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The incomplete combustion of fossil fuels from petrol, natural gas, and fuel oil in the engine of vehicles contributes to air quality degradation through traffic-related air pollutant emissions. The Real-time affordable multi-pollutant (RAMPs) monitors were installed in Kigali, the capital of Rwanda, to fill the gap in air quality datasets. Using RAMPs, this is the first air quality modelling research in Rwanda aiming to report the concentration of NO2 by comparing In-situ monitored data and modelled results. We targeted NO2 emissions from 27 road networks of Kigali to address the impacts of traffic emissions on air quality over 2021. The American Meteorological Society and Environmental Protection Agency regulatory models (AERMOD and ISCST3) were used for simulation. Statistical indexes include fractional bias (FB), the fraction of the prediction within the factor of two of the observations (FAC2), normalized mean square error (NMSE), geometric mean bias (MG), and geometric variance (VG) used to assess models' reliability. Monitoring shows the annual mean of 16.07 μg/m3, 20.35 μg/m3, and 15.46 μg/m3 at Mont-Kigali, Gacuriro, and Gikondo-Mburabuturo stations, respectively. Modelling shows the daily mean of 111.77 μg/m3 and annually mean of 50.42 μg/m3 with AERMOD and daily mean of 200.26 μg/m3 and annually mean of 72.26 μg/m3 with ISCST3. The FB, NMSE, and FAC2 showed good agreement, while MG and VG showed moderate agreement with AERMOD. The FB, NMSE, and MG showed moderate agreement, while FAC2 and VG disagreed with ISCST3. Traffic and urban residential emissions were identified as potential sources of NO2. Results indicated that Kigali residents are exposed to a significant level of NO2 exceeding World Health Organisation limits. Findings will help track the effectiveness of Rwanda’s recently executed pollution-control policy, suggest evidence based on the recommendations to reduce NO2, and use further dispersion models to support ground-based observations to improve public health.

Noise pollution poses a serious threat to public health and continues to grow in extent, frequency, and severity due to the rapid population growth and urbanization, and this is of particular concern in developing countries such as Rwanda. However, data on noise pollution levels, noise laws and regulations are, however, lacking in Rwanda. We assessed the effect of land-use type during a two-month period at nine sites: three commercial sites, three passenger-car parking sites, two road junction sites, and one reference site (Car-Free Zone) in Rwanda. We collected data on noise pollution during weekdays (Monday, Wednesday, and Friday) and Weekends (Saturday and Sunday) in the morning (7h00–10h00), around noon (11h00–14h00), and in the evening (15h00–18h00). The mean noise levels were higher during weekdays (60–80) A-weighted decibels (dB) (A)) than during weekends (50–70 dB (A)). We recorded the lowest noise level at Kigali car-free zone in the morning (34.4 dB (A)) and the highest noise level at Nyabugogo passenger-car parks in the evening (111.2dB (A)). Spatial variation of noise levels interpolated for Kigali City shows higher noise levels (hotspot) in the outskirts of Kigali, Remera and Kimironko. Noise levels recorded in Kigali exceeded the World Health Organization permissible daytime limits during both weekdays and weekends at all land-use types except the car-free zone site. Our results indicate that Kigali residents are exposed to high levels of noise, and urgent development of noise pollution monitoring programs and control measures in Rwanda is required.

Industrial and mining operations are classified as the primary sources of particulate matter (PM10) that pose substantial health and environmental risks, with much attention when situated in or near residential areas. The absence of a standardized approach for quantifying air pollutant fluxes in mining areas has been identified as a research gap, particularly given the increasing rate of mining extraction, especially in developing countries. This study used the AERMOD air pollutants dispersion model to analyze PM10 dispersion from the CIMERWA Cement Plant and adjacent mining sites in Rusizi District, Rwanda, throughout 2022. We developed methods to quantify PM10 horizontal and vertical fluxes and their emission rates within the framework of dispersion analysis. Results indicate high concentrations of PM10 in the vicinity of mining areas, with daily, hourly, monthly, and annual maximum mean ground-level concentrations of 158.86 µg m−3, 92.87 µg m−3, 46.15 µg m−3, and 27.65 µg m−3, respectively. Wind erosion, with a daily horizontal speed of 0.66 m s−1 and shear speed of 0.03 m s−1, contributes to a daily mean horizontal flux of 8.50 µg m−2 s−1 and vertical flux of 0.4 µg m−2 s−1 of PM10. Dispersion maps analysis highlights residents' exposure to significant levels of PM10 depicted with 28 discrete receptors in all directions. The circulation of polluted windy air masses substantially impacts regional air quality. The findings offer evidence-based recommendations for strategic mitigation measures targeted at residents, policymakers, stakeholders, and urban planners to address air quality issues arising from industrial mining activities. [ABSTRACT FROM AUTHOR]

Historically, Romania is known as a mining site of mineral substances, including gold, silver, copper, lead, zin, uranium, manganese, salt, and coal, whereby their long periods of exploitation and extraction affected human health and the environment in various ways. In Moldova Nouă southwest region of Romania, we investigated the environmental impacts of mining activities on air quality over 2021. We quantified PM10 emission rates through in situ monitoring, dispersion modelling, and horizontal and vertical fluxes. Statistical metrics, including the fraction within factor 2 (FAC2), mean bias (MB), mean gross error (MGE), normalized mean bias (NMB), normalized mean gross error (NMGE), coefficient of efficiency (COE), index of agreements (IOAs), and Taylor diagram signifying standards deviation (SD), root mean squared error (RMSE), and correlation coefficient (R), were used to evaluate the reliability of modelling results against observation. Results conclude that PM10 dispersion agrees with MB, MGE, NMB, NMGE, COE, IOA, and Taylor diagram and moderately with FAC2 metrics. PM10 hotspot was investigated in the vicinity of the tailings ponds of 115.5 µg m−3 annual mean, 563.7 µg m−3 daily mean, 63.3 µg m−2 s−1 annual horizontal flux, and 3.0 µg m−2 s−1 annual vertical flux. PM10 dispersion was identified to expand to Moldova Nouă City and nearby country Serbia. Findings concluded that a windy air mass accumulation across the overburdened dumps and ponds causes the increase of PM10 in the air, resulting in the region's pollution. Therefore, results recommend adopting a strategic mitigation measure for residents, policymakers, stakeholders, and urban planners. [ABSTRACT FROM AUTHOR]

Historically, Romania is known as a mining site of mineral substances, including gold, silver, copper, lead, zin, uranium, manganese, salt, and coal, whereby their long periods of exploitation and extraction affected human health and the environment in various ways. In Moldova Nouă southwest region of Romania, we investigated the environmental impacts of mining activities on air quality over 2021. We quantified PM 10 emission rates through in situ monitoring, dispersion modelling, and horizontal and vertical fluxes. Statistical metrics, including the fraction within factor 2 (FAC2), mean bias (MB), mean gross error (MGE), normalized mean bias (NMB), normalized mean gross error (NMGE), coefficient of efficiency (COE), index of agreements (IOAs), and Taylor diagram signifying standards deviation (SD), root mean squared error (RMSE), and correlation coefficient (R), were used to evaluate the reliability of modelling results against observation. Results conclude that PM 10 dispersion agrees with MB, MGE, NMB, NMGE, COE, IOA, and Taylor diagram and moderately with FAC2 metrics. PM 10 hotspot was investigated in the vicinity of the tailings ponds of 115.5 µg m -3 annual mean, 563.7 µg m -3 daily mean, 63.3 µg m -2  s -1 annual horizontal flux, and 3.0 µg m -2  s -1 annual vertical flux. PM 10 dispersion was identified to expand to Moldova Nouă City and nearby country Serbia. Findings concluded that a windy air mass accumulation across the overburdened dumps and ponds causes the increase of PM 10 in the air, resulting in the region's pollution. Therefore, results recommend adopting a strategic mitigation measure for residents, policymakers, stakeholders, and urban planners., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)