Projections of highway vehicle population, energy demand, and CO2 emissions in India to 2040

Arora, Salil; Vyas, Anant; Johnson, Linda Cooke

doi:10.1111/j.1477-8947.2011.01341.x

Cited by 29 publications

(24 citation statements)

References 14 publications

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“…As a key component of economic development and human welfare, transportation activity is increasing rapidly around the world (Uherek et al, 2010;Wang et al, 2006;ICAO/FESG, 2008;Arora et al, 2011;Dargay et al, 2007;Ribeiro et al, 2007). Robust growth in the transportation sector is expected to continue over the next several decades.…”

Section: Importance Of Emissions From the Transportation Sectormentioning

confidence: 99%

Global emission projections for the transportation sector using dynamic technology modeling

et al. 2014

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Abstract. In this study, global emissions of gases and particles from the transportation sector are projected from the year 2010 to 2050. The Speciated Pollutant Emission Wizard (SPEW)-Trend model, a dynamic model that links the emitter population to its emission characteristics, is used to project emissions from on-road vehicles and non-road engines. Unlike previous models of global emission estimates, SPEW-Trend incorporates considerable detail on the technology stock and builds explicit relationships between socioeconomic drivers and technological changes, such that the vehicle fleet and the vehicle technology shares change dynamically in response to economic development. Emissions from shipping, aviation, and rail are estimated based on other studies so that the final results encompass the entire transportation sector. The emission projections are driven by four commonly-used IPCC (Intergovernmental Panel on Climate Change) scenarios (A1B, A2, B1, and B2). With global fossil-fuel use (oil and coal) in the transportation sector in the range of 128–171 EJ across the four scenarios, global emissions are projected to be 101–138 Tg of carbon monoxide (CO), 44–54 Tg of nitrogen oxides (NOx), 14–18 Tg of non-methane total hydrocarbons (THC), and 3.6–4.4 Tg of particulate matter (PM) in the year 2030. At the global level, a common feature of the emission scenarios is a projected decline in emissions during the first one or two decades (2010–2030), because the effects of stringent emission standards offset the growth in fuel use. Emissions increase slightly in some scenarios after 2030, because of the fast growth of on-road vehicles with lax or no emission standards in Africa and increasing emissions from non-road gasoline engines and shipping. On-road vehicles and non-road engines contribute the most to global CO and THC emissions, while on-road vehicles and shipping contribute the most to NOx and PM emissions. At the regional level, Latin America and East Asia are the two largest contributors to global CO and THC emissions in the year 2010; this dominance shifts to Africa and South Asia in the future. By the year 2050, for CO and THC emissions, non-road engines contribute the greatest fraction in Asia and the former USSR, while on-road vehicles make the largest contribution in Latin America, Africa, and the Middle East; for NOx and PM emissions, shipping controls the trend in most regions. These forecasts include a formal treatment of the factors that drive technology choices in the global vehicle sector and therefore represent a robust and plausible projection of what future emissions may be. These results have important implications for emissions of gases and aerosols that influence air quality, human health, and climate change.

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Section: Importance Of Emissions From the Transportation Sectormentioning

confidence: 99%

Global emission projections for the transportation sector using dynamic technology modeling

et al. 2014

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“…The other critical component of the vehicular benchmark is the fuel efficiencies of vehicles in Delhi. Because data on fuel efficiencies are not currently collected by any Indian government agency, estimates from the Automotive Research Association of India (ARAI ) were used by Arora and colleagues () in estimating the fuel efficiencies of Indian vehicles (see table ). We then coupled fuel efficiencies by vehicle type with Delhi's VKT to estimate the fuel used in road transport.…”

Section: Data Sources and Resultsmentioning

confidence: 99%

Implementing Trans‐Boundary Infrastructure‐Based Greenhouse Gas Accounting for Delhi, India

Chávez¹,

Ramaswami²,

Nath³

et al. 2012

J of Industrial Ecology

100

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SummaryCommunity-wide greenhouse gas (GHG) emissions accounting is confounded by the relatively small spatial size of cities compared to nations-due to which, energy use in essential infrastructures serving cities, such as commuter and airline transport, energy supply, water supply, wastewater infrastructures, and others, often occurs outside the boundaries of the cities using them. The trans-boundary infrastructure supply chain footprint (TBIF) GHG emissions accounting method, tested in eight U.S. cities, incorporates supply chain aspects of these trans-boundary infrastructures serving cities, and is akin to an expanded geographic GHG emissions inventory. This article shows the results from applying the TBIF method in the rapidly developing city of Delhi, India.The objectives of this research are to (1) describe the data availability for implementing the TBIF method within a rapidly industrializing country, using the case of Delhi, India; (2) identify methodological differences in implementation of the TBIF method between Indian versus U.S. cities; and (3) compare broad energy use metrics between Delhi and U.S. cities, demonstrated by Denver, Colorado, USA, whose energy use characteristics and TBIF GHG emissions have previously been shown to be similar to U.S. per capita averages.This article concludes that most data required to implement the TBIF method in Delhi are readily available, and the methodology could be translated from U.S. to Indian cities. Delhi's 2009 community-wide GHG emissions totaled 40.3 million metric tonnes of carbon dioxide equivalents (t CO 2 -eq), which are normalized to yield 2.3 t CO 2 -eq per capita; nationally, India reports its average per capita GHG emissions at 1.5 t CO 2 -eq. In-boundary GHG emissions contributed to 68% of Delhi's total, where end use (including electricity) energy in residential buildings, commercial and industrial usage, and fuel used in surface transportation contributed 24%, 19%, and 21%, respectively. The remaining 4% of the in-boundary GHG emissions were from waste disposal, water and wastewater treatment, and cattle. Trans-boundary infrastructures were estimated to equal 32% of Delhi's TBIF GHG emissions, with 5% attributed to fuel processing, 3% to air travel, 10% to cement, and 14% to food production outside the city. Keywords:carbon footprint city-scale greenhouse gas (GHG) emissions emissions accounting industrial ecology material flow analysis (MFA) trans-boundary greenhouse gases (GHGs)

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“…The values in part B indicate that there has been a continuous increase in the number of registered motor vehicles in India. It is evident from these numbers that the registered motor vehicles will increase from approximately 153.75 million in 2020 to 209.58 million in 2040 [13].…”

Section: Vehicle Scenariosmentioning

confidence: 99%

“…The resultant emission estimate increases from 12,548 Mt in 2020 to 16,053 Mt in 2030 [12], which is 28% higher than the 2020 level. The conditions in India will be worse as the motor vehicle population is expected to increase by more than 84% [13], i.e., from 271 million in 2020 to 498 million in 2030. The corresponding emissions are projected to increase from 790 Mt in 2020 to 1,241 Mt in 2030, i.e., a rise of 57% over 10 years [12].…”

Section: Introductionmentioning

confidence: 99%

How Can India Achieve Sustainable Transportation Goals Through Electrification?

Majumder

Kumar

et al. 2020

Preprint

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Air pollution has led to global temperature increases and health hazards. Emission reduction is a global mission, and countries worldwide are working towards this goal. Transportation network electrification is a possible solution. Electrifying only transit systems will not have much impact without energy policy evolution and renewable source share enhancement. Since transportation needs rise with increasing population, emission intensity reduction steps should be implemented soon to affect global emission reduction. This work proposes reducing the share of vehicles with high per-passenger emissions and replacing them with mass transit systems under a generation scenario. It primarily establishes emission trends under the current vehicle scenario with only fossil fuel-burning vehicles and electric vehicle (EV) scenarios. It also considers different fuel mixes and finally compares all vehicle and fuel mix combinations. Results reveal that the proposed transport and fuel mix options help to reach the target set by India under the Paris Agreement.

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Projections of highway vehicle population, energy demand, and CO2 emissions in India to 2040

Cited by 29 publications

References 14 publications

Global emission projections for the transportation sector using dynamic technology modeling

Global emission projections for the transportation sector using dynamic technology modeling

Implementing Trans‐Boundary Infrastructure‐Based Greenhouse Gas Accounting for Delhi, India

How Can India Achieve Sustainable Transportation Goals Through Electrification?

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