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Article

Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia

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Department of Geomatics, National Cheng Kung University, Tainan City 70101, Taiwan
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Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya City 60111, Indonesia
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Department of Safety, Health, and Environmental Engineering, Ming Chih University of Technology, New Taipei City 24301, Taiwan
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Department of Leisure Industry and Health Promotion, National Taipei University of Nursing and Health Sciences, Taipei City 112303, Taiwan
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Research Center for Environmental Changes, Academia Sinica, Taipei City 11529, Taiwan
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Department of Atmospheric Sciences, National Taiwan University, Taipei City 10617, Taiwan
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Institute of Environmental Health, National Taiwan University, Taipei City 100025, Taiwan
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Department of Environmental and Occupational Health, National Cheng Kung University, Tainan City 70101, Taiwan
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National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli County 35053, Taiwan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(23), 8883; https://doi.org/10.3390/ijerph17238883
Received: 3 October 2020 / Revised: 25 November 2020 / Accepted: 27 November 2020 / Published: 29 November 2020
(This article belongs to the Special Issue Spatial Modeling of Air Pollutant Variability)
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM10 variations and 46%, 47%, and 48% of NO2 variations, respectively. The GTWR model performed better (R2 = 0.51 for PM10 and 0.48 for NO2) than the other two models (R2 = 0.49–0.50 for PM10 and 0.46–0.47 for NO2), LUR and GWR. In the PM10 model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO2 variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM10 and NO2, was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM10 and NO2 concentration variations within areas across Asia. View Full-Text
Keywords: geographic and temporal weighted regression (GTWR); geographically weighted regression (GWR); land-use regression (LUR); nitrogen dioxide (NO2); particulate matter (PM10) geographic and temporal weighted regression (GTWR); geographically weighted regression (GWR); land-use regression (LUR); nitrogen dioxide (NO2); particulate matter (PM10)
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MDPI and ACS Style

Widya, L.K.; Hsu, C.-Y.; Lee, H.-Y.; Jaelani, L.M.; Lung, S.-C.C.; Su, H.-J.; Wu, C.-D. Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia. Int. J. Environ. Res. Public Health 2020, 17, 8883. https://doi.org/10.3390/ijerph17238883

AMA Style

Widya LK, Hsu C-Y, Lee H-Y, Jaelani LM, Lung S-CC, Su H-J, Wu C-D. Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia. International Journal of Environmental Research and Public Health. 2020; 17(23):8883. https://doi.org/10.3390/ijerph17238883

Chicago/Turabian Style

Widya, Liadira Kusuma, Chin-Yu Hsu, Hsiao-Yun Lee, Lalu Muhamad Jaelani, Shih-Chun Candice Lung, Huey-Jen Su, and Chih-Da Wu. 2020. "Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia" International Journal of Environmental Research and Public Health 17, no. 23: 8883. https://doi.org/10.3390/ijerph17238883

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