Background. Air pollution has become a major problem around the world and is increasingly an issue in Togo due to increased vehicular traffic. Gaseous pollutants are released by engines and are very harmful to human health and the environment. The fuels used on the major road in Togo, the N2, are adulterated with unknown contents and are of poor quality. Many of the vehicles come from neighboring countries, such as Benin, Ghana and Nigeria. Objectives. The present study aims to evaluate the pollution rate in Togo through the estimation of the concentrations of sulfur dioxide (SO2), nitrogen oxides (NOx), and particular matter (PM) on the international road, the National Road N2, in Lomé, compared to the World Health Organization's (WHO) standard limit. Methods. The simulations of pollutant concentration were performed using the Industrial Source Complex Short Term Version 3 model, which is included in the United States Environmental Protection Agency Regulatory Model (USEPA) AERMOD View software. The meteorological averages data were obtained from the local station near the National Road N2 in Togo in 2018. Hourly averages were calculated according to the European Monitoring Evaluation Programme/European Environmental Agency air pollutant emission inventory guidebook 2016 and were processed using AERMET View and a terrain pre-processor, AERMAP. For the model, the sources of pollution were the vehicles traveling on the road segment. The source was a line volume with 20 m of width and 2 m of height. The estimation methodology covered exhaust emissions of NOx, SO2 and PM contained in the fuel. Results. The simulations provided average hourly, daily and annual concentrations of the different pollutants: 71.91 μg/m3, 42.41 μg/m3,11.23 μg/m3 for SO2; 16.78 μg/m3, 9.89 μg/m3, 2.46 μg/m3 for NOx and below the detection limit, 0.62 μg/m3, 0.15 μg/m3 for PM, respectively. These results indicate that on the National Road N2 in Togo, the concentrations of SO2 were high compared to those of NOx and PM. The daily average concentration of SO2 was twice the permissible limits set by the WHO. Conclusions. Emissions obtained from the AERMOD for NOx and PM were less than the permissible limits set by the WHO, while the rate of SO2 was twice the permissible limit. The fuels used on this road were very rich in sulfur. The sulfur level in fuels must be monitored by stakeholders in Togo. Competing Interests. The authors declare no competing financial interests.

Abstract:We investigate the law of exhaust gases in order to control the pollution that is increasingly present in our daily lives. Pollution is a degradation of the environment by non-natural materials in several environments constituting our universe. Thus, it intervenes as well in water, in the air as in the soil. It is mostly due to human activities, especially in urban areas and industrial areas, and the massive use of automobiles based on gasoline engines. The results show that this pollution is due in part to the existence of the mass and thermal discontinuity characterized by shock waves which occur during the evaporation process, precursor of the incomplete combustion in the combustion chamber of the engines [1,2]. By analytical approach, we establish in this paper the law ϕ of the exhaust gases in poor and rich reaction media during combustion in the combustion chambers of gasoline engines in order to propose the ranges of adequate proportions of additive elements to the petrol. These engines, when operating, release various gaseous pollutants such as: carbon dioxide, oxides of carbon and nitrogen, unburnt hydrocarbons, which undoubtedly contribute to the nuisance and pollution of our environment.

We study in this paper, based on comparison already made in the literature concerning photovoltaic generator power models, the most optimal model applied to the operation of the photovoltaic generator of Sévagan (Togo). The comparison with the experimental data is carried out, which allowed us to verify the validity of the model. Finally, the influence of the characteristic parameters on the photovoltaic module ECO LINE LX-260P used to make the photovoltaic generator of the Sévagan dispensary (in Togo) is studied in order to predict the power production of the module according to the meteorological conditions(temperature-Irradiation). The comparison with the experimental data will be carried out in order to verify the validity of the model. To verify the validity of the model throughout the range of weather conditions, the process was done in two steps: on a sunny day and a cloudy day. A good agreement was observed with 95%, 97% and 99% correlation coefficients for cloudy, sunny days and the generator photocurrent simulation respectively. The results demonstrate an acceptable accuracy of the power model under different environmental conditions.

This paper presents a new neural network approach for the generation of synthetic monthly radiation data for nine localities in Togo. The neural model employed is the well-known Multi-Layer Perceptron (MLP) paradigm, in feedback architecture, using a record of historical values for the supervised network training. The method is based on the MLP ability to extract, from a sufficiently general training set, the existing relationships between variables whose interdependence is unknown a priori. Simulation results are compared to the measured values for the three towns where solar irradiation is measured in Togo. The results show that the generated values are of the real values. The method has been developed using data values from Lomé, Atakpamé and Mango, and is generalized to generate data of any location for the establishment of solar maps. Indeed, the proposed methodology is of general applicability to the estimation of highly complex temporal series.

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