The comparison between in-situ monitored data and modelled results of nitrogen dioxide (NO2): case-study, road networks of Kigali city, Rwanda

Irankunda, Elisephane; Török, Zoltán; Mereuță, Alexandru; Gasore, Jimmy; Kalisa, Egide; Akimpaye, Beatha; Habineza, Theobald; Shyaka, Olivier; Munyampundu, Gaston; Ozunu, Alexandru

doi:10.1016/j.heliyon.2022.e12390

Cited by 7 publications

(1 citation statement)

References 48 publications

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“…However, the Kanombe station provided nearly complete and continuous records. Therefore, it was selected as the reference rain gauge to fill in the missing data from other rainfall gauges in the study area for the period from 1982 to 2016 (Irankunda et al, 2022).…”

Section: Data Collectionmentioning

confidence: 99%

SWAT model calibration for hydrological modeling using concurrent methods, a case of the Nile Nyabarongo River basin in Rwanda

Gasirabo,

Xi,

Kurban

et al. 2023

Front. Water

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The Nile Nyabarongo, which is Rwanda's largest river, is facing stress from both human activities and climate change. These factors have a substantial contribution to the water processes, making it difficult to effectively manage water resources. To address this issue, it is important to find out the most accurate techniques for simulating hydrological processes. This study aimed to calibrate the SWAT model employing various algorithms such as GLUE, ParaSol, and SUFI-2 for the simulation of hydrology in the basin of the Nile Nyabarongo River. Different data sources, such as DEM, Landsat images, soil data, and daily meteorological data, were utilized to input information into the SWAT modeling process. To divide the basin area effectively, 25 sub-basins were created, with due consideration of soil characteristics and the diverse land cover. The outcomes point out that SUFI-2 outperformed the other algorithms for SWAT calibration, requiring fewer computing model runs and producing the best results. ParaSol established residing the least effective algorithm. After calibration with SUFI-2, the most sensitive parameters for modeling were revealed to be (1) the Effective Channel Hydraulic Conductivity (CH K2) measuring how well water can flow through a channel, with higher values indicating better conductivity, (2) Manning's n value (CH N2) representing the roughness or resistance to flow within the channel, with smaller values suggesting a smoother channel, (3) Surface Runoff Lag Time (SURLAG) quantifying the delay between rainfall and the occurrence of surface runoff, with shorter values indicating faster runoff response, (4) the Universal Soil-Loss Equation (USLE P) estimating the amount of soil loss. The average evapotranspiration within the basin was calculated to be 559.5 mma-1. These calibration results are important for decision-making and updating policies related to water balance management in the basin.

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Section: Data Collectionmentioning

confidence: 99%

SWAT model calibration for hydrological modeling using concurrent methods, a case of the Nile Nyabarongo River basin in Rwanda

Gasirabo,

Xi,

Kurban

et al. 2023

Front. Water

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Assessment of seasonal variations in vehicular emissions at traffic intersections in Ibadan using AERMOD dispersion model

Odediran,

Adeniran,

Yusuf

2024

Environmental Quality Mgmt

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African cities grapple with urban air pollution from traffic‐related air pollutants (TRAPs). This study investigated TRAPs concentration variations at traffic intersections (TIs) in Ibadan, Nigeria. AERMOD model was employed to examine TRAPs dispersion at 25 selected TIs, considered as volume sources. Seasonal concentration distributions of six pollutants (CO, NO2, SO2, TVOCs, PM2.5, and PM10) were determined using meteorological, topographical, and pollutants’ emission rates in AERMOD. Estimated peak concentrations of the studied pollutants were generally higher in the rainy season than dry season, surpassing the air quality standards set by World Health Organization (WHO) and Nigeria's National Environmental Standards and Regulations Enforcement Agency (NESREA) during the rainy and dry seasons except SO2 (24 h) concentration which did not exceed the NESREA standard. This study highlighted TIs as significant contributors to air quality degradation in both seasons studied in Ibadan and showed AERMOD's suitability for air dispersion studies.

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Assessment of Urban air pollution by PM10 and NO2 and associated impacts and risks through computational analysis in Kigali, Rwanda

Irankunda,

Ozunu

2024

Energ. Ecol. Environ.

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The comparison between in-situ monitored data and modelled results of nitrogen dioxide (NO2): case-study, road networks of Kigali city, Rwanda

Cited by 7 publications

References 48 publications

SWAT model calibration for hydrological modeling using concurrent methods, a case of the Nile Nyabarongo River basin in Rwanda

SWAT model calibration for hydrological modeling using concurrent methods, a case of the Nile Nyabarongo River basin in Rwanda

Assessment of seasonal variations in vehicular emissions at traffic intersections in Ibadan using AERMOD dispersion model

Assessment of Urban air pollution by PM10 and NO2 and associated impacts and risks through computational analysis in Kigali, Rwanda

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