve acceptable statistical power. | Hue T.Nguyen Sarit L.Kaserzon Phong K.Thai Soumini Vijayasarathy Jennifer Bräunig Nicholas D.Crosbie Anders Bignert Jochen F.Mueller | 2019 | Emerging Contaminants2019，5，1： | 0 |
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