Ibe, Francis Chizoruo2026-03-172026-03-172016-12Ibe, F. C. (2016). Spatio-temporal characterization and dynamic modelling of ambient air quality in Imo State [Unpublished Doctoral Thesis]. Federal Universitry of Technology, Owerrihttps://repository.futo.edu.ng/handle/20.500.14562/2409This work was submitted for the award of the Doctor of Philosophy (PhD) in Environmental ChemistrySpatio-temporal characterization and dynamic modelling of ambient air quality were carried out in Imo State, Nigeria. The study was aimedat evaluating the ambient air quality of Imo State and to present a dynamic model for prediction of atmospheric dispersion and concentration in the study area. Six atmospheric pollutants includingPM10, NO2, SO2, VOC, H2S and CO were measured using Haze Dust Particulate Monitor (10µm), Gasman Air Monitors, Aeroqual Series 300 and Ibrid MX6. The meteorological parameters, wind speed, ambient temperature, air flow, wave height, and wind direction, were measured with Multifunctional Microprocessor DigitalAnemometer, while difference in temperature of wet and dry bulb hygrometer was used to locate the relative humidity from a psychrometric chart and elevation was with GPS map 76.Air quality monitoring was conducted in wet and dry seasons, three times a day (morning, Afternoon and evening) in 4 locations with a total of 16 air sampling sites within the months of November, 2014 to June, 2015. The result showed that the mean concentration of the air pollutants in dry season ranged as follows: PM10 (5.70 – 8.38) mg/m3 , NO2 (0.37- 0.53) ppm, SO2 (0.29- 0.61) ppm, VOC (0.47 - 1.14)mg/m3 , H2S (0.01 – 0.05) ppm and CO (0.29– 49.52) ppm, while in wet season the values were in the range; PM10 (4.91– 7.34) mg/m3 , NO2 (0.43- 0.59) ppm, SO2 (0.43- 0.60) ppm, VOC (0.25- 1.06) mg/m3 , H2S (0.00 – 0.01) ppm and CO (26.42 – 41.77) ppm.Spatial variation of the air pollutants was observed in the study area as revealed by the GIS analysis which was illustrated with spatial variation maps, contour and 3-D surface plots.The Box and Whisker plots showed the characterization and distribution of the data in terms of lower quartile, upper quartile, median, minimum and maximum values. It indicates elevated level of CO, PM10 and SO2 in the afternoon and evening, higher concentration of VOC and H2S in the morning and NO2 showing significant values in the morning and afternoon. The Dynamic models in most locations showed high R2 indicating significant influence of the meteorological factors and previous day concentration (PDC) of the pollutants. The time series models showed that the concentration of the pollutants fluctuated within the period of study. The windrose models revealed the dominant wind speed, direction of dispersion and transportation of the air pollutants. One-way ANOVA (p <0.05) revealed that the difference in mean values of the air pollutants were not statistically significantin some locations due to the influence of season, meteorological factors, location and time of measurement, while that of the meteorological variables were significant in some locations . High correlation was observed between NO2 and SO2, wind speed and air flow, while weak correlation was recorded between PM10 and SO2, VOC and CO, temperature and relative humidity. Hierarchical Cluster Analysis (HCA) grouped both the air pollutants into two major cluster and meteorological parameters into two clusters. The Principal Component Analysis (PCA) revealed two coherent components existing among the air pollutants and between the meteorological variables. The multivariate plots indicate that the meteorological parameters have great influence on the air pollutants.The mean concentration of the air pollutants obtained exceeded the Nigerian National Ambient Air Quality Standards (Nigerian NAAQS) and United States of America NAAAQS while NO2 and SO2 are within the permissible limit in some of the monitoring stations. Air Quality Index (AQI)analysis is within 51 – 300 (moderate – very unhealthy). In conclusion, the study has established the spatial and temporal attributes of the measured ambient air pollutants, the dynamics of atmospheric dispersion and prediction of air pollution events in the study area. The observed AQI within the study area is of great concern and therefore requires serious attention by environmentalists, researchers, regulatory bodies, and of course the government at the various levels.enAmbient air qualityair quality indexdynamic modellingpollution emissionspatio-temporal.Department of ChemistryDoctoral Thesis