Location: IN - India
This dataset represents the transport of one metric ton.km of freight in India by a diesel locomotive. The dataset represents the entire transport life cycle, including the production and maintenance of the locomotive, production and maintenance of the goods wagons, the transportation of goods and the construction, operation, maintenance and disposal of railway track. The scope of this dataset is the operation of the locomotive, which has inputs of locomotive and goods wagon, maintenance (goods wagon and locomotive) and railway track via linking to global datasets, i.e. the infrastructure and maintenance datasets are not Indian-specific.
Diesel consumption includes shunting and is calculated from annual diesel fuel use per rail segment (Indian Railways, 2017d). The fuel use for freight only transport is taken directly, while the diesel use for shunting is calculated from total shunting diesel consumption, the percentage of shunting engine kilometres for freight movement (63%) (Indian Railways, 2017e) and the percentage of freight gross tonne.kms moved by diesel locomotives (35%) (Indian Railways, 2017b). The diesel use for freight in mixed loads and other train journeys is calculated from the total diesel use in these rail segments (Indian Railways, 2017d) and the percentage of diesel gross tonne.kms for freight movements (52%) (Indian Railwasy, 2017b). These figures represent all rail freight movements in India.
Emissions of particulates, nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC) are calculated using emission factors from EcoTransIT (2016). It is assumed that the non-regulated emission factor best fits Indian freight locomotives as these currently do not have to adhere to any emissions standards. The partitioning of particulate emissions into size classes is according to Spielmann et al. (2007). Sulphur dioxide (SO2) emissions are calculated from the sulphur content in local diesel and the assumption that all sulphur is emitted as sulphur dioxide. Personal communication with a representative of the Indian Oil Corporation Limited confirmed that all refineries in India produce only BS IV diesel, which has a sulphur content of 50 ppm. All other emissions to air are extrapolated on the basis of diesel consumption from the global dataset ("transport, freight train, diesel, GLO, 2004"), with the global dataset derived from data primarily of Swiss/European orgin, described in full in Spielmann et al. (2007).
Locomotive production and maintenance are described in the individual global datasets. Locomotive demand per metric ton.km is calculated from the number of diesel locomotives (Indian Railways, 2017a), the percentage of diesel gross metric ton.kms for freight movement (52%) (Indian Railways, 2017b) and the total metric ton.kms of freight moved by diesel locomotives annually. A locomotive lifespan of 40 years is assumed (Spielmann et al., 2007). Goods wagon production and maintenance are described in the individual global datasets. Goods wagon demand per metric ton.km is calculated from the number of goods wagons (Indian Railways, 2017a), the percentage of diesel gross metric ton.kms due to freight rail (52%) (Indian Railways, 2017b) and the total metric ton.kms of freight moved annually (Indian Railways, 2017a). A goods wagon lifespan of 40 years is assumed (Spielmann et al., 2007). The construction, operation, maintenance and disposal of railway track is described in the global dataset. Demand for railway track per metric ton.km is calculated from the total length of two-way railway track (Indian Railways, 2017a) and the metric ton.kms of freight moved by diesel and electric locomotives annually (Indian Railways, 2017c).
References:
Indian Railways (2017a) Annual Report Accounts - Statistical Summary 2017. Indian Railways. Available at: http://www.indianrailways.gov.in/railwayboard/uploads/directorate/stat_…
Indian Railways (2017b) Integrated Report 2016/2017 - Statistical Statement 16: Tonne kilometrage pertaining to steam, diesel and electric locomotives for 2015-16 and 2016-17. Indian Railways. Available at: http://www.indianrailways.gov.in/railwayboard/uploads/directorate/stat_…; Indian Railways (2017c) Integrated Report 2016/2017 - Statistical Statement 19. Indian Railways. Available at: http://www.indianrailways.gov.in/railwayboard/uploads/directorate/stat_…; Indian Railways (2017d) Integrated Report 2016/2017 - Statistics Statement 27. Indian Railways. Available at: http://www.indianrailways.gov.in/railwayboard/uploads/directorate/stat_….; Indian Railwasy (2017e) Integrated Report 2016/2017 - Statistics Statement 17. Indian Railways. Available at: http://www.indianrailways.gov.in/railwayboard/uploads/directorate/stat_…;
Spielmann, M., Bauer, C., Dones, R. & Tuchschmid, M. (2007) Transport Services Data v2.0, ecoinvent association, Zurich, Switzerland.;
EcoTransIT (2016) Ecological Transport Information Tool for Worldwide Transports - Methodology and Data Update
Undefined unit processes (UPRs) are the unlinked, multi-product activity datasets that form the basis for all of the system models available in the ecoinvent database. This is the way the datasets are obtained and entered into the database by the data providers. These activity datasets are useful for investigating the environmental impacts of a specific activity (gate-to-gate), without regard to its upstream or downstream impacts.