scholarly journals Scenario Analysis of Urban Road Transportation Energy Demand and GHG Emissions in China—A Case Study for Chongqing

2018 ◽  
Vol 10 (6) ◽  
pp. 2033 ◽  
Author(s):  
Xianchun Tan ◽  
Yuan Zeng ◽  
Baihe Gu ◽  
Yi Wang ◽  
Baoguang Xu
Keyword(s):  
Scenario Analysis ◽  
Energy Demand ◽  
Ghg Emissions ◽  
Road Transportation ◽  
Transportation Energy ◽  
Urban Road

scholarly journals A Prediction Method of GHG Emissions for Urban Road Transportation Planning and Its Applications

2020 ◽  
Vol 12 (24) ◽  
pp. 10251
Author(s):  
Jing Gan ◽  
Linheng Li ◽  
Qiaojun Xiang ◽  
Bin Ran
Keyword(s):  
Carbon Emissions ◽  
Transportation Planning ◽  
Road Traffic ◽  
Ghg Emissions ◽  
Prediction Method ◽  
Accurate Estimation ◽  
Low Carbon ◽  
Road Transportation ◽  
Urban Road ◽  
Carbon Control

The increasing vehicle usage has brought about a sharp increase in greenhouse gas (GHG) emissions of vehicles, which brings severe challenges to the sustainable development of road transportation in Chinese counties. Low-carbon transportation planning is an essential strategy for carbon control from the source of carbon emissions and is crucial to the full transition to a low-carbon future. For transportation planning designers, a quick and accurate estimation of carbon emissions under different transportation planning schemes is a prerequisite to determine the optimal low-carbon transportation development plan. To address this issue, a novel prediction method of hourly GHG emissions over the urban roads network was constructed in this paper. A case study was conducted in Changxing county, and the results indicate the effectiveness of our proposed method. Furthermore, we applied the same approach to 30 other counties in China to analyze the influencing factors of emissions from urban road networks in Chinese counties. The analysis results indicate that the urban road mileage and arterial road ratio are the two most important factors affecting road network GHG emissions in road traffic planning process. Moreover, the method was employed to derive peak hour emission coefficients that can be used to quickly estimate daily or annual GHG emissions. The peak hour emission of CO2, CH4, and N2O accounts for approximately 9–10%, 8.5–10.5%, 5.5–7.5% of daily emissions, respectively. It is expected that the findings from this study would be helpful for establishing effective carbon control strategies in the transportation planning stage to reduce road traffic GHG emissions in counties.

scholarly journals The Role of Single End-Users and Producers on GHG Mitigation in Pakistan—A Case Study

2020 ◽  
Vol 12 (20) ◽  
pp. 8351 ◽  
Author(s):  
Waqas Ahmed ◽  
Jamil Ahmed Sheikh ◽  
Abbas Z. Kouzani ◽  
M. A. Parvez Mahmud
Keyword(s):  
Energy Source ◽  
Energy Demand ◽  
Meteorological Data ◽  
Ghg Emissions ◽  
Annual Average ◽  
Ghg Mitigation ◽  
Positive Role ◽  
Initial Cost

End energy user is dependent on fossil fuel-based main-grid and contributes toward greenhouse gasses (GHG) emissions. Changing its energy source will change the dynamics of the power plant, contribution towards GHG production. This case study aims to highlight the minute but positive role of a single end energy user, invisible to the main grid in GHG mitigations through photovoltaic energy source, selected among Pakistan’s top 10 most populous cities as per census 2017. Quetta is a selected city in Pakistan as the best fit location based on annual average daily solar radiations (AADSR) data retrieved from National Aeronautics and Space Administration (NASA) meteorological data. Helioscope software is used to select −15° tilt and 180° azimuthal angles, which further increased Quetta’s AADSR value from 5.54 kWh/m2/d to 5.93 kWh/m2/d. For research significance, a realistic approach is undertaken by proper selection of solar panel type based on Quetta’s annual average temperature, load categorization, user selection and inputs from a solar energy expert. Finally, initial cost, investment and GHG mitigation analysis are carried out in RETScreen Expert software, which validates the minute but the prominent role of a single, end energy user by mitigating 122 tons of CO2 in 25-year project life span. Further, the proposed project favors end-user financially by recovering its $4501 initial cost in less than four years by effectively meeting its energy demand and saving $1195 per annum.

scholarly journals Electric Vehicle Integration into Road Transportation, Intelligent Transportation, and Electric Power Systems: An Abu Dhabi Case Study

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1039-1057
Author(s):  
Amro M. Farid ◽  
Asha Viswanath ◽  
Reem Al-Junaibi ◽  
Deema Allan ◽  
Thomas J. T. Van der Van der Wardt
Keyword(s):  
Electric Power ◽  
Intelligent Transportation ◽  
Energy System ◽  
Transportation System ◽  
Electric Power System ◽  
Abu Dhabi ◽  
Road Transportation ◽  
Unit Distance ◽  
The Impact

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

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