Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

被引：153

作者：

de Hoogh, Kees ^{[1
,2
]}

Gulliver, John ^{[3
]}

van Donkelaar, Aaron ^{[4
]}

Martin, Randall V. ^{[4
,5
]}

Marshall, Julian D. ^{[6
]}

Bechle, Matthew J. ^{[6
]}

Cesaroni, Giulia ^{[7
]}

Cirach Pradas, Marta ^{[8
,9
]}

Dedele, Audrius ^{[10
]}

Eeftens, Marloes ^{[1
,2
]}

Forsberg, Bertil ^{[11
]}

Galassi, Claudia ^{[12
,13
]}

Heinrich, Joachim ^{[14
,15
,16
]}

Hoffmann, Barbara ^{[17
,18
]}

Jacquemin, Benedicte ^{[19
,20
,21
]}

Katsouyanni, Klea ^{[22
,23
,24
]}

Korek, Michal ^{[25
]}

Kunzli, Nino ^{[1
,2
]}

Lindley, Sarah J. ^{[26
]}

Lepeule, Johanna ^{[27
,28
]}

Meleux, Frederik ^{[29
]}

de Nazelle, Audrey ^{[30
]}

Nieuwenhuijsen, Mark ^{[8
,9
,31
]}

Nystad, Wenche ^{[32
]}

Raaschou-Nielsen, Ole ^{[33
,34
]}

Peters, Annette ^{[35
]}

Peuch, Vincent-Henri ^{[36
]}

Rouil, Laurence

Udvardy, Orsolya ^{[37
]}

Slama, Remy

Stempfelet, Morgane ^{[38
]}

Stephanou, Euripides G. ^{[39
]}

Tsai, Ming Y. ^{[1
,2
,40
]}

Yli-Tuomi, Tarja ^{[41
]}

Weinmayr, Gudrun ^{[42
]}

Brunekreef, Bert ^{[43
,44
]}

Vienneau, Danielle ^{[1
,2
]}

Hoek, Gerard ^{[43
]}

机构：

[1] Swiss Trop & Publ Hlth Inst, Socinstr 57, CH-4051 Basel, Switzerland

[2] Univ Basel, Peterspl 1, CH-4001 Basel, Switzerland

[3] Imperial Coll London, Dept Epidemiol & Biostat, MRC PHE Ctr Environm & Hlth, St Marys Campus,Norfolk Pl, London W2 1PG, England

[4] Dalhousie Univ, Dept Phys & Atmospher Sci, 6310 Coburg Rd, Halifax, NS B3H 4R2, Canada

[5] Harvard Smithsonian Ctr Astrophys, 60 Garden St, Cambridge, MA 02138 USA

[6] Univ Washington, John R Kiely Prof Civil & Environm Engn, Wilcox 268, Seattle, WA 98195 USA

[7] Lazio Reg Hlth Serv, Dept Epidemiol, Via Cristoforo Colombo 112, I-00147 Rome, Italy

[8] Ctr Res Environm Epidemiol CREAL, Doctor Aiguader 88, E-08003 Barcelona, Spain

[9] CIBERESP, Ave Monforte Lemos,3-5 Pabellon 11 Planta 0, Madrid 28029, Spain

[10] Vytauto Didziojo Univ, Dept Environm Sci, K Donelaicio 58, LT-44248 Kaunas, Lithuania

[11] Umea Univ, Dept Publ Hlth & Clin Med Occupat & Environm Med, SE-90187 Umea, Sweden

[12] Citta Salute & Sci Univ Hosp, Canc Epidemiol Unit, Corso Bramante 88, I-10126 Turin, Italy

[13] Ctr Canc Prevent, Corso Bramante 88, I-10126 Turin, Italy

[14] Univ Munich, Univ Hosp, Munich Inst, Ziemssenstr 1, D-80336 Munich, Germany

[15] Outpatient Clin Occupat Social & Environm Med, Ziemssenstr 1, D-80336 Munich, Germany

[16] Helmholtz Zentrum Munchen, German Res Ctr Environm Hlth, Inst Epidemiol 1, Ingolstadter Landstr 1, D-85764 Neuherberg, Germany

[17] Univ Dusseldorf, IUF Leibniz Res Inst Environm Med, Aufm Hennekamp 50, D-40225 Dusseldorf, Germany

[18] Univ Dusseldorf, Fac Med, Univ Str 1, D-40225 Dusseldorf, Germany

[19] INSERM, U1168, VIMA Aging & Chron Dis Epidemiol & Publ Hlth Appr, 16 Ave Paul Vaillant Couturier, F-94807 Villejuif, France

[20] Univ Versailles St Quentin En Yvelines, UMR S 1168, 2 Ave Source Bievre, F-78180 Montigny Le Bretonneux, France

[21] Univ Pompeu Fabra, Placa Merce 10-12, Barcelona 08002, Spain

[22] Univ Athens, Sch Med, Dept Hyg Epidemiol & Med Stat, 75 Mikras Asias St, GR-11527 Athens, Greece

[23] Kings Coll London, Dept Primary Care & Publ Hlth Sci, Franklin Wilkins Bldg,150 Stamford St, London SE1 9NH, England

[24] Kings Coll London, Environm Res Grp, Franklin Wilkins Bldg,150 Stamford St, London SE1 9NH, England

[25] Karolinska Inst, Inst Environm Med, Nobels Vag 13, S-17165 Stockholm, Sweden

[26] Univ Manchester, Sch Environm Educ & Dev, Geog, Manchester M13 3PL, Lancs, England

[27] INSERM, F-38000 Grenoble, France

[28] Univ Grenoble Alpes, IAB, U1209, Team Environm Epidemiol, F-38000 Grenoble, France

[29] Natl Inst Ind Environm & Risks INERIS, Parc Technol ALATA, F-60550 Verneuil En Halatte, France

[30] Imperial Coll London, Ctr Environm Policy, South Kensington Campus, London SW7 2AZ, England

[31] Hosp del Mar, Res Inst, IMIM, Dr Aiguader 88, Barcelona 08003, Spain

[32] Norwegian Inst Publ Hlth, Div Environm Med, POB 4404, N-0403 Oslo, Norway

[33] Danish Canc Soc Res Ctr, Strandboulevarden 49, DK-2100 Copenhagen, Denmark

[34] Aarhus Univ, Dept Environm Sci, Frederiksborgvej 399,POB 358, DK-4000 Roskilde, Denmark

[35] German Res Ctr Environm Hlth, Helmholtz Zentrum Munchen, Inst Epidemiol 2, Ingolstadter Landstr 1, D-85764 Neuherberg, Germany

[36] ECMWF, Shinfield Pk, Reading RG2 9AX, Berks, England

[37] Natl Publ Hlth Ctr, Albert Florian Ut 2-6, H-1097 Budapest, Hungary

[38] French Inst Publ Hlth, 12 Rue Val dOsne, F-94415 St Maurice, France

[39] Univ Crete, Dept Chem, ECPL, Iraklion 71003, Greece

[40] Univ Washington, Dept Environm & Occupat Hlth Sci, Box 357234, Seattle, WA 98195 USA

[41] Natl Inst Hlth & Welf THL, Dept Hlth Protect, Living Environm & Hlth Unit, POB 95, FI-70701 Kuopio, Finland

[42] Univ Ulm, Inst Epidemiol & Med Biometry, Helmholtzstr 22, D-89081 Ulm, Germany

[43] Univ Utrecht, Inst Risk Assessment Sci, Yalelaan 2, NL-3584 CM Utrecht, Netherlands

[44] Univ Med Ctr Utrecht, Julius Ctr Hlth Sci & Primary Care, Uni Weg 100, NL-3584 CM Utrecht, Netherlands

来源：

ENVIRONMENTAL RESEARCH | 2016年 / 151卷

基金：

美国国家科学基金会;

关键词：

Air pollution; Exposure; Spatial modelling; Fine particulate matter; Nitrogen dioxide; FINE PARTICULATE MATTER; AEROSOL OPTICAL DEPTH; AIR-POLLUTION; EXPOSURE ASSESSMENT; MACC REANALYSIS; ESCAPE PROJECT; AREAS; PM10; ABSORBENCY; PMCOARSE;

D O I：

10.1016/j.envres.2016.07.005

中图分类号：

X [环境科学、安全科学];

学科分类号：

083001 [环境科学];

摘要：

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained similar to 60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR(2): 0.33-0.38). For NO2 CTM improved prediction modestly (adjR2: 0.58) compared to models without SAT and CTM (adjR2: 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：1 / 10

页数：10

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