GIS and MATLAB modeling of criteria pollutants: a study of lower onitsha basin during rains​

Anyika, L. C.; Alisa, C. O.; Nkwoada, Amarachi; Opara, Alexander Iheanyichukwu; Ejike, E. N.; Onuoha, G.N.

doi:10.18801/jstei.060118.47

Cited by 2 publications

(6 citation statements)

References 17 publications

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“…The temporal distribution of NO 2 pollutant is also presented in Fig.2 of WHO annual mean concentration levels where compared to our current data onto Harmattan and previous studies during rains, it depicts that all the sampled area exceeded this value and are therefore heavily polluted by NO 2 on annual bases [6,11,20]. A significant contributor of NO 2 in this study is the frequent movements of heavy duty diesel trucks along the studied area especially at upper Iweka via vehicles exhaust [24].…”

Section: Air Quality Index Evaluationsupporting

confidence: 62%

“…Hence, this similarly confirmed point 1 sampling points to have the lowest PM 10 distribution or least PM 10 polluted sampling spots. Moreover, point 3 showed the highest PM 10 distribution or most polluted sampled spots [6,11].…”

Section: Air Quality Index Evaluationmentioning

confidence: 96%

“…The nine locations were Upper Iweka/Nitel, Mission road/Waterside, Uzodinma street, Port Harcourt road/Niger street, Rest house/GRA, Borromeo hospital, Feggie/Nupe Square, Christ the King College (CKC) and Awada/Oraifite street/ABS-Channel. The detailed description of studied areas with geo-referenced coordinates and maps are also shown in our previous paper by Anyika et al [6], but also represented differently in the digitized map in Fig. 1.…”

Section: Site Descriptionmentioning

confidence: 98%

“…Finally, after determining the value of IAQI p , the AQI value is derived by choosing the max IAQI p as shown below. More detailed explanation was given in our previous paper [6,19], and studies on Beijing's seasonal variant of atmospheric pollution and air quality [12,19]. Additionally, Table 1 is showing concentration limits for air quality index calculation with high and low values.…”

Section: Air Quality Index Evaluationmentioning

confidence: 99%

“…Most awful is the official monitoring of air pollution is rare and global health authorities have particularly singled-out Onitsha's air as predominantly toxic rivaling some polluted cities in China and India [3][4][5]. Subsequently, the reported impact on fossil fuelled combustion, vehicular exhausts, open burning and industrial emissions varies greatly due to seasonal variations especially in Onitsha basins [6]. Hence, the Harmattan and rainy seasons in Nigeria are key dynamics that influence air pollutants distribution and variation in Onitsha, especially the lower basin.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Study of Criteria Pollutants in Nigerian City

Anyika

Alisa

Nkwoada

et al. 2020

AJACR

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Aims: An investigation of characteristic long term air pollutants known for temporal and spatial behaviors was conducted due to increased pollution scenarios in Nigerian cities as a result of deprived environmental enforcement of statutory obligations. Study Design: One of the worlds’ most polluted cities (Onitsha lower basin) in Nigeria was selected for spatio-temporal study of three criteria pollutants combined with GIS and MATLAB alongside associated meteorological conditions during harmattan. Methodology: 72-hourly analyses of the nine different locations having 4 sampling sites and 500 meters apart were done from December to February which generated over 19, 440 experimental data per quarter of each annual study. Results: Upper Iweka/Nitel area recorded the highest concentration of SO2 pollutant at (94.2 µg/m3) due to longer residence times and low wind mixing height. Borromeo hospital showed the least active NO2 region but converges at points 1 due to North-east wind dissimilar to sampling points 1 having the lowest PM10 distribution. Measured temperature parameter correlates inversely with relative humidity and precipitation. The GIS spatial representation corresponded to temporal variability of gaseous and particulate pollutants. Conclusion: All sampled areas had AQI above 50; hence the study identified SO2, NO2, and PM10 as Primary pollutants of Onitsha lower basin.

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Section: Air Quality Index Evaluationsupporting

confidence: 62%

Section: Air Quality Index Evaluationmentioning

confidence: 96%

Section: Site Descriptionmentioning

confidence: 98%