Article: Evaluating the environmental impact of biofuel vehicular emissions in developing countries Journal: International Journal of Global Warming (IJGW) 2024 Vol.34 No.1 pp.62 - 84 Abstract: This study assesses gaseous pollutant emissions from two-wheeler and four-wheeler vehicles using various fuels, focusing on carbon monoxide (CO), carbon dioxide (CO2), and hydrocarbons (HC). Statistical data on emissions are analysed to understand the potential impact of future vehicle growth rates on air quality. Using a top-down approach, emissions of pollutants such as CO, nitrogen oxide (NOX), and sulphur dioxide (SO2) are estimated for the years 2021-2022. The study also considers factors like composition, engine performance, and emission temperature. A deep neural network with fuzzy wavelets (DNN-FW) approach is employed to predict carbon emissions and energy demand management from 2022-2050. MATLAB software is used for implementation. Results show estimated emissions of 0.05 for CO, 32.55 for HC and 16.34 for CO2 by 2050. The study's proposed approach achieves higher regression values (0.99 for SO2 emissions) compared to existing methods like SW-SVR, GB, and RF, indicating improved performance with lower error rates. Accurate input data ensures reliable predictions for future emissions. Inderscience Publishers - linking academia, business and industry through research

Title: Evaluating the environmental impact of biofuel vehicular emissions in developing countries

Authors: G. Balasubramanian; P. Balashanmugam; K. Kumaravel; S. Sivaprakasam

Addresses: Department of Mechanical Engineering, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India ' Department of Mechanical Engineering, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India ' Department of Mechanical Engineering, FEAT, Annamalai Nagar Annamalai University, Chidambaram, Tamil Nadu, India ' Department of Mechanical Engineering, FEAT, Annamalai University, Chidambaram, Tamil Nadu, India

Abstract: This study assesses gaseous pollutant emissions from two-wheeler and four-wheeler vehicles using various fuels, focusing on carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbons (HC). Statistical data on emissions are analysed to understand the potential impact of future vehicle growth rates on air quality. Using a top-down approach, emissions of pollutants such as CO, nitrogen oxide (NO_X), and sulphur dioxide (SO₂) are estimated for the years 2021-2022. The study also considers factors like composition, engine performance, and emission temperature. A deep neural network with fuzzy wavelets (DNN-FW) approach is employed to predict carbon emissions and energy demand management from 2022-2050. MATLAB software is used for implementation. Results show estimated emissions of 0.05 for CO, 32.55 for HC and 16.34 for CO₂ by 2050. The study's proposed approach achieves higher regression values (0.99 for SO₂ emissions) compared to existing methods like SW-SVR, GB, and RF, indicating improved performance with lower error rates. Accurate input data ensures reliable predictions for future emissions.

Keywords: biofuel; vehicular emissions; hydrocarbons; carbon monoxides; carbon dioxide; top-down approach; deep neural network; fuzzy wavelets; energy demand management; EDM.

DOI: 10.1504/IJGW.2024.141403

International Journal of Global Warming, 2024 Vol.34 No.1, pp.62 - 84

Received: 21 Dec 2023
Accepted: 08 Mar 2024
Published online: 11 Sep 2024 *

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Title: Evaluating the environmental impact of biofuel vehicular emissions in developing countries

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