Mitigation potential of greenhouse gas emission and implications on fuel consumption due to clean energy vehicles as public passenger transport in Kathmandu Valley of Nepal: A case study of trolley buses in Ring Road

Pradhan, Shreekar; Ale, Bhakta Bahadur; Amatya, Vishwa B.

doi:10.1016/j.energy.2005.10.013

Cited by 38 publications

(12 citation statements)

References 3 publications

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“…In the transport sector, for categories other than twowheelers, the emission factors of N 2 O, NO x , CO and NMVOCs were taken from Shrestha et al 2013, who studied emissions from the on-road traffic fleet in the Kathmandu Valley using vehicle survey data and the International Vehicle Emissions (IVE) model (Table S7). The NO x emission factors for heavy-duty diesel vehicles were considered from Sadavarte and Venkataraman (2014); the EFs for Indian vehicles were modeled using the MOBILEv6.2 model. These were found to be consistent with EFs from for Chinese vehicles.…”

Section: Emission Factorsmentioning

confidence: 99%

Nepal emission inventory – Part I: Technologies and combustion sources (NEEMI-Tech) for 2001–2016

et al. 2019

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Abstract. The lack of a comprehensive, up-to-date emission inventory for the Himalayan region is a major challenge in understanding the extensive regional air pollution, including its causes, impacts and mitigation pathways. This study describes a high-resolution (1 km × 1 km) present-day emission inventory for Nepal, developed with a higher-tier approach. The complete study is divided into two parts; this paper covers technologies and combustion sources in residential, industrial, commercial, agricultural diesel-use and transport sectors as Part I (NEEMI-Tech), while emissions from the open burning of municipal waste and agricultural residue in fields and fugitive emissions from waste management, paddy fields, enteric fermentation and manure management for the period 2001–2016 will be covered in Part II (NEEMI-Open). The national total energy consumption (except hydropower, solar and wind energy) estimated in the base year 2011 was 374 PJ, with the residential sector being the largest energy consumer (79 %), followed by industry (11 %) and the transport sector (7 %). Biomass is the dominant energy source, contributing to 88 % of the national total energy consumption, while the rest is from fossil fuel. A total of 8.9 Tg of CO2, 110 Gg of CH4, 2.1 Gg of N2O, 64 Gg of NOx, 1714 Gg of CO, 407 Gg of NMVOCs, 195 Gg of PM2.5, 23 Gg of BC, 83 Gg of OC and 24 Gg of SO2 emissions were estimated in 2011 from the five energy-use sectors considered in NEEMI-Tech. The Nepal emission inventory provides, for the first time, temporal trends of fuel and energy consumption and associated emissions in Nepal for a long period, 2001–2016. The energy consumption showed an increase by a factor of 1.6 in 2016 compared to 2001, while the emissions of various species increased by a factor of 1.2–2.4. An assessment of the top polluting technologies shows particularly high emissions from traditional cookstoves and space-heating practices using biomass. In addition, high emissions were also computed from fixed-chimney Bull's trench kilns (FCBTKs) in brick production, cement kilns, two-wheeler gasoline vehicles, heavy-duty diesel freight vehicles and kerosene lamps. The monthly analysis shows December, January and February as periods of high PM2.5 emissions from the technology-based sources considered in this study. Once the full inventory including open burning and fugitive sources (Part II) is available, a more complete picture of the strength and temporal variability in the emissions and sources will be possible. Furthermore, the large spatial variation in the emissions highlights the pockets of growing urbanization, which emphasize the importance of the detailed knowledge about the emission sources that this study provides. These emissions will be of value for further studies, especially air-quality-modeling studies focused on understanding the likely effectiveness of air pollution mitigation measures in Nepal.

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Section: Emission Factorsmentioning

confidence: 99%

Nepal emission inventory – Part I: Technologies and combustion sources (NEEMI-Tech) for 2001–2016

et al. 2019

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“…The LEAP model has been used for energy systems planning [12][13][14], sector level analysis [15][16][17][18], GHG mitigation analysis [19][20][21][22] and other purposes. The LEAP modeling methodology is based on building the energy use and supply database and extending it further to simulate various scenarios of energy demand and supply.…”

Section: Long-range Energy Alternatives Planning System (Leap) Modelmentioning

confidence: 99%

Using Sankey diagrams to map energy flow from primary fuel to end use

Subramanyam

Paramshivan

Kumar

et al. 2015

Energy Conversion and Management

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a b s t r a c tThe energy sector is the largest contributor to gross domestic product (GDP), income, employment, and government revenue in both developing and developed nations. But the energy sector has a significant environmental footprint due to greenhouse gas (GHG) emissions. Efficient production, conversion, and use of energy resources are key factors for reducing the environmental footprint. Hence it is necessary to understand energy flows from both the supply and the demand sides. Most energy analyses focus on improving energy efficiency broadly without considering the aggregate energy flow. We developed Sankey diagrams that map energy flow for both the demand and supply sides for the province of Alberta, Canada. The diagrams will help policy/decision makers, researchers, and others to understand energy flow from reserves through to final energy end uses for primary and secondary fuels in the five main energy demand sectors in Alberta: residential, commercial, industrial, agricultural, and transportation. The Sankey diagrams created for this study show total energy consumption, useful energy, and energy intensities of various end-use devices. The Long-range Energy Alternatives Planning System (LEAP) model is used in this study. The model showed that Alberta's total input energy in the five demand sectors was 189 PJ, 186 PJ, 828.5PJ, 398 PJ, and 50.83 PJ, respectively. On the supply side, the total energy input and output were found to be 644.84 PJ and 239 PJ, respectively. These results, along with the associated energy flows were depicted pictorially using Sankey diagrams. The Sankey diagrams reveal the current efficiencies within various end-use sectors and could help identify options for improving energy efficiency in order to reduce GHG emissions.

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“…At the local level, it has been used to model the total energy consumption and associated emissions of the household sector in Delhi, India [19]. It has also been widely used to study the energy and environmental impacts of the transport sector [20,21], of electricity generation [22,23], and of the utilization of biomass energy [24]. However, there have been few studies using LEAP to comprehensively evaluate the efficiency of city-level policies and measures aimed at reducing energy demand and greenhouse gas (GHG) emissions, and covering all urban sectors [6,25,26].…”

Section: The Leap Modelmentioning

confidence: 99%

Alternative Scenarios for the Development of a Low-Carbon City: A Case Study of Beijing, China

2011

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Abstract:The establishment of low-carbon cities has been suggested all over the World, since cities are key drivers of energy usage and the associated carbon emissions. This paper presents a scenario analysis of future energy consumption and carbon emissions for the city of Beijing. The Long-range Energy Alternatives Planning (LEAP) model is used to simulate a range of pathways and to analyze how these would change energy consumption and carbon emissions from 2007 to 2030. Three scenarios have been designed to describe future energy strategies in relation to the development of Beijing city, namely a reference scenario (RS), control scenario (CS), and integrated scenario (IS). The results show that under the IS the total energy demand in Beijing is expected to reach 88.61 million tonnes coal equivalent (Mtce) by 2030 (59.32 Mtce in 2007), 55.82% and 32.72% lower than the values under the RS and the CS, respectively. The total carbon emissions in 2030 under the IS, although higher than the 2007 level, will be 62.22% and 40.27% lower than under the RS and the CS, respectively, with emissions peaking in 2026 and declining afterwards. In terms of the potential for reduction of energy consumption and carbon emissions, the industrial sector will continue to act as the largest contributor under the IS and CS compared with the RS, while the building and transport sectors are identified as promising fields for achieving effective control of energy consumption and carbon emissions over the next two decades. The calculation results show that an integrated package of measures is the most effective in terms of energy savings and carbon emissions mitigation, although it also faces the largest challenge to achieve the related targets. OPEN ACCESSEnergies 2011, 4 2296

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Mitigation potential of greenhouse gas emission and implications on fuel consumption due to clean energy vehicles as public passenger transport in Kathmandu Valley of Nepal: A case study of trolley buses in Ring Road

Cited by 38 publications

References 3 publications

Nepal emission inventory – Part I: Technologies and combustion sources (NEEMI-Tech) for 2001–2016

Nepal emission inventory – Part I: Technologies and combustion sources (NEEMI-Tech) for 2001–2016

Using Sankey diagrams to map energy flow from primary fuel to end use

Alternative Scenarios for the Development of a Low-Carbon City: A Case Study of Beijing, China

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