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DECARBONIZING CAMPUS MOBILITY: A COMPUTATIONAL INTELLIGENCE FRAMEWORK FOR EMISSION-AWARE URBAN TRANSPORT PLANNING


Article Information

Title: DECARBONIZING CAMPUS MOBILITY: A COMPUTATIONAL INTELLIGENCE FRAMEWORK FOR EMISSION-AWARE URBAN TRANSPORT PLANNING

Authors: Khurram Iqbal, Perfshan Erum, Shujaat Ali, Khalid Bin Muhammad, Khalid Mahboob, Sarwat Ishaque, Hamza Birjees

Journal: Kashf Journal of Multidisciplinary Research (KJMR)

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31

Publisher: Kashf Institute of Development & Studies

Country: Pakistan

Year: 2025

Volume: 2

Issue: 5

Language: en

DOI: 10.71146/kjmr434

Keywords: CO2 Emissions Environmental Performance Data Analysis

Categories

Abstract

Currently, the majority of the cities throughout the world have been burdened with gases that are formed by automobiles. The rapid and continuous growth in industrialization and urbanization has caused much damage to the environment. The foremost source of environmental pollution in the city is mainly due to the industrial waste and traffic congestion. Carbon dioxide (CO2) emission is considered one of the major causes of global warming. In this article, a case study of the Institute of Business Management (IoBM) is presented. Data was gathered from 25th April 2017 to 20th March 2021 to gain information about all the types of cars parked inside the campus. This research purpose is to understand the models and interpret the CO2 emission rate of all the models of different companies. Lastly, this case study is an effort to suggest and recommend the major steps in controlling CO2 emissions that have been observed through the data.


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