Journal of Korean Society for Atmospheric Environment (한국대기환경학회지)

Korean Society for Atmospheric Environment (한국대기환경학회)
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Exploration and Application of Regulatory PM10 Measurement Data for Developing Long-term Prediction Models in South Korea

PM10 장기노출 예측모형 개발을 위한 국가 대기오염측정자료의 탐색과 활용

  • Yi, Seon-Ju (Division of Public Health, Department of Public Health Science, Graduate School of Public Health, Seoul National University) ;
  • Kim, Ho (Division of Public Health, Department of Public Health Science, Graduate School of Public Health, Seoul National University) ;
  • Kim, Sun-Young (Institute of Health and Environment, Seoul National University)
  • 이선주 (서울대학교 보건대학원 보건학과 보건학 전공) ;
  • 김호 (서울대학교 보건대학원 보건학과 보건학 전공) ;
  • 김선영 (서울대학교 보건환경연구소)
  • Received : 2015.10.21
  • Accepted : 2016.02.01
  • Published : 2016.02.29
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Abstract

Many cohort studies have reported associations of individual-level long-term exposures to $PM_{10}$ and health outcomes. Individual exposures were often estimated by using exposure prediction models relying on $PM_{10}$ data measured at national regulatory monitoring sites. This study explored spatial and temporal characteristics of regulatory $PM_{10}$ measurement data in South Korea and suggested $PM_{10}$ concentration metrics as long-term exposures for assessing health effects in cohort studies. We obtained hourly $PM_{10}$ data from the National Institute of Environmental Research for 2001~2012 in South Korea. We investigated spatial distribution of monitoring sites using the density and proximity in each of the 16 metropolitan cities and provinces. The temporal characteristics of $PM_{10}$ measurement data were examined by annual/seasonal/diurnal patterns across urban background monitoring sites after excluding Asian dust days. For spatial characteristics of $PM_{10}$ measurement data, we computed coefficient of variation (CV) and coefficient of divergence (COD). Based on temporal and spatial investigation, we suggested preferred long-term metrics for cohort studies. In 2010, 294 urban background monitoring sites were located in South Korea with a site over an area of $415.0km^2$ and distant from another site by 31.0 km on average. Annual average $PM_{10}$ concentrations decreased by 19.8% from 2001 to 2012, and seasonal $PM_{10}$ patterns were consistent over study years with higher concentrations in spring and winter. Spatial variability was relatively small with 6~19% of CV and 21~46% of COD across 16 metropolitan cities and provinces in 2010. To maximize spatial coverage and reflect temporal and spatial distributions, our suggestion for $PM_{10}$ metrics representing long-term exposures was the average for one or multiple years after 2009. This study provides the knowledge of all available $PM_{10}$ data measured at national regulatory monitoring sites in South Korea and the insight of the plausible longterm exposure metric for cohort studies.

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References

  1. Beelen, R., O. Raaschou-Nielsen, M. Stafoggia, Z.J. Andersen, G. Weinmayr, B. Hoffmann, K. Wolf, E. Samoli, P. Fischer, M. Nieuwenhuijsen, P. Vineis, W.W. Xun, K. Katsouyanni, K. Dimakopoulou, A. Oudin, B. Forsberg, L. Modig, A.S. Havulinna, T. Lanki, A. Turunen, B. Oftedal, W. Nystad, P. Nafstad, U. De Faire, N.L. Pedersen, C.G. Ostenson, L. Fratiglioni, J. Penell, M. Korek, G. Pershagen, K.T. Eriksen, K. Overvad, T. Ellermann, M. Eeftens, P.H. Peeters, K. Meliefste, M. Wang, B. Bueno-de-Mesquita, D. Sugiri, U. Kramer, J. Heinrich, K. de Hoogh, T. Key, A. Peters, R. Hampel, H. Concin, G. Nagel, A. Ineichen, E. Schaffner, N. Probst-Hensch, N. Kunzli, C. Schindler, T. Schikowski, M. Adam, H. Phuleria, A. Vilier, F. Clavel-Chapelon, C. Declercq, S. Grioni, V. Krogh, M.Y. Tsai, F. Ricceri, C. Sacerdote, C. Galassi, E. Migliore, A. Ranzi, G. Cesaroni, C. Badaloni, F. Forastiere, I. Tamayo, P. Amiano, M. Dorronsoro, M. Katsoulis, A. Trichopoulou, B. Brunekreef, and G. Hoek (2014) Effects of longterm exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project, Lancet, 383(9919), 785-795. https://doi.org/10.1016/S0140-6736(13)62158-3
  2. Bell, M.L., K. Ebisu, and R.D. Peng (2011) Community-level spatial heterogeneity of chemical constituent levels of fine particulates and implications for epidemiological research, J. Expo. Sci. Environ. Epidemiol., 21(4), 372-384. https://doi.org/10.1038/jes.2010.24
  3. Blanchard, C.L., E.L. Carr, J.F. Collins, T.B. Smith, D.E. Lehrman, and H.M. Michaels (1999) Spatial representativeness and scales of transport during the 1995 integrated monitoring study in California's San Joaquin Valley, Atmos. Environ., 33(29), 4775-4786. https://doi.org/10.1016/S1352-2310(99)00284-8
  4. Brauer, M., M. Amann, R.T. Burnett, A. Cohen, F. Dentener, M. Ezzati, S.B. Henderson, M. Krzyzanowski, R.V. Martin, R. Van Dingenen, A. van Donkelaar, and G.D. Thurston (2012) Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution, Environ. Sci. Technol., 46(2), 652-660. https://doi.org/10.1021/es2025752
  5. Chan, L.Y., W.S. Kwok, S.C. Lee, and C.Y. Chan (2001) Spatial variation of mass concentration of roadside suspended particulate matter in metropolitan Hong Kong, Atmos. Environ., 35(18), 3167-3176. https://doi.org/10.1016/S1352-2310(00)00505-7
  6. Cyrys, J., M. Eeftens, J. Heinrich, C. Ampe, A. Armengaud, R. Beelen, T. Bellander, T. Beregszaszi, M. Birk, G. Cesaroni, M. Cirach, K. de Hoogh, A. De Nazelle, F. de Vocht, C. Declercq, A. Dedele, K. Dimakopoulou, K. Eriksen, C. Galassi, R. Grauleviciene, G. Grivas, O. Gruzieva, A.H. Gustafsson, B. Hoffmann, M. Iakovides, A. Ineichen, U. Kramer, T. Lanki, P. Lozano, C. Madsen, K. Meliefste, L. Modig, A. Molter, G. Mosler, M. Nieuwenhuijsen, M. Nonnemacher, M. Oldenwening, A. Peters, S. Pontet, N. Probst-Hensch, U. Quass, O. Raaschou-Nielsen, A. Ranzi, D. Sugiri, E.G. Stephanou, P. Taimisto, M.Y. Tsai, E. Vaskovi, S. Villani, M. Wang, B. Brunekreef, and H. Hoek (2012) Variation of $NO_2$ and NOx concentrations between and within 36 European study areas: results from the ESCAPE study, Atmos. Environ., 62, 374-390. https://doi.org/10.1016/j.atmosenv.2012.07.080
  7. Cyrys, J., M. Pitz, J. Heinrich, H.E. Wichmann, and A. Peters (2008) Spatial and temporal variation of particle number concentration in Augsburg, Germany, Sci. Total Environ., 401(1), 168-175. https://doi.org/10.1016/j.scitotenv.2008.03.043
  8. Diggle, P.J., R. Menezes, and T.L. Su (2010) Geostatistical inference under preferential sampling, J. R. Stat. Soc. Ser. C Appl. Stat., 59(2), 191-232. https://doi.org/10.1111/j.1467-9876.2009.00701.x
  9. Eeftens, M., M.Y. Tsai, C. Ampe, B. Anwander, R. Beelen, T. Bellander, G. Cesaroni, M. Cirach, J. Cyrys, K. de Hoogh, A. De Nazelle, F. de Vocht, C. Declercq, A. Dedele, K. Eriksen, C. Galassi, R. Grazuleviciene, G. Grivas, J. Heinrich, B. Hoffmann, M. Iakovides, A. Ineichen, K. Katsouyanni, M. Korek, U. Kramer, T. Kuhlbusch, T. Lanki, C. Madsen, K. Meliefste, A. Molter, G. Mosler, M. Nieuwenhuijsen, M. Oldenwening, A. Pennanen, N. Probst-Hensch, U. Quass, O. Raaschou-Nielsen, A. Ranzi, E. Stephanou, D. Sugiri, O. Udvardy, E. Vaskovi, G. Weinmayr, B. Brunekreef, and A. De Nazelle (2012a) Spatial variation of $PM_{2.5}$, $PM_{10}$, $PM_{2.5}$ absorbance and PM coarse concentrations between and within 20 European study areas and the relationship with $NO_2$-Results of the ESCAPE project, Atmos. Environ., 62, 303-317. https://doi.org/10.1016/j.atmosenv.2012.08.038
  10. Eeftens, M., R. Beelen, K. de Hoogh, T. Bellander, G. Cesaroni, M. Cirach, C. Declercq, E. Dons, A. de Nazelle, K. Dimakopoulou, K. Eriksen, G. Falq, P. Fischer, C. Galassi, R. Grazuleviciene, J. Heinrich, B. Hoffmann, M. Jerrett, D. Keidel, M. Korek, T. Lanki, S. Lindley, C. Madsen, A. Molter, G. Nador, M. Nieuwenhuijsen, M. Nonnemacher, X. Pedeli, O. Raaschou-Nielsen, E. Patelarou, U. Quass, A. Ranzi, C. Schindler, M. Stempfelet, E. Stephanou, D. Sugiri, M.Y. Tsai, T. Yli-Tuomi, M.J. Varro, D. Vienneau, S.V. Klot, K. Wolf, B. Brunekreef, and G. Hoek (2012b) Development of land use regression models for $PM_{2.5}$, $PM_{2.5}$ absorbance, $PM_{10}$ and PMcoarse in 20 European study areas; results of the ESCAPE project, Environ. Sci. Technol., 46 (20), 11195-11205. https://doi.org/10.1021/es301948k
  11. Fang, G.C. and S.C. Chang (2010) Atmospheric particulate ($PM_{10}$ and $PM_{2.5}$) mass concentration and seasonal variation study in the Taiwan area during 2000-2008, Atmos. Res., 98(2), 368-377. https://doi.org/10.1016/j.atmosres.2010.07.005
  12. Ha, E.H., Y.C. Hong, B.E. Lee, B.H. Woo, J. Schwartz, and D.C. Christiani (2001) Is air pollution a risk factor for low birth weight in Seoul?, Epidemiology, 12 (6), 643-648. https://doi.org/10.1097/00001648-200111000-00011
  13. Hart, J.E., J.D. Yanosky, R.C. Puett, L. Ryan, D.W. Dockery, T.J. Smith, E. Garshick, and F. Laden (2009) Spatial modeling of $PM_{10}$ and $NO_2$ in the continental United States, 1985-2000, Environ. Health Persp., 117(11), 1690-1696. https://doi.org/10.1289/ehp.0900840
  14. Hauck, H., A. Berner, B. Gomiscek, S. Stopper, H. Puxbaum, M. Kundi, and O. Preining (2004) On the equivalence of gravimetric PM data with TEOM and betaattenuation measurements, J. Aerosol Sci., 35(9), 1135-1149. https://doi.org/10.1016/j.jaerosci.2004.04.004
  15. Heo, J.B., P.K. Hopke, and S.M. Yi (2009) Source apportionment of $PM_{2.5}$ in Seoul, Korea, Atmos. Chem. Phys., 9(14), 4957-4971. https://doi.org/10.5194/acp-9-4957-2009
  16. Hoek, G., R. Beelen, K. de Hoogh, D. Vienneau, J. Gulliver, P. Fischer, and D. Briggs (2008) A review of landuse regression models to assess spatial variation of outdoor air pollution, Atmos. Environ., 42(33), 7561-7578. https://doi.org/10.1016/j.atmosenv.2008.05.057
  17. Hoek, G., R.M. Krishnan, R. Beelen, A. Peters, B. Ostro, B. Brunekreef, and J.D. Kaufman (2013) Long-term air pollution exposure and cardio-respiratory mortality: a review, Environ. Health, 12, 43. https://doi.org/10.1186/1476-069X-12-43
  18. Hong, Y.C., J.T. Lee, H. Kim, E.H. Ha, J. Schwartz, and D.C. Christiani (2002) Effects of air pollutants on acute stroke mortality, Environ. Health Persp., 110(2), 187-191. https://doi.org/10.1289/ehp.02110187
  19. Jerrett, M., A. Arain, P. Kanaroglou, B. Beckerman, D. Potoglou, T. Sahsuvaroglu, J. Morrison, and C. Giovis (2005) A review and evaluation of intraurban air pollution exposure models, J. Expo. Anal. Environ. Epidemiol., 15(2), 185-204. https://doi.org/10.1038/sj.jea.7500388
  20. Jones, N.C., C.A. Thornton, D. Mark, and R.M. Harrison (2000) Indoor/outdoor relationships of particulate matter in domestic homes with roadside, urban and rural locations, Atmos. Environ., 34(16), 2603-2612. https://doi.org/10.1016/S1352-2310(99)00489-6
  21. Kim, E., H. Park, Y.C. Hong, M. Ha, Y. Kim, B.N. Kim, Y. Kim, Y.M. Roh, B.E. Lee, J.M. Ryu, B.M. Kim, and E.H. Ha (2014) Prenatal exposure to $PM_{10}$ and $NO_2$ and children's neurodevelopment from birth to 24 months of age: Mothers and Children's Environmental Health (MOCEH) study, Sci. Total Environ., 481, 439-445. https://doi.org/10.1016/j.scitotenv.2014.01.107
  22. Kim, S.Y., L. Sheppard, T.V. Larson, J.D. Kaufman, and S. Vedal (2015) Combining $PM_{2.5}$ Component Data from Multiple Sources: Data Consistency and Characteristics Relevant to Epidemiological Analyses of Predicted Long-Term Exposures, Environ. Health Persp., 123(7), 651-658. https://doi.org/10.1289/ehp.1307744
  23. Krudysz, M., K. Moore, M. Geller, C. Sioutas, and J. Froines (2009) Intra-community spatial variability of particulate matter size distributions in Southern California/Los Angeles, Atmos. Chem. Phys., 9(3), 1061-1075. https://doi.org/10.5194/acp-9-1061-2009
  24. Kunzli, N. and I.B. Tager (1997) The semi-individual study in air pollution epidemiology: a valid design as compared to ecologic studies, Environ. Health Persp., 105(10), 1078-1083. https://doi.org/10.1289/ehp.971051078
  25. Lee, A., A. Szpiro, S.Y. Kim, and L. Sheppard (2015) Impact of preferential sampling on exposure prediction and health effect inference in the context of air pollution epidemiology, Environmetrics, 26 (4), 255-267. https://doi.org/10.1002/env.2334
  26. Lee, B.J., B. Kim, and K. Lee (2014) Air pollution exposure and cardiovascular disease, Toxicol. Res., 30(2), 71-75. https://doi.org/10.5487/TR.2014.30.2.071
  27. Lee, J.T., D. Shin, and Y. Chung (1999) Air pollution and daily mortality in Seoul and Ulsan, Korea, Environ. Health Persp., 107(2), 149-154. https://doi.org/10.1289/ehp.99107149
  28. Lee, J.T., H. Kim, H. Song, Y.C. Hong, Y.S. Cho, S.Y. Shin, Y.J. Hyun, and Y.S. Kim (2002) Air pollution and asthma among children in Seoul, Korea, Epidemiology, 13(4), 481-484. https://doi.org/10.1097/00001648-200207000-00018
  29. Li, R., C. Wiedinmyer, and M.P. Hannigan (2013) Contrast and correlations between coarse and fine particulate matter in the United States, Sci. Total Environ., 456, 346-358.
  30. Lim, Y.H., H. Kim, J.H. Kim, S. Bae, H.Y. Park, and Y.C. Hong (2012) Air pollution and symptoms of depression in elderly adults, Environ. Health Persp., 120(7), 1023-1028. https://doi.org/10.1289/ehp.1104100
  31. Ministry of environment (MOE) (2011) Guidelines for installation and management of national air quality monitoring networks. (in Korean)
  32. National institute of environmental research and Ministry of environment (NIER) (2002-2013) Annual Report of Ambient Air Quality in Korea. (in Korean)
  33. Nguyen, H.T. and K.H. Kim (2006a) Evaluation of $SO_2$ pollution levels between four different types of air quality monitoring stations, Atmos. Environ., 40(36), 7066-7081. https://doi.org/10.1016/j.atmosenv.2006.06.011
  34. Nguyen, H.T. and K.H. Kim (2006b) Comparison of spatiotemporal distribution patterns of $NO_2$ between four different types of air quality monitoring stations, Chemosphere, 65(2), 201-212. https://doi.org/10.1016/j.chemosphere.2006.02.061
  35. Ott, D.K., N. Kumar, and T.M. Peters (2008) Passive sampling to capture spatial variability in $PM_{{10}-{2.5}}$, Atmos. Environ., 42(4), 746-756. https://doi.org/10.1016/j.atmosenv.2007.09.058
  36. Pinto, J.P., A.S. Lefohn, and D.S. Shadwick (2004) Spatial States, J. Air. Waste Manage. Assoc., 54(4), 440-449. https://doi.org/10.1080/10473289.2004.10470919
  37. Pope III, C.A. and D.W. Dockery (2006) Health effects of fine particulate air pollution: lines that connect, J. Air. Waste. Manage. Assoc., 56(6), 709-742. https://doi.org/10.1080/10473289.2006.10464485
  38. Qu, W.J., R. Arimoto, X.Y. Zhang, C.H. Zhao, Y.Q. Wang, L.F. Sheng, and G. Fu (2010) Spatial distribution and interannual variation of surface $PM_{10}$ concentrations over eighty-six Chinese cities, Atmos. Chem. Phys., 10(12), 5641-5662. https://doi.org/10.5194/acp-10-5641-2010
  39. Querol, X., A. Alastuey, T. Moreno, M.M. Viana, S. Castillo, J. Pey, S. Rodriguez, B. Artinano, P. Salvador, M. Sanchez, S. Garcia Dos Santos, M.D. Herce Garraleta, R. Fernadez-Patier, S. Moreno-Grau, L. Negral, M.C. Minguillon, E. Monfort, M.J. Sanz, R. Palomo-Marin, E. Pinlla-Gil, E. Cuevas, J. De La Rosa, and A. Sanchez De La Campa (2008) Spatial and temporal variations in airborne particulate matter ($PM_{10}$ and $PM_{2.5}$) across Spain 1999-2005, Atmos. Environ., 42(17), 3964-3979. https://doi.org/10.1016/j.atmosenv.2006.10.071
  40. Shin, S.E., C.H. Jung, and Y.P. Kim (2011) Analysis of the measurement difference for the $PM_{10}$ concentrations between Beta-ray absorption and gravimetric methods at Gosan, Aerosol Air. Qual. Res., 11(7), 846-853.
  41. Son, J.Y., J.T. Lee, Y.H. Park, and M.L. Bell (2013) Shortterm effects of air pollution on hospital admissions in Korea, Epidemiology, 24(4), 545-554. https://doi.org/10.1097/EDE.0b013e3182953244
  42. Son, J.Y., M.L. Bell, and J.T. Lee (2011) Survival analysis to estimate the association between long-term exposure to different sizes of airborne particulate matter and risk of infant mortality using a birth cohort in Seoul, Korea, Environ. Health Persp., 119(5), 725-730. https://doi.org/10.1289/ehp.1002364
  43. Wilson, J.G., S. Kingham, J. Pearce, and A.P. Sturman (2005) A review of intraurban variations in particulate air pollution: Implications for epidemiological research, Atmos. Environ., 39(34), 6444-6462. https://doi.org/10.1016/j.atmosenv.2005.07.030
  44. Yang, K.L. (2002) Spatial and seasonal variation of $PM_{10}$ mass concentrations in Taiwan, Atmos. Environ., 36(21), 3403-3411. https://doi.org/10.1016/S1352-2310(02)00312-6
  45. Yanosky, J.D., C.J. Paciorek, J. Schwartz, F. Laden, R. Puett, and H.H. Suh (2008) Spatio-temporal modeling of chronic $PM_{10}$ exposure for the Nurses' Health Study, Atmos. Environ., 42(18), 4047-4062. https://doi.org/10.1016/j.atmosenv.2008.01.044
  46. Yi, O., Y.C. Hong, and H. Kim (2010) Seasonal effect of $PM_{10}$ concentrations on mortality and morbidity in Seoul, Korea: a temperature-matched case-crossover analysis, Environ. Res., 110(1), 89-95. https://doi.org/10.1016/j.envres.2009.09.009

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