4.2. Life-Cycle Assessment of ERS and Current Fossil-Powered Truck Transport
As a result of the SLCA, the main hot spots identified were raw material extraction, production and use phases, which therefore were selected for quantification with LCA. Included processes and components are: (i) raw material extraction for roads, lorries, diesel, and road electrification; (ii) processes for turning the raw material into products; (iii) combustion of diesel, emissions from electricity generation, catenary friction, road, break, and tire wear emissions, and lorry maintenance. The other life-cycle phases were excluded from the LCA. The inventory analysis of the infrastructure utilized data from 1000 V railway systems, which use very similar components to overhead line ERS. This data was further adjusted with the help of a railway and ERS expert. For the components where there was no suitable data in Ecoinvent, simplified components were modelled (see Table 6
Market processes and system model “allocation, cut-off by classification” were used for all materials and processes [49
]. Europe was chosen as the geographical reference point. The value chain can, however, include materials and processes from other parts of the world. Four scenarios for electricity generation were applied, all based on Ecoinvent data: European mix, Nordic mix, wind-generated electricity, and a worst-case scenario that assumed coal-generated marginal electricity. The type of electricity for vehicle propulsion in the use phase is the only difference between the scenarios, thereby showing the sensitivity of the model for this key factor. Truck traffic volume was initially set to 1000 vehicles per direction and day, which corresponds to a major Swedish highway [30
]. Trucks had a gross vehicle weight of 16–32 ton, with an average load factor of 5.79 ton [50
]. Diesel trucks met Euro 6 emission limits. Diesel consumption was 0.037 L/tkm, which corresponds to 0.21 L/km (Ecoinvent 3.2 database). Electricity consumption was set to 0.17 kWh/tkm, which corresponds to the same amount of energy consumption as the diesel truck when calculating with diesel engine efficiency of 42%, electric engine efficiency of 95%, and electricity losses in the ERS of five percent. Catenary friction was estimated as 10 kg of copper per km and year, which is the same amount as for railway systems [51
]. Without full scale tests it is, however, yet uncertain whether this data is fully valid for ERS due to differences in traffic intensity, speed, and movement of the pantograph-shaped pick-up.
Comparing characterization results of ERS- and diesel-powered trucks, Figure 2
, revealed: (i) wind-powered ERS have lower environmental impact than the diesel system in 11 out of 18 impact categories; (ii) ERS powered by European electricity mix or marginal electricity have higher environmental impact in 12 and 13 out of 18 categories respectively, as compared to the current diesel system. That number is 10 for the Nordic electricity mix scenario; (iii) there are substantial differences in GHG emissions: ERS that use coal-based marginal electricity cause the highest emissions (229 g/tkm), followed by diesel (165 g/tkm), EU mix electricity (117 g/tkm), Nordic mix (41 g/tkm) and wind-generated electricity (31 g/tkm); and (iv) a closer look at ERS infrastructure reveals that most environmental impacts are tied to the three components of copper catenaries, catenary masts and road barriers. Other parts, such as converters or cables, play a minor role.
Normalization of the results shows that freshwater eutrophication, human toxicity, eco-toxicity and natural land transformation are the most relevant impact categories for the investigated systems. ERS, no matter how electricity is generated, have higher impact in the toxicity categories, which is largely due to the extensive use of copper and emissions from catenary friction. The fossil-powered system has a much higher impact on natural land transformation, mainly due to petroleum production.
A closer look at the role of different life-cycle phases for the climate change category, Figure 3
, reveals that most emissions occur in the use phase if trucks are powered by diesel, marginal electricity or EU mix electricity. If electricity is produced in a less carbon intensive way, as is the case with Nordic mix and wind-power, extraction to distribution (E–D) phases constitute the main source of CO2
e) emissions. It is, however, not the ERS infrastructure that causes high emissions in E–D phases. Instead, road and lorry production cause about 20 g CO2
e emissions per tkm, which can be compared with 1.5 g/tkm for electrification of the road with ERS.
The amount of tkm transported on ERS is a central parameter: the more goods that are transported on an ERS, the less is the share of building the infrastructure, E–D phases, for each tkm. The number of tkm is in turn dependent on the number of trucks and their average load factor. In order to evaluate if electrification of a specific road is favorable from a sustainability perspective, it is necessary to adjust the assumptions of the LCA model. Figure 4
clarifies the dependence of life-cycle environmental impact and the number of tkm transported on ERS. It shows the environmental break-even times for the different scenarios, that is, the time until the environmental impact of the road electrification is compensated by lower impact in the use phase. ReCiPe endpoint was used to get one accumulated, comparable number for environmental impacts. The marginal electricity scenario is not displayed because it has higher life-cycle environmental impact per tkm than the diesel system, hence there is no break-even.
Generally, break-even times are short if Nordic mix or wind-power generated electricity are used: assuming 1000 trucks per day, break-even is only three to four years and with 500 trucks per day that time is below 10 years. The situation is different, though, if EU mix electricity is assumed: a minimum of about 700 trucks per day is required to achieve a break-even time of 10 years, and with 1000 heavy vehicles per day, that time is seven to eight years. A break-even time shorter than five years is only possible on roads with high traffic flow of more than 1400 trucks per direction and day. From a purely GHG emission perspective, break-even times are considerably (about 70%) shorter when assuming the same amount of freight transport per day. Climate change is, however, only one of many impacts that have to be considered.