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Accepted (AM)Open Access (License Unspecified), Open
Journal article
An assessment of air pollutant exposure methods in Mexico City, Mexico
Journal of the Air & Waste Management Association (1995), v 65(5), pp 581-591
04 May 2015
PMID: 25947316
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM
10
, PM
2.5
, O
3
, CO, NO
2
, and SO
2
and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r = 0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures.
Implications: Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.
Metrics
Details
- Title
- An assessment of air pollutant exposure methods in Mexico City, Mexico
- Creators
- Luis O. Rivera-González - University of MichiganZhenzhen Zhang - University of MichiganBrisa N. Sánchez - University of MichiganKai Zhang - The University of Texas Health Science Center at HoustonDaniel G. Brown - University of MichiganLeonora Rojas-Bracho - Oldham CouncilAlvaro Osornio-Vargas - University of AlbertaFelipe Vadillo-Ortega - Universidad Nacional Autónoma de MéxicoMarie S. O'Neill - Department of Epidemiology, of Michigan, School of Public Health
- Publication Details
- Journal of the Air & Waste Management Association (1995), v 65(5), pp 581-591
- Publisher
- Taylor & Francis
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000354047100009
- Scopus ID
- 2-s2.0-84942580933
- Other Identifier
- 991020100208804721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Environmental
- Environmental Sciences
- Meteorology & Atmospheric Sciences