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http://dx.doi.org/10.5467/JKESS.2017.38.4.283

Analysis of Empirical Multiple Linear Regression Models for the Production of PM2.5 Concentrations  

Choo, Gyo-Hwang (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Lee, Kyu-Tae (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Jeong, Myeong-Jae (Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University)
Publication Information
Journal of the Korean earth science society / v.38, no.4, 2017 , pp. 283-292 More about this Journal
Abstract
In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.
Keywords
satellite; aerosol optical thickness; particulate matter; multiple linear regression model; $PM_{2.5}$;
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1 Xin, J., Zhang, Q., Wang, L., Gong, C., Wang, Y., Liu, Z., and Gao, W., 2014, The empirical relationship between the $PM_{2.5}$ concentration and aerosol optical depth over the background of North China from 2009 to 2011, Atmospheric Research, 138, 179-188.   DOI
2 Zhao, H., Che, H., Zhang, X., Ma, Y., Wang, Y., Wang, H., and Wang, Y., 2013, Characteristics of visibility and particulate matter (PM) in an urban area of Northeast China., Atmospheric Pollution Research, 4, 427-434.   DOI
3 Zheng, J., Che, W., Zheng, Z., Chen, L., and Zhong, L., 2013, Analysis of spatial and temporal variability of PM10 concentrations using MODIS aerosol optical thickness in the Pearl River Delta region, China, Aerosol and Air Quality Research, 13, 862-876.
4 Benas, N., Beloconi, A., and Chrysoulakis, N., 2013, Estimation of urban PM10 concentration, based on MODIS and MERIS/AATSR synergistic observations, Atmospheric Environment, 79, 448-454.   DOI
5 Brook, R.D., Rajagopalan, S., Pope, C.A., Brook, J.R., Bhatnagar, A., Diez-Roux, A.V., Holguin, F., Hong, Y.L., Luepker, R.V., Mittleman, M.A., Peters, A., Siscovick, D., Smith, S.C., Whitsel, L., Kaufman, J.D., Epidemiol, A.H.A.C., Dis, D.K.C., and Metab, C.N.P.A., 2010, Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American heart association, Circulation, 121, 2331-2378.   DOI
6 Environmental Protection Agency (EPA), 2015, PM centers, http://www.epa.gov/ncer/science/pm/centers.html, Accessed on 2 October 2015.
7 Chen, B.B., Sverdlik, L.G., Imashev, S.A., Solomon, P.A., Lantz, J., Schauer, J.J., Shafer, M.M., and Artamonova, M.S., 2013, Empirical relationship between particulate matter and aerosol optical depth over Northern Tien-Shan, Central Asia, Air Quality, Atmosphere and Health, 6, 385-396.   DOI
8 Chun, Y. and Lim, J.Y., 2004, The recent characteristics of Asian dust and haze events in Seoul, Korea, Meteorology and Atmospheric Physics, 87, 143-152.
9 Eck, T.F., Holben, B.N., Reid, J.S., Dubovik, O., Smirnov, A., O'Neill, N.T., Slutsker, I., and Kinne, S., 1999, Wavelength dependence of the optical depth of biomass burning, urban and desert dust aerosols, Journal of Geophysical Research, 104, 31333-31349.   DOI
10 Holben, B.N., Tanre, D., Smirnov, A., Eck, T.F., Slutsker, I., Abuhassan, N., Newcomb, W.W., Schafer, J.S., Chatenet, B., Lavenu, F., Kaufman, Y.J., Vande Castle, J., Setzer, A., Markham, B., Clark, D., Frouin, R., Halthore, R., Karneli, A., O'Neill, N.T., Pietras, C., Pinker, R.T., Voss, K., and Zibordi, G., 2001, An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET, Journal of Geophysical Research, 106(D11), 12067-12097, doi:10.1029/2001JD900014.   DOI
11 Hoek, G., Krishnan, R.M., Beelen, R., Peters, A., Ostro, B., Brunekreef, B., and Kaufman, J.D., 2013, Long-term air pollution exposure and cardio-respiratory mortality: a review, Environmental Health, 12, doi:10.1186/1476-069X-12-43.   DOI
12 International Panel on Climate Change (IPCC), 2013, Climate Change 2013, The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
13 Kim, H.S., Yoon, M.B., and Sohn, J.J., 2010, An Analysis on the Episodes of Large-scale Transport of Natural Airborne Particles and Anthropogenically Affected Particles from Different Sources in the East Asian Continent in 2008, Journal of the Korean Earth Science Society, 31, 600-607. (in Korean)   DOI
14 Kaufman, Y.J., Tanre, D., and Boucher, O., 2002, A satellite view of aerosols in the climate system, Nature, 419, 215-223.   DOI
15 Kim, B.K., Lee, D.I., Kim, J.C., and Lee, J.H., 2012, Characteristics of Diurnal Variation of High $PM_{2.5}$ Concentration by Spatio-Temporal Wind System in Busan, Korea, Journal of the Korean Earth Science Society, 33, 469-480. (in Korean)   DOI
16 Kim, H.S., Kim, J.M., and Sohn, J.J., 2012, An Analysis of MODIS Aerosol Optical Properties and Ground-based Mass Concentrations in Central Korea in 2009, Journal of the Korean Earth Science Society, 33, 269-279. (in Korean)   DOI
17 Lee, K.H., Lee, D.H., and Kim, Y.J., 2006, Application of MODIS satellite observation data for air quality forecast, Journal of Korean Society for Atmospheric Environment, 22(6), 851-862. (in Korean)
18 Lee, K.H. and Park, S.S., 2012, Relationship between $PM_{2.5}$ mass concentrations and MODIS aerosol optical thickness at Dukjuk and Jeju island, Korean Journal of Remote Sensing, 28(4), 449-458. (in Korean)   DOI
19 Li, C., Tsa,y S.C., Hsu, N.C., Kim, J.Y., Howell S.G., Huebert B.J., Ji Q., Jeong M.-J., Wang S.-H., Hansell R.A., and Bell S.W., 2012, Characteristics and composition of atmospheric aerosols in Phimai, central Thailand during BASE-ASIA, Atmospheric Environment, doi:10.1016/j.atmosenv.2012.04.003.   DOI
20 Liu, Y., Sarnat, J.A., Kilaru V., Jacob, D.J., and Koutrakis, P., 2005, Estimating ground-level $PM_{2.5}$ in the Eastern United States using satellite remote sensing, Environmental Science and Technology, 39, 3269-3278.   DOI
21 Schwartz, J., Dockery, W., and Neas, L.M., 1996, Is daily mortality associated specifically with fine particles, Journal of the Air & Waste Management Association, 46, 927-939.   DOI
22 Liu, Y., Franklin, M., Kahn, R., and Koutrakis, P., 2007, Using aerosol optical thickness to predict ground-level $PM_{2.5}$ concentrations in the St. Louis area: A comparison between MISR and MODIS, Remote Sensing of Environment, 107, 33-44.   DOI
23 Liu, X., Cheng, Y., Zhang, Y., Jung, J., Sugimoto, N., Chang, S.Y., Kim, Y.J., Fan, S., and Zeng, L., 2008, Influences of relative humidity and particle chemical composition on aerosol scattering properties during the 2006 PRD campaign, Atmospheric Environment, 42, 1525-1536.   DOI
24 Pan, X.L., Yan, P., Tang, J., Ma, J.Z., Wang, Z.F., Gbaguidi, A., and Sun, Y.L., 2009, Observational study of influence of aerosol hygroscopic growth on scattering coefficient over rural area near Beijing mega-city, Atmospheric Chemistry and Physics, 9, 7519-7530.   DOI
25 Seo, S., Kim J., Jeong, U., Kim, W., Holben, B.N., Kim S.-W., Song C.H., and Lim J.H., 2015, Estimation of $PM_{10}$ concentrations over Seoul using multiple empirical models with AERONET and MODIS data collected during the DRAGON-Asia campaign, Atmospheric Chemistry and Physics, 15, 319-334.   DOI
26 Tiwari, S., Chate, D.M., Srivastava, A.K., Bisht, D.S. and Padmanabhamurty, B., 2012, Assessments of PM1, $PM_{2.5}$ and $PM_{10}$ concentrations in Delhi at different mean cycles. Geofizika, 29, 51-57.
27 World Health Organization, 2006, Health risks of particulate matter from long-range transboundary air pollution, Eur. Cent. For Environ. And Health, Bonn, Germany.