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Int. J. Environ. Res. Public Health 2014, 11(1), 983-1000; doi:10.3390/ijerph110100983
Article

Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics

1
, 2,†,* , 3,†
, 1,†
 and 1,†
Received: 14 November 2013; in revised form: 17 December 2013 / Accepted: 19 December 2013 / Published: 10 January 2014
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Abstract: Tropospheric ozone (O3) pollution is a major problem worldwide, including in the United States of America (USA), particularly during the summer months. Ozone oxidative capacity and its impact on human health have attracted the attention of the scientific community. In the USA, sparse spatial observations for O3 may not provide a reliable source of data over a geo-environmental region. Geostatistical Analyst in ArcGIS has the capability to interpolate values in unmonitored geo-spaces of interest. In this study of eastern Texas O3 pollution, hourly episodes for spring and summer 2012 were selectively identified. To visualize the O3 distribution, geostatistical techniques were employed in ArcMap. Using ordinary Kriging, geostatistical layers of O3 for all the studied hours were predicted and mapped at a spatial resolution of 1 kilometer. A decent level of prediction accuracy was achieved and was confirmed from cross-validation results. The mean prediction error was close to 0, the root mean-standardized-prediction error was close to 1, and the root mean square and average standard errors were small. O3 pollution map data can be further used in analysis and modeling studies. Kriging results and O3 decadal trends indicate that the populace in Houston-Sugar Land-Baytown, Dallas-Fort Worth-Arlington, Beaumont-Port Arthur, San Antonio, and Longview are repeatedly exposed to high levels of O3-related pollution, and are prone to the corresponding respiratory and cardiovascular health effects. Optimization of the monitoring network proves to be an added advantage for the accurate prediction of exposure levels.
Keywords: tropospheric ozone (O3); geostatistical analysis; prediction; interpolation; spatial resolution; visualization; Geographical Information Systems (GIS) tropospheric ozone (O3); geostatistical analysis; prediction; interpolation; spatial resolution; visualization; Geographical Information Systems (GIS)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Kethireddy, S.R.; Tchounwou, P.B.; Ahmad, H.A.; Yerramilli, A.; Young, J.H. Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics. Int. J. Environ. Res. Public Health 2014, 11, 983-1000.

AMA Style

Kethireddy SR, Tchounwou PB, Ahmad HA, Yerramilli A, Young JH. Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics. International Journal of Environmental Research and Public Health. 2014; 11(1):983-1000.

Chicago/Turabian Style

Kethireddy, Swatantra R.; Tchounwou, Paul B.; Ahmad, Hafiz A.; Yerramilli, Anjaneyulu; Young, John H. 2014. "Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics." Int. J. Environ. Res. Public Health 11, no. 1: 983-1000.


Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert