Global NEST Journal

Air pollutant emissions and fuel consumption of vehicles equipped with internal combustion engines are highly susceptible to the conditions of engine operation. The purpose of this research was to investigate the correlation between the emissions of individual pollutants (carbon monoxide, hydrocarbons, nitrogen oxides, and carbon dioxide), the fuel consumption and various dynamic conditions of the operation of an engine. The empirical data was obtained by testing of passenger car with a spark-ignition engine on a chassis dynamometer in 12 various driving tests, both type-approval and special. The results indicate, that the strongest correlation exists between the emissions of carbon dioxide and hydrocarbons and between the fuel consumption and the emissions of hydrocarbons and carbon dioxide. The weakest correlation was found to be between the emissions of carbon monoxide and nitrogen oxides. The average value of vehicle velocity proved to be suitable zero-dimensional characteristic of the dynamic driving conditions. The correlation between the emission of hydrocarbons and the average vehicle velocity can be assessed as the strongest, while between the emission of nitrogen oxides and the average vehicle velocity – the weakest.

The problem of air pollution is one of the most important problems faced by the world in the context of large urban agglomerations. Numerous activities are being undertaken all over the world to both counteract existing pollution and prevent the emergence of another one. Manufacturing is one of the activities that have a significant negative impact on the natural environment. Starting from the production itself, through the life of vehicles, and ending with the problems of storage and recycling of used means of transport, at every stage there are negative effects on the environment. There is no doubt that in all types of pro-ecological activities, it may be extremely important to predict the future state based on various determinants occurring in the analysed or preceding period of time. To this end, various types of mathematical and statistical tools are being used. Recently, you can also notice interest in all types of methods aided by artificial intelligence. Such methods include artificial neural networks, fuzzy logic, or evolutionary algorithms. The article presents the problems of environmental pollution as a result of the development of motorization. The main components of exhaust gases from car engines are discussed, which are particularly harmful to the natural environment. Methods for reducing the emission of pollutants emitted from internal combustion engines are described, and the monitoring of hazards related to air pollution is discussed. The possibilities of using artificial neural networks as a tool for modelling the state of air pollution have also been discussed.

Two hydrological climate modelling techniques, general circulation model (GCM) and hypothetical climate change scenarios, were used to analyse the hydrological response to the anticipated climate change scenarios in the Subarnarekha river basin in Eastern India. Both models verified individually for the same river basin and a comparative performance of the models was evaluated to relate the two models for the near (2014-2040) period climate. The hydrological response under the anticipated climate change in the Subarnarekha river basin is well assessed by GCM under the RCP 8.5 scenarios compared to the RCPs 4.5. Results indicate GCM best suited over the hypothetical climate change scenarios as GCM has demonstrated their potential in accurately reproducing the past observed climatic changes. The strong performance of the hypothetical climate change scenarios model, particularly for warming climate scenarios, suggests that it may have distinct advantages for the analysis of water balance components in the river basin. The monthly streamflows of Subarnarekha river basin was simulated using a total of 14 years (2000-2013) daily observed streamflow data in the ArcSWAT model integrated with model calibration and uncertainty analysis by means of SUFI-2 algorithm. The results indicate during the calibration the coefficient of determination (R2) and Nash-Sutcliff Efficiency (NSE) were reported as 0.98 and 0.97, respectively, while during the validation the R2 and NSE were obtained as 0.94 and 0.94, respectively, confirms the hydrological model performance was very good both in calibration and validation. The obtained climate change water impact index (ICCWI) values reveal the Subarnarekha river basin is more responsive to climate change. The reduction in precipitation along with the significant warming under the projected future climate is likely to reduce availability of water substantially in the study region. This work would be useful for the effective management of water resources for sustainable agriculture and in mitigating natural hazards such as droughts and floods in the study region.

Hydrological modeling of a watershed is necessary for water resources planning and management. The hydrology of upper Ribb watershed has been analyzed using spatially semi-distributed Soil and water assessment tool (SWAT) model. This study aimed to determine the water balance components and its relation with the rainfall which reaches to the surface of the earth. Different spatio-temporal (land use, soil, digital elevation model, climate data, river discharge) data were used for hydrological modelling of Upper Ribb watershed. The applicability of SWAT model in Upper Ribb watershed has been evaluated using coefficient of determination (R2) and Nash Sutcliff efficiency (NSE) parameters. The calibration results revealed the observed data showed a very good agreement with the simulated data with the R2 and NSE values of 0.90 and 0.84 respectively. Similarly, the validation results of streamflow were acceptable with the R2 and NSE values of 0.80 and 0.82 respectively. The monthly average streamflow from Upper Ribb watershed were found 13.39 m3/s. The major portion of the rainfall contributes to the surface runoff due to the major percentage of the watershed is covered with agricultural lands. The groundwater flow was high in forested areas, while evapotranspiration was found very high in water bodies (Ribb reservoir). In this study area the rainfall showed a direct relationship with the streamflow. The ratio of streamflow and evapotranspiration with rainfall was 0.61 and 0.36 respectively. Due to the presence of high amount of surface runoff and evapotranspiration the deep recharge which contributes to the ground water is not that much significant.