Effect of Transportation Structure Change on Emissions Reduction

1
Effect of Transportation Structure Change on
Emissions Reduction
Based on Panel Data Model

• Reporter Xing Limin

2
Outline

• Introduction
• Panel Data Model
• Results and Discussion
• Conclusion

3

• Introduction Backgrounds

• Vehicle emissions have become important driving
  force for haze weather in China.
• In 2013, 20--30 PM2.5 in Beijing was produced
  by tail gas of motor vehicle. Institute of
  Atomospheric Physics, Chinese Academy of Sciences
• Energy consumption and CO2 in transport
  increase rapidly in past 20 years.
• Highway play a dominant role in turnover and
  CO2emissions.
• Transport structure oriented emission reduction
  policy in other countries can provide experience
  for China.
• America, Europe, Japan

4
Introduction Literature

• About transport carbon reduction, most authors
  research on energy price adjustment, technique
  improvement , tax policy.
• Few literature on the effect of transport
  structure change on CO2 reduction.
• Eg. Wei Qingqi et al(2014) built VEC model,
  concluded that traffic structure optimization has
  long term influence on energy intensity decrease.
• Disadvantage the quantitative relationship
  between structure change and CO2 reduction is
  not established.

5
Panel Data Model Variables and Data

• Independent Variables X1,X2,X3,X4 respectively
  stand for percentage of highway, railway,
  waterage (ocean carriage excluded) and civil
  aviation (international transport excluded).
• Dependent Variables Y stands for CO2 emissions/
  converted turnover.
• Cross section of the individual U.S., Europe,
  Japan, China.
• Data Resource Passenger- freight transport
  turnover come from Transport Statistical
  Yearbook, CO2 emissions come from World Bank
  Database. All the data are from 1990-2011.

6
Panel Data Model Stationarity Test

• X1,X2,X3,X4,Y
• first difference
• series are stable

7
Panel Data Model Cointegration Test

• Johansen cointegration test.
• Show that there is a long term balanced
  relation between transport structure and
  CO2/converted turnover.

8
Panel Data Model Model Building

• Based on Hausman test and F test, fixed effect
  and variable coefficient model is determined.

(1)
China U.S. Europe Japan
9
Panel Data Model Model Building

• imply the first difference
  value of percent of highway, railway, waterage
  and civil aviation turnover.
• signify the first difference value of carbon
  emissions /converted turnover.
• i1,2,3,4. respectively stand for China, U.S.,
  Europe, Japan from up to down in the Eq(1).
• stand for when
  increase/decrease 1,the amount of CO2
  will change.

10
Results and Discussion

• 1 change of highway percent would lead
  to increase at CO2 / converted turnover by 4.44,
  2.46 , 3.47,-1.77 in U.S., Europe, Japan and
  China.
• are all negative . Railway percent
  CO2 / converted turnover
  (Japanmax-3.63,Chinamin-0.38).
• negative. Waterage percent CO2
  / converted turnover (Europemax-22.11,China-0.
  056,U.S.0.805,Japan-0.093)
• positive. civil aviation percent
  CO2 / converted turnover
• (Japan U.S., China ,Europe.
  149.67,54.99,54.53,-27.07)

11
Conclusions

• Long term balanced relation existes between
  transport structure and carbon emission
  performance.
• Increase in the share of waterage and railway
  will lead to traffic carbon emissions reduction.
  Besides, the influence degree is quite varied due
  to different transport structure in different
  countries ,and different carbon emission
  performance of different traffic ways.

12

• Thanks!