Influence of the Motor Vehicle Parking Structure by Fuel Type and Ecological Class on Greenhouse Gas Emissions

Abstract

Introduction. The results of estimating greenhouse gas (GHG) emissions by a vehicle fleet are described, using the COPERT-4 methodology and the baseline data contained in 1-BDD form, concerning the number of vehicle fleets in Russia and three options for detailing the fleet structure by the fuel type and ecological class in different organizations. Such data is not provided in the forms of state statistical reports and is generated by the researchers.Materials and methods. Various approaches to the structuring of the park by the fuel type and the ecological class give a slight variation in the values of GHG emissions’ gross (up to 4.1%), which confirms the correctness and approaches’ validity to the generation of the required initial data. The authors introduce the concept of total conditional transport work in order to adjust the values of the average annual mileage to the generation of the required initial data in the calculation of GHG emissions gross by the fleet of cars. Moreover, the value of total conditional transport work for all considered GHG variants should be the same.Results. As a result, if such adjustment is not made, the difference between the obtained calculated values of GHG emissions gross by the vehicle fleet for different authors would reach 25-30%. Discussion and conclusions. The reliability of the GHG emission values estimation is confirmed by the indirect method or by comparing the data of statistical reporting on the volumes of motor fuel consumption depending on different consumers in the fuel and energy balance, and on the fuel consumption values, and on the greenhouse gas emissions gross by the COPERT-4 method.

Methods and results of forecasting number and structure of motor fleet in the Russian Federation by types of engine and fuel used for calculation of greenhouse gases emission till 2050

“…Based on the above information and summarization of the results of similar forecasts made in other countries and also results of expert assessments made by specialists from MADI, NIIAT and other Russian organizations [7], [10] in the table 1 there are presented the results of the forecast of the structure of the car, freight motor vehicles and buses fleets in the Russian Federation for the period up to 2050 by the type of engine (type of fuel) according to the inertial and innovative scenario. Total 100,0 100,0 100,0 100,0 100,0…”

“…For reliable forecast of gross greenhouse gas emission with the use of the level 3 method for road transport of the IPCC methodology and the COPERT software [7], [8] except for the number of Russian motor fleet it`s required to define the fleet structure by: working volume of engines for cars, the total mass of freight motor vehicles and passenger capacity of buses; environmental class of motor vehicles; the type of power plants used.…”

Model for the assessment greenhouse gas emissions from road transport

“…The volumes of consumption of different types of fuel (electricity) by the car fleet for a given forecast period were determined by the method given in [6], based on the number of passenger, light commercial, freight exchanges and buses with different types of engines, their specific fuel consumption (g/km) and the weighted average annual mileage of passenger, light commercial, freight trucks and buses [6]. The volumes of consumption of different types of fuel (electricity) were established taking into account the balance of fuel consumption and the results of calculations under the COPERT program [9] or NIIAT [4] , and for the forecast periodtaking into account the trends of increasing fuel efficiency of vehicles (2% per year).…”

“…The volumes of consumption of different types of fuel (electricity) were established taking into account the balance of fuel consumption and the results of calculations under the COPERT program [9] or NIIAT [4] , and for the forecast periodtaking into account the trends of increasing fuel efficiency of vehicles (2% per year). The assessment of the impact of these indicators, especially the weighted average annual mileage, on the reliability of the estimation of gross GHG emissions by the vehicle fleet according to this method is considered in detail in [6].…”

“…In addition to GHG emissions by mobile road transport facilities, quite a lot of GHG is emitted by road transport infrastructure facilities (car service network, other facilities of production and technical base, as well as the road network), which should also be taken into account [1]. Considering that part of the source data cannot be determined based on the results of statistical analysis or field measurements, but only by calculation, it is important to verify the results of estimat-ing GHG emissions, which can be performed using different methods [6] and [7].…”