GIS-based geostatistical approaches study on spatial-temporal distribution of ozone and its sources in hot, arid climates

• Published in: Air quality, atmosphere and health Vol. 17; no. 6; pp. 1163 - 1182
• Main Authors: Yassin, Mohamed F., Al-Jazzaf, Ameenah M., Shalash, Musaed
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2024; Springer Nature B.V
• Subjects: Air monitoring; Air pollution; Arid climates; Aridity; Atmospheric aerosols; Atmospheric Protection/Air Quality Control/Air Pollution; Autumn; Condition monitoring; Data analysis; Deserts; Earth and Environmental Science; Environment; Environmental Health; Environmental impact; Environmental monitoring; Geographic information systems; Geographical distribution; Geostatistics; Hazardous air pollutants; Health Promotion and Disease Prevention; Health risks; Interpolation; Meteorological conditions; Meteorological data; Meteorological parameters; Meteorology; Nitrogen dioxide; Ozone; Pollutants; Pollution sources; Remote sensing; Risk assessment; Seasonal variability; Seasonal variations; Seasons; Spatial analysis; Spatial distribution; Spatial variability; Spatiotemporal data; Spring; Spring (season); Summer; Temporal distribution; Threat evaluation; Urban environments; Winter; Kuwait; GIS; Ozone; Air pollutants; IDW; Kriging; Meteorological conditions
• ISSN: 1873-9318; 1873-9326
• DOI: 10.1007/s11869-021-01038-2

Ambient ozone (O 3 ) is a critical atmospheric pollutant with significant potential threats to human health and the environment. Geographic information systems (GIS) techniques have opened up a wide range of methods for the assessment of health risks associated with pollutant exposure in urban environments. Accordingly, this study aimed to identify the sources and spatial-temporal distribution of O 3 in regions under hot, arid climates. GIS-based geostatistical interpolation approaches were applied to analyze and locate the sources and spatial-temporal distribution of O 3 in the state of Kuwait, which was taken as a case study. The spatial distribution of O 3 in Kuwait was mapped using GIS functions. Hourly observation data for O 3 concentration along with air pollutants and meteorological condition data for five years were collected from four air-monitoring stations representing open, residential, industrial, and commercial areas. To evaluate the accuracy of several spatial interpolation approaches, O 3 concentration was estimated using the inverse distance weighted (IDW) and kriging approaches. Both attribute and geographic data were analyzed and mapped along with meteorological data to investigate the sources and the spatial-temporal distribution of O 3 . The results showed the O 3 and NO 2 concentrations during the four seasons were less than that in the regional and international limits. Seasonal spatial variability showed that the opposite trend of variations between O 3 and NO 2 recorded high concentrations in the summer and spring seasons for O 3 , while it was in the winter and autumn seasons for NO 2 . A high correlation was found between O 3 pollutants and meteorological parameters. The highest O 3 concentration was recorded in the summer season, followed by spring. The minimum O 3 concentration was during the winter season. The concentrations of NO during the summer and spring seasons were lower than during the winter and autumn seasons. The strongest correlation was found between O 3 and NO 2 during the summer and autumn in the four regions.