Ground-Level Ozone Pollution in Upper Northern, Thailand : An ArcGIS-Based Approach

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Supawan Srirattana

Abstract

Ground-level ozone in the air we breathe even relatively low levels can cause health effects. Thus, it is important to analyze the spatial-temporal ozone concentrations. The IDW interpolation technique by ArcMap 10.5® software was used to simulate and access ground-level ozone data in areas where without ambient air quality monitoring stations in 8 provinces (Chiang Rai, Chiang Mai, Phrae, Nan, Phayao, Lampang, Lamphun, and Mae Hong Son) during the year 2017 – 2019. The ground-level zone input data were obtained from the pollution control department, Thailand. The Mean Error (ME) and Root Mean Squared Error (RMSE) were used to find the most suitable power for IDW interpolation. The IDW interpolation with power 3 was represented the best condition. IDW interpolation of monthly maximum 1-hour reveal that orange and red were found as the major of AQI colors in all 8 provinces. Orange was found in every province, while red was only distributed in Chiang Rai and some areas in Chiang Mai during ozone crisis (February to June). For monthly maximum 8-hour, AQI ratings were ranging from green to purple, and most areas were faced with ozone pollution in the red to the purple. Nevertheless, July to January was rarely reached a high level of ozone. Additionally, the IDW interpolation map of Chiang Mai in May 2017 was chosen for discussion as an example to converted data from 2D - spatiotemporal interpolation map to the number of sub-districts in which ozone AQI levels were got to the unhealthy zone.

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References

AirNow. (2021). Air Quality Index (AQI) Basics. https://www.airnow.gov/aqi/aqi-basics/

AirNow. (2022). What Is the AQI? https://www.airnow.gov/education/students/what-is-the-aqi/

Akkala, A., Devabhaktuni, V., & Kumar, A. (2010). Interpolation techniques and associated software for environmental data. Environmental Progress & Sustainable Energy, 29(2), 134-141.https://doi.org/https://doi.org/10.1002/ep.10455

Asian Institute of Technology. (2020). Hidden Danger! Summer ‘Ozone’ Spikes.

https://www.ait.ac.th/2020/03/hidden-danger-summer-ozone-spikes-ait-expert-dr-ekbordin-winijku-advises-avoiding-outdoor-activities/

Bartier, P. M., & Keller, C. P. (1996). Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Computers & Geosciences, 22(7), 795-799.https://doi.org/https://doi.org/10.1016/0098-3004(96)00021-0

Beelen, R., Hoek, G., Pebesma, E., Vienneau, D., de Hoogh, K., & Briggs, D. J. (2009). Mapping of background air pollution at a fine spatial scale across the European Union. Sci Total Environ, 407(6), 1852-1867.https://doi.org/10.1016/j.scitotenv.2008.11.048

Bell, M. L. (2006). The use of ambient air quality modeling to estimate individual and population exposure for human health research: a case study of ozone in the Northern Georgia Region of the United States. Environ Int, 32(5), 586-593.https://doi.org/10.1016/j.envint.2006.01.005

Bureau of Registration Administration. (2021). Official statistics registration systems. https://stat.bora.dopa.go.th/new_stat/webPage/statByYear.php

Chontanat Suwan. (2022). GIS DATA. https://csuwan.weebly.com/360436343623360936603650362736213604--download.html

Eldrandaly, K. A., & Abu-Zaid, M. S. (2015). Comparison of Six GIS-Based Spatial Interpolation Methods for Estimating Air Temperature in Western Saudi Arabia. 2015, 18(1), 38-45.https://doi.org/10.3808/jei.201100197

Energy Policy and Planning office. (2022). The provinces and administrative areas.http://www.e-report.energy.go.th/area.html

GISGeography. (2021). Inverse Distance Weighting (IDW) Interpolation.https://gisgeography.com/inverse-distance-weighting-idw-interpolation/

Gong, G., Mattevada, S., & O'Bryant, S. E. (2014). Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas. Environ Res, 130, 59-69.https://doi.org/10.1016/j.envres.2013.12.005

Hammond, D., Conlon, K., Barzyk, T., Chahine, T., Zartarian, V., & Schultz, B. (2011). Assessment and application of national environmental databases and mapping tools at the local level to two community case studies. Risk Anal, 31(3), 475-487.https://doi.org/10.1111/j.1539-6924.2010.01527.x

Isaaks, E. H. a. S., R.M. (1989). An Introduction to Applied Geostatistics (Vol. 1). Oxford University Press N.

Jarvis, C. H., & Stuart, N. (2001). A Comparison among Strategies for Interpolating Maximum and Minimum Daily Air Temperatures. Part II: The Interaction between Number of Guiding Variables and the Type of Interpolation Method. Journal of Applied Meteorology, 40(6), 1075-1084. https://doi.org/10.1175/1520-0450(2001)040<1075:ACASFI>2.0.CO;2

Jeffrey, S., Carter, J., Moodie, K., & Beswick, A. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling & Software, 16, 309-330. https://doi.org/10.1016/S1364-8152(01)00008-1

Jung, S.-W., Lee, K., Cho, Y.-S., Choi, J.-H., Yang, W., Kang, T.-S., Park, C., Kim, G.-B., Yu, S.-D., & Son, B.-S. (2016). Association by Spatial Interpolation between Ozone Levels and Lung Function of Residents at an Industrial Complex in South Korea. International journal of environmental research and public health, 13(7), 728.https://doi.org/10.3390/ijerph13070728

Kravchenko, A., & Bullock, D. G. (1999). A Comparative Study of Interpolation Methods for Mapping Soil Properties. Agronomy Journal, 91(3), 393-400. https://doi.org/https://doi.org/10.2134/agronj1999.00021962009100030007x

Li, L., Zhou, X., Kalo, M., & Piltner, R. (2016). Spatiotemporal Interpolation Methods for the Application of Estimating Population Exposure to Fine Particulate Matter in the Contiguous U.S. and a Real-Time Web Application. International journal of environmental research and public health, 13(8).https://doi.org/10.3390/ijerph13080749

Maduako, I., Ebinne, E., Idorenyin, U., & Ndukwu, R. (2017). Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study. Journal of Geographic Information System, 09, 354-371.

https://doi.org/10.4236/jgis.2017.93022

Mishra, R., Kumar, A., & Singh, S. (2015). GIS Application in Urban Traffic Air Pollution Exposure Study: A Research Review. Suan Sunandha Science and Technology Journal, 2.

Munyati, C., & Sinthumule, N. I. (2021). Comparative suitability of ordinary kriging and Inverse Distance Weighted interpolation for indicating intactness gradients on threatened savannah woodland and forest stands. Environmental and Sustainability Indicators, 12, 100151. https://doi.org/https://doi.org/10.1016/j.indic.2021.100151

National Aeronautics and Space Administration. (2003). Chemistry in the Sunlight.

https://earthobservatory.nasa.gov/features/ChemistrySunlight/chemistry_sunlight3.php

Pinichka, C., Makka, N., Sukkumnoed, D., Chariyalertsak, S., Inchai, P., & Bundhamcharoen, K. (2017a). Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach. PloS one, 12(12), e0189909-e0189909.

https://doi.org/10.1371/journal.pone.0189909

Pinichka, C., Makka, N., Sukkumnoed, D., Chariyalertsak, S., Inchai, P., & Bundhamcharoen, K. (2017b). Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach. PloS one, 12(12), e0189909.https://doi.org/10.1371/journal.pone.0189909

Pollution Control Department. (2020). Thailand State of Pollution 2020.http://air4thai.pcd.go.th/webV2/download.php

Pollution Control Department. (2021). Thailand's air quality and situation reports: Air Quality Map. http://air4thai.pcd.go.th/webV2/index.php

Pollution Control Department. (2022). Regional Air Quality and Situation Reports.http://air4thai.pcd.go.th/webV3/#/Home

Qiao, P., Lei, M., Yang, S., Yang, J., Guo, G., & Zhou, X. (2018). Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing. Environmental Science and Pollution Research, 25(16), 15597-15608.https://doi.org/10.1007/s11356-018-1552-y

Robichaud, A., & Ménard, R. (2014). Multi-year objective analyses of warm season ground-level ozone and PM2.5 over North America using real-time observations and Canadian operational air quality models. Atmos. Chem. Phys., 14(4), 1769-1800. https://doi.org/10.5194/acp-14-1769-2014

Rojas-Avellaneda, D. (2007). Spatial interpolation techniques for stimating levels of pollutant concentrations in the atmosphere. Revista Mexicana de Física, 53(6).

Royal Irrigation Department. (2018). Spatial precipitation analysis from ground rainfall data and satellite imagery together with topographic data: case study in southern Thailand.http://kmcenter.rid.go.th/kchydhome/km_hydro/tran/1.pdf

Rytkönen, M. J. (2004). Not all maps are equal: GIS and spatial analysis in epidemiology. Int J Circumpolar Health, 63(1), 9-24.

https://doi.org/10.3402/ijch.v63i1.17642

Sajjadi, S. A., Zolfaghari, G., Adab, H., Allahabadi, A., & Delsouz, M. (2017). Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality. MethodsX, 4, 372-390.https://doi.org/https://doi.org/10.1016/j.mex.2017.09.006

Simpson, G., & Wu, Y. H. (2014). Accuracy and Effort of Interpolation and Sampling: Can GIS Help Lower Field Costs? ISPRS International Journal of Geo-Information, 3(4), 1317-1333.

https://www.mdpi.com/2220-9964/3/4/1317

State of Global Air. (2020). Ozone Exposure Ground-level ozone pollution is on the rise, contributing to health problems and climate change.https://www.stateofglobalair.org/air/ozone#climate-connection

Stockholm Environment Institute. (2021). Air quality in Thailand Understanding the regulatory context. https://cdn.sei.org/wp-content/uploads/2021/02/210212c-killeen-archer-air-quality-in-thailand-wp-2101e-final.pdf

United States Census Bureau. (2022). Cartographic Boundary Files - Shapefile.https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html

US. EPA. (2014). Air quality index: A guide to air quality and your health.https://www.airnow.gov/sites/default/files/2018-04/aqi_brochure_02_14_0.pdf

US. EPA. (2021). Ground-level Ozone Pollution: Ground-level Ozone Basics.https://www.epa.gov/ground-level-ozone-pollution/ground-level-ozone-basics#wwh

US. EPA. (2021a). Ground-level Ozone Pollution.https://www.epa.gov/ground-level-ozone-pollution

US. EPA. (2021b). Ground-level Ozone Pollution: Health Effects of Ozone Pollution.https://www.epa.gov/ground-level-ozone-pollution/health-effects-ozone-pollution

Viroat Srisurapanon, & Chana Wanichapun. (2019). Environmental Policies in Thailand and their Effects.https://www.un.org/esa/gite/iandm/viroatpaper.pdf

Weather Spark. (2022). The Weather Year Round Anywhere on Earth.https://weatherspark.com/

Weber, D., & Englund, E. (1992). Evaluation and comparison of spatial interpolators. Mathematical Geology, 24(4), 381-391.https://doi.org/10.1007/BF00891270

Willmott, C. J. (1982). Some Comments on the Evaluation of Model Performance. Bulletin of the American Meteorological Society, 63(11), 1309-1313. https://doi.org/10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2

Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O'Donnell, J., & Rowe, C. M. (1985). Statistics for the evaluation and comparison of models. Journal of Geophysical Research: Oceans, 90(C5), 8995-9005.https://doi.org/https://doi.org/10.1029/JC090iC05p08995

Wuthiwongyothin, S., Kalkan, C., & Panyavaraporn, J. (2021). Evaluating Inverse Distance Weighting and Correlation Coefficient Weighting Infilling Methods on Daily Rainfall Time Series. SNRU Journal of Science and Technology, 13(2), 71-79. https://ph01.tci-thaijo.org/index.php/snru_journal/article/view/243635/166054