Evaluation of Pollutants Along the National Road N2 in Togo using the AERMOD Dispersion Model

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

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.

A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two Years

Air pollution is a leading cause of global premature mortality and is especially prevalent in many low- and middle-income countries (LMICs). In sub-Saharan Africa, preliminary monitoring networks, satellite retrievals of air-quality-relevant species, and air quality models show ambient fine particulate matter (PM_2.5) concentrations that far exceed the World Health Organization guidelines, yet many areas remain largely unmonitored and understudied. Deploying a network of five low-cost PurpleAir PM_2.5 monitors over 2 years (2019-2021), we present the first multiyear ambient air pollution monitoring data results from Lomé, Togo, a major West African coastal city with a population of about 1.4 million people. The full-study time period network-wide mean measured daily PM_2.5 concentration is 23.5 μg m^-3 m^-3. The strong regional influence of the dry and dusty Harmattan wind increases the local average PM_2.5 concentration by up to 58% during December through February, but the diurnal and weekly trends in PM_2.5 are largely controlled by local influences. At all sites, more than 87% of measured days exceeded the new WHO Daily PM_2.5 guidelines; these first measurements highlight the need for air quality improvement in a rapidly growing urban metropolis.

Estimation of economic costs of air pollution caused by motor vehicles in Iran (Isfahan)

Since mobile sources are one of the most important sources of air pollution, this paper tries to estimate the health effects and economic burden due to fine particulate matter (PM_2.5) concentrations from motor vehicles. In this regard, we calculate the economic costs of air pollution emitted by vehicles in Isfahan over the period from March 2018 to March 2020. The concentration of urban traffic pollution based on the generalized additive model (GAM) as well as spatial distribution of pollution is estimated. Health effects are evaluated using AirQ⁺ updated by the WHO European Centre for Environment and Health. Economic burden of mortality attributable air pollution from traffic is calculated using value of a statistical life (VOSL), and the value of life years (VOLY) approach. The results indicated that the number of deaths attributable to PM_2.5 from motor vehicles in these two consecutive years was 136 (95%CI: 89-179), and 147 cases (95%CI: 96-194), respectively. The number of years of life lost due to premature death from air pollution was 2079 years annually. The economic costs imposed under VOSL approach were on average USD 51.7 (95%CI: 43-75) million per year, and according to VOLY approach USD 11.5 (95%CI: 9-13) million per year. These results help to analyze the cost-benefit and prioritize control measures to reduce air pollution. In addition, combination of these results with other externality cost of road traffic can take account for urban transportation planning.