Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Research Article
  • Published:

Comparison of spatial interpolation methods for the estimation of air quality data

Journal of Exposure Science & Environmental Epidemiology volume 14, pages 404–415 (2004)Cite this article

Abstract

We recognized that many health outcomes are associated with air pollution, but in this project launched by the US EPA, the intent was to assess the role of exposure to ambient air pollutants as risk factors only for respiratory effects in children. The NHANES-III database is a valuable resource for assessing children's respiratory health and certain risk factors, but lacks monitoring data to estimate subjects’ exposures to ambient air pollutants. Since the 1970s, EPA has regularly monitored levels of several ambient air pollutants across the country and these data may be used to estimate NHANES subject's exposure to ambient air pollutants. The first stage of the project eventually evolved into assessing different estimation methods before adopting the estimates to evaluate respiratory health. Specifically, this paper describes an effort using EPA's AIRS monitoring data to estimate ozone and PM10 levels at census block groups. We limited those block groups to counties visited by NHANES-III to make the project more manageable and apply four different interpolation methods to the monitoring data to derive air concentration levels. Then we examine method-specific differences in concentration levels and determine conditions under which different methods produce significantly different concentration values. We find that different interpolation methods do not produce dramatically different estimations in most parts of the US where monitor density was relatively low. However, in areas where monitor density was relatively high (i.e., California), we find substantial differences in exposure estimates across the interpolation methods. Our results offer some insights into terms of using the EPA monitoring data for the chosen spatial interpolation methods.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Similar content being viewed by others

Abbreviations

AIRS:

Aerometric Information Retrieval System

BG:

block group

CO:

carbon monoxide

EPA:

Environmental Protection Agency

FIPS:

Federal Information Processing System

IDW:

inversed distance weighting

NAAQS:

National Ambient Air Quality Standards

NAMS:

National Air Monitoring Stations

NCHS:

National Center for Health Statistics

NHANES:

National Health and Nutrition Examination Survey

NO2:

nitrogen dioxide

O3:

ozone

OAQPS:

Office of Air Quality Planning and Standards

PM10:

particulate matter below 10ìm mean diameter

SLAMS:

State and Local Air Monitoring Stations

SO2:

sulfur dioxide

TSP:

total suspended particulates

References

  • Abbey D., Mills P., Petersen F., and Beeson W.I. Long-term ambient concentrations of total suspended particulates and oxidants as related to incidence of chronic disease in California seventh-day adventists. Env Health Perspect 1991: 94: 43–50.

    CAS  Google Scholar 

  • Bailey T.C., and Gatrell A.C. Interactive Spatial Data Analysis. Longman: London, 1995.

    Google Scholar 

  • Brown P.J., Le N.D., and Zidek J.V. Multivariate spatial interoplation and exposure to air pollutants. Can J Stat 1994: 22: 489–509.

    Article  Google Scholar 

  • Brunekreef B., Dockery D., and Krzyzanowski M. Epidemiologic studies on short-term effects of low levels of major ambient air pollution components. Env Health Perspect 1995: 103 (Suppl. 2): 3–13.

    CAS  Google Scholar 

  • Burrough P.A., and McDonnell R.A. Principles of Geographical Information Systems. Oxford University Press, Oxford, 1998.

    Google Scholar 

  • Casado L.S., Rouhani S., Cardelino C.A., and Ferrier A.J. Geostatistical analysis and visualization of hourly ozone data. Atmos Environ 1994: 28: 2105–2118.

    Article  CAS  Google Scholar 

  • Chestnut L., Schwartz J., Savitz D., and Burchfiel C. Pulmonary function and ambient particulate matter: epidemiological evidence from NHANES-I. Arch Environ Health 1991: 46 (3): 135–144.

    Article  CAS  Google Scholar 

  • Detels R., Tashkin D., Sayre J., Rokaw S., Coulson A., Massey F., and Wegman D. The UCLA population studies of chronic obstructive respiratory disease, 9: lung function changes associated with chronic exposure to photochemical oxidants, a cohort study among never-smokers. CHEST 1987: 92 (4): 594–603.

    Article  CAS  Google Scholar 

  • Duddek C., Le N.D., Zidek J.V., and Burnett R.T. Multivariate imputation in cross-sectional analysis of health effects associated with air pollution. J Environ Ecol Stat 1995: 2: 191–212.

    Article  Google Scholar 

  • Griffith D.A. Advanced Spatial Statistics. Kluwer Academic Publishers: Dordrecht, 1988.

    Book  Google Scholar 

  • Gunnink J.L., and Burrough P.A. Interactive spatial analysis of soil attribute patterns using exploratory data analysis (EDA) and GIS. In: Masser I., Salge F. (Eds). Spatial Analytical Perspectives on GIS. Taylor & Francis, New York, 1996, pp. 87–99.

    Google Scholar 

  • Isaaks E.H., and Srinivasta R.M. Applied Geostatistics. Oxford University Press: Oxford, 1989.

    Google Scholar 

  • Kinney P.L., Aggarwal M., Nikiforov S.V., and Nadas A. Methods development for epidemiologic investigations of the health effects of prolonged ozone exposure. Part III: an approach to retrospective estimation of lifetime ozone exposure using a questionnaire and ambient monitoring data (U.S. sites). Health Effects Inst Res Rep 1998: 81: 79–107.

    CAS  Google Scholar 

  • Kunzli N., Lurman F., Segal M., Ngo L., Balmes J., and Tager I. Association between lifetime ambient ozone exposure and pulmonary function in college freshman—results of a pilot study. Environ Res 1997: 72: 8–23.

    Article  CAS  Google Scholar 

  • Lefohn A.S., Knudsen H.P., Logan J.A., Simpson J., and Bhumralkar C. An evaluation of the kriging method to predict 7-h seasonal mean ozone concentrations for estimating crop losses. JAPCA 1987: 37: 595–602.

    Article  CAS  Google Scholar 

  • Lefohn A.S., Knudsen H.P., and McEvoy L.R. The use of kriging to estimate monthly ozone exposure parameters for the Southeastern United States. Environ Pollut 1988: 53: 27–42.

    Article  CAS  Google Scholar 

  • Linn W., Shamoo D., Anderson K., Peng R., Avol E., Hackney J., and Gong H. Short-term air pollution exposures and responses in los angeles area school children. J Exp Anal Environ Epi 1996: 6 (4): 449–472.

    CAS  Google Scholar 

  • Liu L.-J.S., and Rossini A.J. Use of kriging models to predict 12-hour mean ozone concentrations in metropolitan Toronto — a pilot study. Environ Int 1996: 22: 677–692.

    Article  CAS  Google Scholar 

  • McConnell R., Berhane K., Gilliland F., London S., Vora H., Avol E., Gauderman J., Margolis H., Lurmann F., Thomas D., and Peters J. Air Pollution and Bronchitis Symptoms in Southern California Children with Asthma. Environ Health Perspect 1999: 107 (9): 757–760.

    Article  CAS  Google Scholar 

  • Mulholland J.A., Butler A.J., Wilkinson J.G., Russell A.G., and Tolbert P.E. Temporal and spatial distributions of ozone in Atlanta: regulatory and epidemiologic implications. J Air Waste Mngt Assoc 1998: 48: 418–426.

    Article  CAS  Google Scholar 

  • Nikiforov S.V., Aggarwal M., Nadas A., and Kinney P.L. Methods for spatial interpolation of long-term ozone concentrations. J Exposure Anal Environ Epidemiol 1998: 8: 465–481.

    CAS  Google Scholar 

  • Norris G., Youngpong S., Koenig J., Larson T., Sheppard L., and Stout J. An association between fine particles and asthma emergency department visits for children in Seattle. Environ Health Perspect 1999: 107 (6): 489–493.

    Article  CAS  Google Scholar 

  • Oliver M.A. Geostatistics, rare disease and the environment. In: Masser I., Salge F. (Eds). Spatial Analytical Perspectives on GIS. Taylor & Francis, New York, 1996, pp. 67–85.

    Google Scholar 

  • Peters J., Avol E., Navidi W., London S., Gauderman W., Lurmann F., Linn W., Margolis H., Rappaport E., Gong H., and Thomas D. A study of twelve southern california communities with differing levels and types of air pollution. Am J Respir Crit Care Med 1999: 159: 760–767.

    Article  CAS  Google Scholar 

  • Pope C.A., Bates D., and Raizenne M. Health effects of particulate air pollution: time for reassessment? Environ Health Perspect 1995a: 103 (5): 472–480.

    Article  Google Scholar 

  • Pope C.A., Dockery D., and Schwartz J. Review of epidemiological evidence of health effects of particulate air pollution. Inhal Toxicol 1995b: 7: 1–18.

    Article  CAS  Google Scholar 

  • Schwartz J. Lung function and chronic exposure to air pollution: a cross-sectional analysis of NHANES II. Environ Res 1989: 50: 309–321.

    Article  CAS  Google Scholar 

  • Schwartz J. Air pollution and blood markers of cardiovascular risk. Environ Health Perspect 2001: 109 (Suppl. 3): 405–409.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Schwartz J., Dockery D., Neas L., Wypij D., Ware J., Spengler J., Koutrakis P., Speizer F., and Ferris B. Acute effects of summer air pollution on respiratory symptom reporting in children. Am J Respir Crit Care Med 1994: 150: 1234–1242.

    Article  CAS  Google Scholar 

  • Schwartz J., and Zeger S. Passive smoking, air pollution, and acute respiratory symptoms in a diary study of student nurses. Am Rev Respir Dis 1990: 141: 62–67.

    Article  CAS  Google Scholar 

  • Stern B., Jones L., Raizenne M., Burnett R., Meager J.C., and Franklin C.A. Respiratory health effects associated with ambient sulfates and ozone in two rural canadian communities. Environ Res 1989: 49: 20–39.

    Article  CAS  Google Scholar 

  • Stern B., Raizenne M., Burnett R., Jones L., Kearney J., and Franklin C.A. Air pollution and childhood respiratory health: exposure to sulfate and ozone in 10 Canadian rural communities. Environ Res 1994: 66: 125–142.

    Article  CAS  Google Scholar 

  • Thurston G., Ito K., Kinney P., and Lippmann M. A multi-year study of air pollution and respiratory hospital admissions in three new state metropolitan areas: results for 1988 and 1989 summers. J Exp Anal Environ Epi 1992: 2 (4): 429–450.

    CAS  Google Scholar 

  • US Environmental Protection Agency. Air Quality Criteria for Ozone and Related Photochemical Oxidants. Vol. I of III Office of Research and Development, Washington, DC, July, 1996a, EPA/600/P-93/004aF.

  • US Environmental Protection Agency. Air Quality Criteria for Particulate Matter. Vol. I of III Office of Research and Development, Washington, DC, April, 1996b, EPA/600/P-95/001aF.

  • Vedal S., Petkau J., White R., and Blair J. Acute effects of ambient inhalable particles in asthmatic and nonasthmatic children. Am J Respir Crit Care Med 1998: 157: 1034–1043.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge the assistance of Milton Siegel of U.S. EPA National Center for Environmental Assessment — Washington Division, in analyzing the data, and Stephen Andrews of Indus Corporation in retrieving the AIRS data.

Author information

Authors and Affiliations

  1. School of Computational Sciences, George Mason University, Fairfax, VA, USA

    David W Wong

  2. National Center for Environmental Assessment, US Environmental Protection Agency, Washington, USA

    Lester Yuan & Susan A Perlin

Authors
  1. David W Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lester Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Susan A Perlin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David W Wong.

Additional information

The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wong, D., Yuan, L. & Perlin, S. Comparison of spatial interpolation methods for the estimation of air quality data. J Expo Sci Environ Epidemiol 14, 404–415 (2004). https://doi.org/10.1038/sj.jea.7500338

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.jea.7500338

Keywords

This article is cited by

Search

Advanced search

Quick links