scholarly journals Logarithmic Mean Divisia Index Decomposition of CO2 Emissions from Urban Passenger Transport: An Empirical Study of Global Cities from 1960–2001

2019 ◽  
Vol 11 (16) ◽  
pp. 4310 ◽  
Author(s):  
Meiting Tu ◽  
Ye Li ◽  
Lei Bao ◽  
Yuao Wei ◽  
Olivier Orfila ◽  
...  

The urban transport sector has become one of the major contributors to global CO2 emissions. This paper investigates the driving forces of changes in CO2 emissions from the passenger transport sectors in different cities, which is helpful for formulating effective carbon-reduction policies and strategies. The logarithmic mean Divisia index (LMDI) method is used to decompose the CO2 emissions changes into five driving determinants: Urbanization level, motorization level, mode structure, energy intensity, and energy mix. First, the urban transport CO2 emissions between 1960 and 2001 from 46 global cities are calculated. Then, the multiplicative decomposition results for megacities (London, New York, Paris, and Tokyo) are compared with those of other cities. Moreover, additive decomposition analyses of the 4 megacities are conducted to explore the driving forces of changes in CO2 emissions from the passenger transport sectors in these megacities between 1960 and 2001. Based on the decomposition results, some effective carbon-reduction strategies can be formulated for developing cities experiencing rapid urbanization and motorization. The main suggestions are as follows: (i) Rational land use, such as transit-oriented development, is a feasible way to control the trip distance per capita; (ii) fuel economy policies and standards formulated when there are oil crisis are effective ways to suppress the increase of CO2 emissions, and these changes should not be abandoned when oil prices fall; and (iii) cities with high population densities should focus on the development of public and non-motorized transport.

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 764 ◽  
Author(s):  
Jaruwan Chontanawat

ASEAN is a dynamic and diverse region which has experienced rapid urbanization and population growth. Their energy demand grew by 60% in the last 15 years. In 2013, about 3.6% of global greenhouse-gas emissions was emitted from this region and the share is expected to rise substantially. Hence, a better understanding of driving forces of the changes in CO2 emissions is important to tackle global climate change and develop appropriate policies. Using IPAT combined with variance analysis, this study aims to identify the main driving factors of CO2 emissions for ASEAN and four selected countries (Indonesia, Malaysia, Philippines and Thailand) during 1971–2013. The results show that population growth and economic growth were the main driving factors for increasing CO2 emissions for most of the countries. Fossil fuels play an important role in increasing CO2 emissions, however the growth in emissions was compensated by improved energy efficiency and carbon intensity of fossil energy. The results imply that to decouple energy use from high levels of emissions is important. Proper energy management through fuel substitution and decreasing emission intensity through technological upgrades have considerable potential to cut emissions.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 525 ◽  
Author(s):  
Edwin R. Grijalva ◽  
José María López Martínez

The emissions of CO2 gas caused by transport in urban areas are increasingly serious, and the public transport sector plays a vital role in society, especially when considering the increased demands for mobility. New energy technologies in urban mobility are being introduced, as evidenced by the electric vehicle. We evaluated the positive environmental effects in terms of CO2 emissions that would be produced by the replacement of conventional urban transport bus fleets by electric buses. The simulation of an electric urban bus conceptual model is presented as a case study. The model is validated using the speed and height profiles of the most representative route within the city of Madrid—the C1 line. We assumed that the vehicle fleet is charged using the electric grid at night, when energy demand is low, the cost of energy is low, and energy is produced with a large provision of renewable energy, principally wind power. For the results, we considered the percentage of fleet replacement and the Spanish electricity mix. The analysis shows that by gradually replacing the current fleet of buses by electric buses over 10 years (2020 to 2030), CO2 emissions would be reduced by up to 92.6% compared to 2018 levels.


2020 ◽  
Vol 12 (10) ◽  
pp. 4175 ◽  
Author(s):  
Gideon Nkam Taka ◽  
Ta Thi Huong ◽  
Izhar Hussain Shah ◽  
Hung-Suck Park

Ethiopia, among the fastest growing economies worldwide, is witnessing rapid urbanization and industrialization that is fueled by greater energy consumption and high levels of CO2 emissions. Currently, Ethiopia is the third largest CO2 emitter in East Africa, yet no comprehensive study has characterized the major drivers of economy-wide CO2 emissions. This paper examines the energy-related CO2 emissions in Ethiopia, and their driving forces between 1990 and 2017 using Kaya identity combined with Logarithmic Mean Divisia Index (LMDI) decomposition approach. Main findings reveal that energy-based CO2 emissions have been strongly driven by the economic effect (52%), population effect (43%), and fossil fuel mix effect (40%) while the role of emission intensity effect (14%) was less pronounced during the study period. At the same time, energy intensity improvements have slowed down the growth of CO2 emissions by 49% indicating significant progress towards reduced energy per unit of gross domestic product (GDP) during 1990-2017. Nonetheless, for Ethiopia to achieve its 2030 targets of low-carbon economy, further improvements through reduced emission intensity (in the industrial sector) and fossil fuel share (in the national energy mix) are recommended. Energy intensity could be further improved by technological innovation and promotion of energy-frugal industries.


2019 ◽  
Vol 11 (18) ◽  
pp. 4929 ◽  
Author(s):  
Zou ◽  
Tang ◽  
Wu

In recent decades, the Beijing–Tianjin–Hebei (BTH) region has experienced rapid economic growth accompanied by increasing energy demands and CO2 emissions. Understanding the driving forces of CO2 emissions is necessary to develop effective policies for low-carbon economic development. However, because of differences in the socioeconomic systems within the BTH region, it is important to investigate the differences in the driving factors of CO2 emissions between Beijing, Tianjin, and Hebei. In this paper, we calculated the energy-related industrial CO2 emissions (EICE) in Beijing, Tianjin, and Hebei from 2006 to 2016. We then applied an extended LMDI (logarithmic mean Divisia index) method to determine the driving forces of EICE during different time periods and in different subregions within the BTH region. The results show that EICE increased and then decreased from 2006 to 2016 in the BTH region. In all subregions, energy intensity, industrial structure, and research and development (R&D) efficiency effect negatively affected EICE, whereas gross domestic product per capita effect and population had positive effects on EICE. However, R&D intensity and investment intensity had opposite effects in some parts of the BTH region; the effect of R&D intensity on EICE was positive in Beijing and Tianjin but negative in Hebei, while the effect of investment intensity was negative in Beijing but positive in Tianjin and Hebei. The findings of this study can contribute to the development of policies to reduce EICE in the BTH region.


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