Zhaohua Wang and Wei Liua, Determinants of CO2 emissions from household daily travel in Beijing, China: Individual travel characteristic perspectives, Applied Energy Volume 158, 15 November 2015, Pages 292–299, doi:10.1016/j.apenergy.2015.08.065
Abstract: The article investigates the changes in personal travel characteristics and CO2 emissions, and then discusses the effects of population, economic activity, transport capacity, vehicle emission intensity, and individual travel characteristic which includes the effects of transportation intensity, transportation mode share, and vehicle-use intensity on CO2 emissions based on decomposition analysis.
2. Where do the authors work, and what are their areas of expertise? Note any other publications by the authors with relevance to the 6Cities project.
Zhaohua Wang: School of Management and Economics, Center for Energy & Environmental Policy Research of Beijing Institute of Technology, and Collaborative Innovation Center of Electric Vehicles in Beijing.
Wei Liu: School of Management and Economics of Beijing Institute of Technology and Economic & Planning Research Institute of the Ministry of Railways, Beijing 100038, China
Zhaohua Wang and Wei Liu, The Impacts of Individual Behavior on Household Daily Travel Carbon Emissions in Beijing, China, Energy Procedia Volume 61, 2014, Pages 1318–1322 International Conference on Applied Energy, ICAE2014, doi:10.1016/j.egypro.2014.11.1090
3. What are the main findings or arguments presented in the article or report? The article estimated household daily travel CO2 emissions in Beijing from 2000 to 2012. It also analyzed influence factors of CO2 emissions by decomposition analysis. The result shows that vehicle-use intensity, economic activity and population were driving emissions up. Promoting individual behavioral change and reducing car use should be emphasized.
4. Describe at least three ways that the argument is supported.
The study calculated the household daily travel CO2 emissions due to different transportation modes in Beijing from 2000 to 2012, as shown in Fig. 1. Results show that household daily travel CO2 emission continued to rise during the study period. They increased four-fold, from 4.34 Mt in 2000 to 18.58 Mt in 2012, and the annual growth rate was 13%. Particularly, the growth rates in 2004 and 2009 had slowed due to the a reduced daily trip frequency induced by the SARS outbreak in 2004 and new odd–even traffic control measures launched in 2009.
Decomposition results show that the economic activity effect is the leading factor contributing to the increase in household daily travel CO2 emissions in Beijing: it causes the emissions to increase by 12.13 Mt in the study period, accounting for 85.18% of overall emissions. The per capita disposable income factor reflects the quality of life as well as economic growth. In Beijing, the per capita disposable income has increased almost three-fold in the last decade, from 10,300 Yuan in 2000 to 36,500 Yuan in 2012, as shown in Fig. 2. As the economic status improves, people with a higher standard of living will pursue a higher quality of life, so they might shift from public transportation to faster, more comfortable travel modes, for example private cars and taxis. High-income households tend to own more private cars and to use each of these vehicles slightly more extensively than low-income households: many people consider a car to be a status symbol. Therefore, increased incomes have inevitably led to excessive demand for private cars, which resulted in the rapid growth of CO2 emissions.
The vehicle-use intensity effect is the second most important factor leading to the growth of household daily travel CO2 emissions. Fig. 3 shows the situation of vehicle-use intensity in Beijing from 2000 to 2012, from which we can find that only the private car use intensity presents an increasing trend. From the perspective of vehicle population for each transport mode, the number of bus and subway vehicles increased by 4% and 17% respectively. However, the number of private cars in Beijing has increased more than 6-fold in this study period, which caused a significant change in residential transport behavior, as shown in Table 3. For one thing, the increased number of private cars makes people choose a private car instead of a public transport mode.
5. What three (or more) quotes capture the message of the article or report?
“This research examines the features and driving factors of CO2 emissions from household daily travel in Beijing from 2000 to 2012. It first investigates the changes in personal travel characteristics and CO2 emissions, and then discusses the effects of population, economic activity, transport capacity, vehicle emission intensity, and individual travel characteristic which includes the effects of transportation intensity, transportation mode share, and vehicle-use intensity on CO2 emissions based on decomposition analysis.”
“Results show that: (1) CO2 emission due to urban traffic has increased from 4.34 Mt in 2000 to 18.58 Mt in 2012, following an annual growth rate of 13%; (2) the per capita disposable income, vehicle-use intensity, population and transport capacity effects are found to be the main drivers that increase household daily travel CO2 emissions; and (3) the transportation intensity, vehicle emission intensity, and transportation mode share have effects on the reduction of CO2 emissions over the study period.”
“However, few studies have examined the driving forces for household transport CO2 emissions from the perspective of individual travel characteristic. Therefore, this study aims to fill this gap and develops a comprehensive picture of the driving forces behind changing CO2 emissions, related to household daily travel, from a systemic point of view. Thus, taking Beijing as an example, this study first calculates the CO2 emissions from household daily transportation from 2000 to 2012, and then constructs a structural decomposition model to examine the main factors that influence the changes in emissions by using LMDI.”
6. What were the methods, tools and/or data used to produce the claims or arguments made in the article or report?
Estimation of CO2 emission: In general, two methods are used to calculate CO2 emissions from the transport sector: the fuel-based method and the distance-based method. In the fuel-based method, emissions are calculated by multiplying the fuel consumption by its CO2 emission coefficient. In the distance-based approach, emissions can be estimated by using distance based emission factors and transport activity data such as vehicle-kilometers or person-kilometers travelled by different vehicle types. Due to data limitations, this study uses an improved distance-based method to estimate household daily travel CO2 emissions in Beijing.
LMDI decomposition model: Logarithmic Mean Divisia Index approach has the ability to perform a perfect decomposition and to accommodate zero values in the data set [46]. Thus, this study constructs a decomposition analysis model by applying LMDI to investigate the major factors that may affect changes in Beijing’s household daily travel CO2 emissions.
Data sources and pre-treatment: Passenger turnover volumes of different modes are estimated by multiplying the total passenger trip volume by the ratio of the four types of transportation mode as collected from Annual Reports on Development of Beijing Transport. However, due to the end-number license plate policy implemented in October 2008 in Beijing, private cars will be not allowed to be inside the fifth ring road zone for one day per week (except weekends) by means of grouping by the end number of the car license plate. Thus, the actually number of on-road private car is a little less than the vehicle population reported by the Statistics. For convenience, the article multiplied the official data by 0.8 to get the number of private cars for decomposition in this study.
7. How (if at all) are health disparities or other equity issues addressed in the article or report? The health disparities or equity issues are not mentioned in the article.
8. Where has this article or report been referenced or discussed? (In some journals, you can see this in a sidebar.) This article has not been referenced or discussed in other articles.
9. Can you learn anything from the article or report’s bibliography that tells us something about how the article or report was produced? The bibliography is about the energy use or policies in household aspects. Therefore, I think the author starts to analyze different areas of household using energy. Then related them to conclude the factors of CO2 emissions from household daily travel in Beijing.
10. What three points, details or references from the text did you follow up on to advance your understanding of how air pollution science has been produced and used in governance and education in different settings?
The government should continue to optimize the structure and quality of transport systems to make adequate preparation for the promotion of green energy.
Officials should strongly advocate the idea of low-carbon transport and continue to encourage people to use public transport.
From the article we can know that how to decarbonize the transport sector is one of the greatest challenges facing China.
2. Where do the authors work, and what are their areas of expertise? Note any other publications by the authors with relevance to the 6Cities project.
3. What are the main findings or arguments presented in the article or report?
The article estimated household daily travel CO2 emissions in Beijing from 2000 to 2012. It also analyzed influence factors of CO2 emissions by decomposition analysis. The result shows that vehicle-use intensity, economic activity and population were driving emissions up. Promoting individual behavioral change and reducing car use should be emphasized.
4. Describe at least three ways that the argument is supported.
5. What three (or more) quotes capture the message of the article or report?
6. What were the methods, tools and/or data used to produce the claims or arguments made in the article or report?
7. How (if at all) are health disparities or other equity issues addressed in the article or report?
The health disparities or equity issues are not mentioned in the article.
8. Where has this article or report been referenced or discussed? (In some journals, you can see this in a sidebar.)
This article has not been referenced or discussed in other articles.
9. Can you learn anything from the article or report’s bibliography that tells us something about how the article or report was produced?
The bibliography is about the energy use or policies in household aspects. Therefore, I think the author starts to analyze different areas of household using energy. Then related them to conclude the factors of CO2 emissions from household daily travel in Beijing.
10. What three points, details or references from the text did you follow up on to advance your understanding of how air pollution science has been produced and used in governance and education in different settings?