Road Density-Presentation_2nd Draft.pptx

Paper presented in Sustainable Energy and Environmental Challenges (VII SEEC), International Conference at IIT BHU.

1. Projection of 2-wheeler vehicle fleet in India using road density per capita for accurate emission estimation Kumar Saurabh (PhD Scholar) & Dr. Rudrodip Majumdar Energy Environment and Climate Change, National Institute of Advanced Studies IISc . Campus, Bengaluru, Karnataka - 560012 16 th December 2022 SEEC2022_072

2. Background C omplicated task – Projection of road travel demand and associated emissions Core – Identification of on-road vehicle stock (current and in future timeline) Established – GDP per capita of a country as main explanatory independent parameter Other factors – Road density , Public transport status, Urbanization, Consumer b ehaviour Considered for this study – Road density per 1000 persons (as land is a limiting factor) Source: Huo , H., Wang, M., Johnson, L., & He, D. (2007). Saturation level of vehicle ownership (GDP/capita) : North America – 0.8 (800 per 1000 people) Europe/Japan – 0.6 (600 per 1000 people) Developing Asian countries – 0.45 (450 per 1000 people)

3. Why road density/capita? Model Framework Road-density (in km) per 1000 persons will also follow a similar S-shape curve (assumed by Gompertz or logistic functions) as there is a high degree of correlation (0.98) between GDP per capita and road length per capita in India. Function used for study – Gompertz function Existing model ( GDP based ) – Model A : Time series model used for study: Revised model ( Road-density based ) – Model B : Revised model ( Road-density & GDP based ) – Model C :  

4. Methodology Three models conceptualized – A ( GDP-based ); B ( road d ensity-based ) & C ( road & GDP-based ). Statistical significance of parameter estimates ( α , β , δ , and θ ) were obtained from ANOVA table. All above values obtained for different saturation values of vehicle ownership ( γ ) – 200 , 250, 300, 350, 400, 450, and 500 . The values of R 2 for all the three models ( A , B and C ) with different γ ( 200 to 500 ) were recorded as a range. 2W vehicle fleet projection by assuming constant 6 % growth in GDP per capita (in PPP terms) and constant 2% growth rate for road density per 1000 persons. Results Model A & B – All α , β or δ , and θ are found to be statistically significant for all values of γ . Model C – All α , δ , and θ ( except β) are found to be statistically significant for all values of γ . Model C – GDP estimate β is found to be statistically significant at only 10 % ( p<0.1 ) for γ =200 , statistically insignificant for γ =250 , significant at 1% (p<0.01) for other γ = 300, 350, 400, 450 & 500 . Similar results in statistical significance observed by adding an additional variable (GDP) in Model B (road density-based) to facilitate its transition to Model C . Adding additional variable in Model A is significant.

5. Results – Model A Results – Model B Assuming 6% growth in GDP per capita (PPP) : Year GDP/capita (PPP) γ = 200 γ = 300 γ = 400 γ = 500 2020 7250 US$ 146 151 152 153 2030 13000 US$ 187 245 284 313 2040 23250 US$ 199 290 372 444 2050 41650 US$ 200 299 395 488 Assuming 2% growth in Road density per 1000 persons: Year Road Density/1000 γ = 200 γ = 300 γ = 400 γ = 500 2020 4.7 km 140 147 151 152 2030 5.7 km 164 206 233 252 2040 7.0 km 186 254 307 351 2050 8.5 km 196 282 359 426

6. Discussion & Conclusion The R 2 for Models A, B, and C varied between the ranges (0.880-0.945 ) , (0.978-0.988) , and (0.988-0.989) , respectively, for different γ values (200, 250, 300, 350, 400, 450, and 500). Example: For γ =500 , on-road 2W vehicle fleet in 2050: Model A – 81.50 Cr. Model B – 71.25 Cr. Model C – 69.50 Cr . Road density per 1000 people is significantly better explanatory variable than GDP per capita for projecting on-road vehicle fleet as it removes over-projections .

7. Thank You . Reference: Huo , H., Wang, M., Johnson, L., & He, D. (2007). Projection of Chinese motor vehicle growth, oil demand, and CO 2 emissions through 2050. Transportation Research Record , 2038(1), 69-77 .