Long term characterization of the vehicle stock in Turkey. (October 2021)

• Record Type: Journal Article
• Authors: Aydınalp Köksal, Merih; Tekeli, Ş. Elçin; Ara Aksoy, Shihomi; Kızıltan, Anna; Kızıltan, Mustafa; Duran, Nilhan; Aslanoğlu, S. Yeşer; Öztürk, Fatma; Özyürek, Nazan; Doğan, Pervin; Yılmaz, Ağça Gül; Köksal, Canan Esin; Çetintürk Gürtepe, İrde; Yereli, Ahmet Burçin; Birpınar, Mehmet Emin; Güllü, Gülen
• Is Part Of: Transportation research. Volume 99(2021)
• Publication Date: 2021-10
• Subjects: Registered Vehicle Forecast -- Scrapped Vehicles Predictions -- Automobile -- ARMA -- Turkey; C22 -- C53 -- R42; ACF Autocorrelation Function -- AIC Akaike Information Criteria -- ANFIS Adaptive Network-based Fuzzy Inference System -- ANN Artificial Neural Networks -- APE Absolute Percentage Error -- AR Auto-Regressive -- ARMA Auto Auto-Regressive Moving Average -- BAU Business As Usual -- CAFÉ Corporate Average Fuel Economy -- BIC Bayesian Information Criteria -- EV Electric Vehicle -- GDP Gross Domestic Product -- GHG Greenhouse gases -- M1 Passenger Cars -- MA Moving Average -- MAPE Mean Average Percentage Error -- N1 Light Commercial Vehicles -- NEMS National Energy Modeling System -- ODD Automotive Distributers' Association -- PACF Partial Autocorrelation Function -- REPAC Realistic Vehicle Adoption Model -- TRAN Transportation Model -- TurkStat Turkish Statistical Institute; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2021.102988
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: A framework is developed to characterize the vehicle fleet for policy assessment. The fleet is profiled based on size, age, fuel, technology, engine volume, mileage. The fleet profile is characterized based on five scenarios for the 2020–2030 period. Business-as-usual scenario results presented a rapidly increasing and aging fleet. Scenarios on implementing incentives resulted in a younger and fuel-efficient fleet. Abstract: Projections of vehicle profiles play an essential role in developing government policies for emissions reductions in the automotive sector. Determining the trends of key parameters related to tailpipe emissions is critical for analyzing the adverse effects of vehicle emissions on air quality. This study presents a framework that can be used to assess the impacts of the vehicle fleet characteristics on pollutant emissions. Passenger cars and light commercial category vehicles in the Turkish vehicle fleet are analyzed in terms of size (sales and scrappage rates), age distribution, fuel type, engine displacement, and mileage. The distributions based on these parameters are forecasted for the 2020–2030 period under five alternative policy scenarios for Turkey. Should no scrappage incentives be imposed, the average vehicle age is estimated to increase significantly, and shares of hybrid and electric vehicles will be minor.