Pakistan’s Transport Sector Modeling Using AIM/Enduse †
by
Waqas Nazir Awan
1,2,*,
Sidra Khan
3,
Muhammad Zulfiqar
4,
Ubaid Ur Rehman Zia
5 and
Peng Wang
1,2 1
School of Engineering, University of Science and Technology of China, Hefei 230026, China
2
Energy Strategy Research Center, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
3
Department of Computer Engineering, University of Engineering and Technology, Lahore 39161, Pakistan
4
Department of Mechanical Engineering, Capital University of Science and Technology, Islamabad 44000, Pakistan
5
Energy Unit, Sustainable Development Policy Institute, Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
†
Presented at the 4th International Conference on Advances in Mechanical Engineering (ICAME-24), Islamabad, Pakistan, 8 August 2024.
Eng. Proc. 2024, 75(1), 1; https://doi.org/10.3390/engproc2024075001
Published: 19 September 2024
(This article belongs to the Proceedings of 4th International Conference on Advances in Mechanical Engineering (ICAME-24))
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Figure 1
<p>Stock under both scenarios according to transport share.</p> "> Figure 2
<p>Outlook of energy under both scenarios according to fuels.</p> "> Figure 3
<p>Outlook of emissions under both scenarios according to vehicle type.</p> "> Figure 4
<p>Share of public and private transport.</p> ">
Versions Notes
<p>Stock under both scenarios according to transport share.</p> "> Figure 2
<p>Outlook of energy under both scenarios according to fuels.</p> "> Figure 3
<p>Outlook of emissions under both scenarios according to vehicle type.</p> "> Figure 4
<p>Share of public and private transport.</p> ">
Abstract
:Pakistan is actively exploring sustainable transportation solutions, considering environmental impact, and economic development. By adopting more sustainable modes of transport and investing in infrastructure, Pakistan can pave the way toward a greener and more efficient future. Leveraging the AIM/Enduse framework, we analyze the energy and environmental impact using Baseline (BL) and Counter Measure (CM) scenarios. Our findings indicate, with penetration of 30%, 50%, and 100% green vehicles into the existing transport system, Pakistan may save 5 MTOE, 11 MTOE, and 24.6 MTOE of energy in 2030, 2040, and 2050, respectively. Similarly, it will also reduce CO2 emissions by 22 MtCO2eq, 41 MtCO2eq, and 104 MtCO2eq in respective years.
1. Introduction
Pakistan’s transport sector has been neglected since the 1990s [1]. No such investment is nominated to plan this sector, which leads to a significant negative impact on Railways and Air transport. Most of the freight is shifted from railway to road. Similarly, trends show that many of airlines stop working; in 2020, Pakistan had only 30 operational aircrafts [2]. Most of these aircraft are currently used for passenger transport. This low investment leads to Pakistan having the worst transport for internationally in terms of energy and environment. Most fleets have low efficiency which consume large amounts of energy and emit more CO2. Pakistan is already facing energy crises and has been declared a vulnerable country in terms of climate [3]. This study particularly focuses on efficiency and new energy vehicles; efficiency in terms of progress in existing technology which may consume less energy and emit fewer emissions, and new energy vehicles meaning modern technology, i.e., technology transfers from existing internal combustion engines to electric motors or hydrogen engines. We assumed that the tail-end emission from new energy vehicles is zero or less.
In this regard, the Government of Pakistan approved the electric vehicles policy in 2019 [4]; according to this, around 30% of vehicles in 2030 will be electric vehicles. The penetration rate (as compared to developed countries) is very low in Pakistan [5]. Many factors affect the penetration of EVs, like motor technology, battery technology, and charging infrastructure. Unfortunately, Pakistan is dependent on imports of all components of EVs, which increases their cost and makes them unaffordable for ordinary users to adopt. Currently, the imported low-cost technology has low efficiency and battery capacity, leading to low penetration in the existing transport sector. This study focuses on how efficient vehicles affect energy and emissions. It is expected that higher efficiency vehicles consume less energy and emit less CO2.
2. Methodology
This study assessed energy and emissions of road, rail, air, and water transport in Pakistan. After the evidence-based assessment, this study proposed policy measures for energy and the environment.
2.1. Modeling Tool
AIM/Enduse [6] is a comprehensive technology selection framework used to evaluate country-level policies aimed at reducing greenhouse gas emissions and local air pollution. It also supports energy policy analysis. The model simulates the entire energy and material flow within an economy, from primary energy and material supply to end-use services, including conversion and supply of secondary energy and materials. By providing a detailed representation of various technologies, AIM/Enduse optimizes system costs by minimizing them under constraints such as meeting service demands, energy availability, and other relevant factors. Additionally, this recursive dynamic model can perform multi-year calculations and analyze different scenarios, including policy countermeasures, enabling a thorough evaluation of different policy options.
2.2. Model Scenarios
Two scenarios were developed using AIM/Enduse. The first is the baseline (BL) scenario, which works based on the historical trend of data. In the BL, the system moves as it is moving normally. The baseline is taken from 2020 and forecasted to 2050. The second scenario is a policy scenario called the Counter Measure (CM) scenario in which new energy vehicles are penetrated as shown in Table 1.
2.3. Scenario Assumptions
The following are the counter measure (CM) scenario assumptions for this study:
- It is assumed that 30%, 50%, and 100% ‘efficient’ and ‘new energy (zero emission)’ vehicles will be penetrated in 2030, 2040, and 2050 respectively;
- Three parameters are analyzed in both scenarios from 2020 to 2050: the stock, energy, and emission;
- New energy vehicles are zero-emission vehicles operating on electric and hydrogen fuel.
2.4. Data Limitations
Most of the data are taken from the Pakistan Economic Survey [2] and the Pakistan Energy Yearbook [7]. The stock of transport breakdown, i.e., two-wheelers, cars, buses, etc., is available, but their energy consumption is not mentioned, so there are assumptions too to conduct this study. As for elaboration of assumption, energy is given in the Pakistan Energy Yearbook [7] for the whole transport sector, not classified into two-wheeler, three-wheeler, cars, and other sub-categories. Therefore, this is assumed according to stock available, running pattern, the efficiency of vehicles, milage, and user choices. Further, some studies give an idea about classification of energy consumption which is cited in references.
3. Result and Discussion
Results are discussed in three domains: stock, energy, and emission.
3.1. Stock Outlook
As per the Pakistan Economic Survey [2], in 2020 there were 30 million vehicles registered in Pakistan. Factoring in historical trends, this number is expected to reach 42 million vehicles in 2030, 58 million vehicles in 2040, and 81 million vehicles in 2050. Stock was kept constant in both scenarios. The BL scenario contains existing and efficient vehicles (less fuel consuming, but the entire fleet is ICE-based technology) as shown in Figure 1. The CM scenario contains existing, efficient, and ‘new energy’ (i.e., zero emission) vehicles. In the CM scenario, 30%, 50%, and 100% new energy and efficient vehicles exist in 2030, 2040, and 2050 respectively.
In both scenarios, in 2020, with 100% existing stock, there are no efficient vehicles and no new energy vehicles. With the passage of time, technology improves and penetrates the system so that in 2030, 70% of existing stock and 30% of efficient stock is operating on ICE-based technology but consuming less fuel as shown in the BL scenario in Figure 1. A similar trend is shown in the CM scenario, with an addition (in fact, this is substitution, because stock was kept constant) of new energy vehicles. In 2040, there is 50% existing stock and 50% efficient stock in the BL scenario, while the CM scenario shows the same trend with substitution of new energy vehicles. In 2050, there is 100% efficient stock in both scenarios, while the CM scenario contains new energy vehicles as a new substitution. Two-wheelers and cars dominate the whole transport sector as per stock.
3.2. Energy Outlook
The BL scenario contains existing ICE technology vehicle (which emit CO2) and efficient (improved ICE technology) vehicles. The CM scenario contains existing, efficient and new energy (i.e., zero emission) vehicles. In 2030, 4.9 MTOE (12%) of energy was saved, in 2040, 10.7 MTOE (22.5%) of energy was saved, while in 2050, 24.8 MTOE (51%) of energy was saved. As per the CM scenario, 2040 is the peak energy-consuming year. Comparatively, cumulative consumption of energy is 18.45 MTOE as shown in Figure 2. This is because the overall number of transports is increasing per year. It appears that 2050 will have more vehicles and so must be the peak energy-consuming year, but in 2050, all stock is new energy vehicles which consume less energy. In 2030, the overall transport is less, i.e., 42 million, as compared to 2040, i.e., 58 million. The two factors, penetration of new energy vehicles and increasing transport per year makes 2040 the peak energy consuming year.
In the BL scenario, gasoline, diesel, and CNG fuels are the dominant fuels. In the CM scenario, electricity, hydrogen, and biofuels are the dominant fuels. Motor cars, two-wheelers, and freight trucks are the most energy-consuming transport. In 2030, 25–26% of energy is used by new technology. In 2040, 44-45% of energy is used by new technology, and in 2050, 100% of energy is used by new technology.
3.3. Emission Outlook
In 2030, 22 MtCO2eq (20%) of CO2 emissions are reduced, while in 2040, 45 MtCO2eq (35%) of emissions are reduced, and in 2050, 104 MtCO2eq (99%) of emissions are reduced, as shown in Figure 3. Freight trucks, motor cars, and two-wheelers are the most emission-producing transport. Although 2050 contains 100% zero-emission transport, ship and air transport still use polluting fuels so it will have around 1% of emissions this year.
4. Conclusions
Overall, with the penetration of new energy and efficient vehicles, Pakistan can save much energy and reduce more emissions, and this efficient technology will impact positively on users. It gives more kilometers of travel with less fuel which is an economical option for its adoption. However, the need for infrastructure and battery capacity is a big challenge for Pakistan’s transport sector. Since 2030 is the target year as per the EV policy of Pakistan, and deep focus shows that passenger transport consumes almost 58% of energy in 2030, energy use can be further reduced by motivating the rider to use public transport as shown in Figure 4.
Author Contributions
Conceptualization, W.N.A. and S.K.; methodology, U.U.R.Z.; software, S.K.; validation, P.W., W.N.A. and S.K.; formal analysis, W.N.A.; investigation, P.W.; resources, U.U.R.Z.; data curation, M.Z.; writing—original draft preparation, W.N.A.; writing—review and editing, S.K.; visualization, S.K.; supervision, P.W.; project administration, P.W. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
This study was approved by the Review and Editorial Board of Capital University of Engineering and Technology (CUST), Islamabad, 44000.
Informed Consent Statement
Not applicable.
Data Availability Statement
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Shahid, M.; Ullah, K.; Imran, K.; Masroor, N.; Sajid, M.B. Economic and environmental analysis of green transport penetration in Pakistan. Energy Policy 2022, 166, 113040. [Google Scholar] [CrossRef]
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- Pacific, A.; Model, I. AIM/Enduse Model Manual. In Asia Pacific Integrated Model; 2010; Volume 3. Available online: https://drive.google.com/file/d/1PCRtsnbtiZiLVB_1erAGgGCkdep4N7PG/view (accessed on 12 September 2024).
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Figure 1.
Stock under both scenarios according to transport share.
Figure 2.
Outlook of energy under both scenarios according to fuels.
Figure 3.
Outlook of emissions under both scenarios according to vehicle type.
Figure 4.
Share of public and private transport.
Table 1.
Scenario detail for AIM/Enduse model.
| Scenario | 2020 | 2030 | 2040 | 2050 |
|---|---|---|---|---|
| Baseline (BL) | Existing: 100% New Energy Vehicles: 0% | Existing: 100% New Energy Vehicles: 0% | Existing: 100% New Energy Vehicles: 0% | Existing: 100% New Energy Vehicles: 0% |
| Counter Measure (CM) | Existing: 100% New Energy Vehicles: 0% | Existing: 70% New Energy Vehicles: 30% | Existing: 50% New Energy Vehicles: 50% | Existing: 0% New Energy Vehicles: 100% |
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MDPI and ACS Style
Awan, W.N.; Khan, S.; Zulfiqar, M.; Zia, U.U.R.; Wang, P. Pakistan’s Transport Sector Modeling Using AIM/Enduse. Eng. Proc. 2024, 75, 1. https://doi.org/10.3390/engproc2024075001
AMA Style
Awan WN, Khan S, Zulfiqar M, Zia UUR, Wang P. Pakistan’s Transport Sector Modeling Using AIM/Enduse. Engineering Proceedings. 2024; 75(1):1. https://doi.org/10.3390/engproc2024075001
Chicago/Turabian StyleAwan, Waqas Nazir, Sidra Khan, Muhammad Zulfiqar, Ubaid Ur Rehman Zia, and Peng Wang. 2024. "Pakistan’s Transport Sector Modeling Using AIM/Enduse" Engineering Proceedings 75, no. 1: 1. https://doi.org/10.3390/engproc2024075001