title: Evaluation of observation-fused regional air quality model results for population air pollution exposure estimation.
abstract: In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRRs are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account for spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses.
authors.affiliation: Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, United States.
authors.forename: Gang
authors.initials: G
authors.lastname: Chen
authors.affiliation: Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, United States.
authors.forename: Jingyi
authors.initials: J
authors.lastname: Li
authors.affiliation: Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, United States. Electronic address: qying@civil.tamu.edu.
authors.forename: Qi
authors.initials: Q
authors.lastname: Ying
authors.affiliation: The EMMES Corporation, Rockville, MD 20850, United States.
authors.forename: Seth
authors.initials: S
authors.lastname: Sherman
authors.affiliation: Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, MD 20852, United States.
authors.forename: Neil
authors.initials: N
authors.lastname: Perkins
authors.affiliation: Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, MD 20852, United States.
authors.forename: Rajeshwari
authors.initials: R
authors.lastname: Sundaram
authors.affiliation: Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, MD 20852, United States.
authors.forename: Pauline
authors.initials: P
authors.lastname: Mendola
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution / Q000706:statistics & numerical data*; D004781:Environmental Exposure / Q000032:analysis / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000379:methods; D006801:Humans; D008956:Models, Chemical; D052638:Particulate Matter / Q000032:analysis; D012044:Regression Analysis; D013997:Time Factors
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Community Multiscale Air Quality (CMAQ) model; Data fusing; Exposure; Inverse distance weighting; Model performance; Population weighted average
references.citation: Sci Total Environ. 2014 Mar 1;473-474:275-85
references.pmid: 24374589
references.citation: Paediatr Perinat Epidemiol. 2011 Sep;25(5):413-24
references.pmid: 21819423
references.citation: Soc Sci Med. 1996 Mar;42(6):843-55
references.pmid: 8778997
references.citation: Biometrics. 2005 Mar;61(1):36-45
references.pmid: 15737076
references.citation: Environ Int. 2006 Jul;32(5):586-93
references.pmid: 16516968
references.citation: Environ Health Perspect. 2000 Oct;108(10):941-7
references.pmid: 11049813
references.citation: Am J Obstet Gynecol. 2010 Oct;203(4):326.e1-326.e10
references.pmid: 20708166
references.citation: Environ Health Perspect. 2012 Jan;120(1):68-76
references.pmid: 22049372
references.citation: Am J Epidemiol. 2012 Jan 15;175(2):91-8
references.pmid: 22167746
references.citation: Environ Res. 2012 Jul;116:1-10
references.pmid: 22579357
references.citation: Environ Health Perspect. 2007 Jul;115(7):989-95
references.pmid: 17637911
references.citation: JAMA. 2004 Nov 17;292(19):2372-8
references.pmid: 15547165