Issue |
E3S Web Conf.
Volume 258, 2021
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2021)
|
|
---|---|---|
Article Number | 01008 | |
Number of page(s) | 8 | |
Section | IT in Environmental Science | |
DOI | https://doi.org/10.1051/e3sconf/202125801008 | |
Published online | 20 May 2021 |
Econometric modeling for energy losses and GHG emissions scenario: a governance case for toll digitalization
1 Moscow State Institute of International Relations (University) of the Ministry of Foreign Affairs of the Russian Federation, Moscow, Russia
2 National Institute of Maritime Affairs, Bahria University, Sector E-8, 44000 Islamabad, Pakistan
3 Peter the Great St. Petersburg Polytechnic University, Graduate School of Service and Trade, 195251, St. Petersburg, Russia
* Corresponding author: kanwar.javediqbal@gmail.com
There are growing climatic concerns of global warming due to increase of GHG emissions in the Earth’s atmosphere. There is a dire need of energy conservation and GHG emissions reduction by minimizing energy losses and bringing efficiencies in all processes including the transportation sector which has a major share. The business as usual case of energy losses and emissions from road transport with manual toll system has significant impacts not only on the atmosphere but also on non-renewables’ reserves and balance of payments of a country. It is a major challenge for energy sector governance and climate mitigation strategies worldwide. Thus, this paper aimed at developing econometric modeling for the assessment of various aspects and different scenarios of energy losses, emissions, BOPs and economic growth. The proposed modeling is based on multivariate Seemingly Unrelated Regression (SUR) model and can be used for informed decision-making process effectively. It will help in rationalizing the case for toll digitalization in order to accrue multiple benefits in terms of maintaining BOPs and environmental security with reduced emissions and energy losses.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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