Advertisement

The International Journal of Life Cycle Assessment

, Volume 21, Issue 10, pp 1425–1437 | Cite as

Life cycle assessment of ocean energy technologies

  • Andreas Uihlein
Open Access
LCA FOR ENERGY SYSTEMS AND FOOD PRODUCTS

Abstract

Purpose

Oceans offer a vast amount of renewable energy. Tidal and wave energy devices are currently the most advanced conduits of ocean energy. To date, only a few life cycle assessments for ocean energy have been carried out for ocean energy. This study analyses ocean energy devices, including all technologies currently being proposed, in order to gain a better understanding of their environmental impacts and explore how they can contribute to a more sustainable energy supply.

Methods

The study followed the methodology of life cycle assessment including all life cycle steps from cradle to grave. The various types of device were assessed, on the basis of a functional unit of 1 kWh of electricity delivered to the grid. The impact categories investigated were based on the ILCD recommendations. The life cycle models were set up using detailed technical information on the components and structure of around 180 ocean energy devices from an in-house database.

Results and discussion

The design of ocean energy devices still varies considerably, and their weight ranges from 190 to 1270 t, depending on device type. Environmental impacts are closely linked to material inputs and are caused mainly by mooring and foundations and structural components, while impacts from assembly, installation and use are insignificant for all device types. Total greenhouse gas emissions of ocean energy devices range from about 15 to 105 g CO2-eq. kWh−1. Average global warming potential for all device types is 53 ± 29 g CO2-eq. kWh−1. The results of this study are comparable with those of other studies and confirm that the environmental impacts of ocean energy devices are comparable with those of other renewable technologies and can contribute to a more sustainable energy supply.

Conclusions

Ocean energy devices are still at an early stage of development compared with other renewable energy technologies. Their environmental impacts can be further reduced by technology improvements already being pursued by developers (e.g. increased efficiency and reliability). Future life cycle assessment studies should assess whole ocean energy arrays or ocean energy farms.

Keywords

Device type Horizontal axis turbine Ocean energy Point absorber Tidal energy Wave energy 

1 Introduction

The world’s oceans and seas are an abundant source of various forms of renewable energy. According to Falcão (2010) and Esteban and Leary (2012), six types of ocean energy can be distinguished: ocean wave, tidal range, tidal current, ocean current, ocean thermal energy and salinity gradient. In this paper, we focus on ocean wave and tidal current, which represent a potentially significant source of electricity in Europe (Magagna and Uihlein 2015). The corresponding energy industries have made considerable progress in recent years but are still at an early stage of development (Magagna and Uihlein 2015). A number of technologies are nearing the pre-commercial array demonstration stage, and others are being deployed in full-scale prototypes in real-sea environments (Magagna and Uihlein 2015).

As a form of renewable energy, ocean energy can contribute to a more sustainable energy supply, but it is not environmentally friendly per se. The activities involved in the manufacture, operation, maintenance and decommissioning of ocean energy devices will have various effects on the environment. However, only a few life cycle assessments (LCAs) of individual wave and tidal energy converters have been performed to date, with a main focus on devices at an advanced stage of development (Magagna and Uihlein 2015). Most studies (e.g. Parker et al. 2007; Douglas et al. 2008; Walker and Howell 2011) have looked only at energy and carbon as impact categories. According to Uihlein and Magagna (2015), good quality studies are lacking, especially for tidal current, ocean thermal energy and salinity gradient devices, and further LCA studies are needed to produce more estimates for all ocean energy technologies. For a number of wave energy device types, such as point absorbers and attenuators (the most common types), there are no LCA studies at all.

The European Commission’s Joint Research Centre (JRC) has developed an ocean energy database which contains detailed technical information on 186 wave and tidal energy devices that have been tested or deployed in real-water conditions (Uihlein et al. 2015). In this paper, we assess the environmental impacts of eight types of wave energy and seven types of tidal energy devices on the basis of information in the JRC database. The remainder of the paper is structured as follows: In Section 2, we present our methodology, including goal and scope definition, functional unit and system boundaries. Section 3 gives an overview of the data, information and assumptions used to establish the LCA model. Section 4 sets out the results. Discussions and conclusions can be found in Section 5.

2 Methods

2.1 Goal and scope definition

The goal of the study is to assess the environmental impacts of various ocean energy devices producing electricity and delivering it to the European electricity network. The LCA is performed at aggregate level for tidal energy and wave energy device types, rather than on individual devices at a specific site. The study will help to identify variations between ocean energy device types with respect to environmental impacts, to identify the most important life cycle stages of ocean energy devices in terms of environmental impacts and to understand differences between wave and tidal devices.

2.2 Functional unit and system boundaries

The functional unit of the study is 1 kWh of electricity delivered to the European electricity network. The LCA encompasses all life cycle steps ‘from cradle to grave’, including device assembly, installation, use and end of life, as recommended in Raventos et al. (2010). Apart from the device itself (Section 3.1), it also covers mooring and foundations and the cable connection to the grid (Section 3.2). The study assumes deployment in Europe but takes account of worldwide upstream and downstream emissions and resource inputs (Section 2.3). Assumed device lifetime is 20 years. The life cycle of an ocean energy device is shown schematically in Fig. 1.
Fig. 1

Schematic life cycle of an ocean energy device. Pink: life cycle step, blue: component, green: sub-component

2.3 Life cycle impact assessment and interpretation

The life cycle impact assessment was performed at midpoint level and follows the recommendation in Hauschild et al. (2012). All impact categories rated levels II and III in Hauschild et al. (2012) have been included in this study (Table 1).
Table 1

Life cycle impact assessment methods used in this study

Impact category

Short name

LCIA method

Indicator

Unit

Climate change

Global warming

IPCC baseline model

Global warming potential

kg CO2 eq.

Acidification

Acidification

Accumulated exceedance

Accumulated exceedance

Mole of H+ eq.

Ozone depletion

Ozone depletion

WMO model

Ozone depletion potential

kg CFC-11 eq.

Particulate matter/respiratory inorganics

Particulate matter

RiskPoll model

Fine particles

kg PM2.5 eq.

Ionising radiation, human health

Ionising radiation

Human health effect model

Human exposure

kg U235 eq.

Human toxicity, cancer effects

Human tox. cancer

USEtox model

Comparative toxic units

CTUh

Human toxicity, non-cancer effects

Human tox. non-cancer

USEtox model

Comparative toxic units

CTUh

Photochemical ozone formation

Summer smog

LOTOS-EUROS model

Ozone concentration increase

kg NMVOC

Freshwater eutrophication

Freshwater eutroph.

EUTREND model

Nutrients reaching end compartment

kg P eq.

Marine eutrophication

Marine eutroph.

EUTREND model

Nutrients reaching end compartment

kg N eq.

Terrestrial eutrophication

Terrestrial eutroph.

Accumulated exceedance

Accumulated exceedance

kg N eq.

Freshwater ecotoxicity

Freshwater ecotox.

USEtox model

Comparative toxic units

CTUh

Resource depletion, fossil and mineral

Resource depletion

CML2002 reserve based

Scarcity

kg Sb eq.

3 Life cycle inventory data

The GaBi v6.4 LCA software was used to model the system (Eyerer 1996; Thinkstep 2015a). Most of the primary data used stems from the JRC ocean energy database, while secondary data has mainly been retrieved from the GaBi professional database (Thinkstep 2015b). Below, we give a detailed description of the life cycle inventory and data sources used for modelling.

The JRC database includes information on tidal and wave energy devices that have been tested or deployed in real-water conditions. In addition, it contains information on tidal and wave energy projects in which such devices were used (Uihlein et al. 2015). In total, the database covers 83 tidal devices from 36 developers and 103 wave devices from 50 developers. These were all released after 1995, over 75 % after 2007 and over 50 % after 2010. They can be classified into seven tidal and eight wave energy device types (Magagna and Uihlein 2015). Figures 2 and 3 show a breakdown of the devices according to type. For some types (e.g. Archimedes screw, overtopping device), not many devices have been tested in real-water conditions, while others can be found more often: for example, the database contains 49 horizontal and 7 vertical axis turbines (tidal energy devices), 53 point absorbers and 16 oscillating wave surge converters (wave energy devices). For tidal energy converters, a design consensus seems to emerge in favour of horizontal axis turbines (Magagna and Uihlein 2015).
Fig. 2

Number of tidal energy devices in the database according to device type

Fig. 3

Number of wave energy devices in the database according to device type

3.1 Device-specific data

At device level, the database hosts technical information on structural components and sub-components, such as numbers, weight, dimensions and materials. In addition, it contains information such as device type and developer, power rating, release year, technology readiness level and technical information (e.g. rotor speeds, blade tip speeds, pitch angles, freeboard). The type of technical information and the parameters for structural components are shown in Table A1 (Electronic supplementary material).

3.1.1 Structural components

Device types differ considerably in terms of design and structural components. Some components are found in certain device types only and are not applicable or not used for others. Figure 4 shows an example of the structural components of tidal devices in the database according to device type. The most common structural component is a rotor, as these are used in the most common device types (horizontal axis turbines, vertical axis turbines and enclosed-tip devices). Some components, such as pods or ballast, are used more rarely.
Fig. 4

Structural components of tidal devices in the database

In many cases, data gaps exist in the database because information was unavailable or not disclosed by a developer for reasons of confidentiality. Various assumptions and estimates were made in order to fill the gaps (Table C1, Electronic supplementary material). In general, component mass was estimated on the basis of dimensions and average database values, and it was assumed that the most common material type was used in each case. For horizontal axis turbines and point absorbers, for example, about 90 % of the input parameters for calculating the mass of the structural components had to be based on average data. More importantly, however, we performed sensitivity analyses to assess the influence of these uncertainties and identified the most significant parameters determining the LCA results (Section 4.3).

3.1.2 Power take-off and related components

We also retrieved from the database information on power take-off (PTO) and related components, including data on turbine, shaft, gearbox, generator, control systems, frequency converter and auxiliary systems. The type of technical information and the PTO parameters are shown in Table A2 (Electronic supplementary material). Data gaps were filled in the same way as for structural components (Table C2, Electronic supplementary material).

3.2 Project-specific data

The type of mooring and foundation used for individual devices and the electrical connection, installation and maintenance depend on the individual project in which the device is deployed.

3.2.1 Mooring and foundations

Of the types of mooring and foundation used for the projects in the database (see Table B1, Electronic supplementary material), foundations were by far the most used, followed by moorings and anchors. Mooring and foundation information was used where available. If devices had been deployed in several projects, we used the mooring and foundation information from the most recent project (assuming that commercial deployment equates to more realistic conditions of use). For devices for which there was no information, we calculated and assumed the average of all mooring and foundations used in projects involving the device type in question (Table C3, Electronic supplementary material).

3.2.2 Electrical connection

Not all the projects in the database were grid connected. The electrical connection was modelled using three parts: cable, connector and hub (Table B1, Electronic supplementary material). We assumed a 33-kV AC transmission cable (Lopez et al. 2010) with an assumed weight of 20 kg/m (Anonymous 2011). Electrical losses from the connection were not considered in this study. Cable length was retrieved from the database; if it was unavailable, we assumed the average value (2980 m). For connector and hub, we assumed a weight of 5000. No substations were included in this study.

In some cases, additional electricity networks have to be built and the existing grid has to be upgraded or reinforced when ocean arrays are deployed in remote areas with weaker grids (Magagna and Uihlein 2015). Such upgrades have not been included in this study.

3.2.3 Installation and maintenance

The database includes records of maintenance and installation operations carried out in the course of ocean energy projects. These include duration and vessel types used. If no information was available, we used average values (26 h for installation and 100 h maintenance per year). We assumed that 70 % of the operations are executed using a vessel and 30 % using a barge.

As deployment of ocean energy devices has been limited to date, the database provides no information on replacement parts and replacement intervals. Following the example of previous studies (Parker et al. 2007; Thomson et al. 2011; Dalton et al. 2014), we assumed that no parts have to be replaced.

3.3 Power output

Electricity production was calculated using the nominal capacity of the devices. Reported capacities range from 0.07 to 3000 kW, with the majority of devices having a nominal capacity between 500 and 1000 kW (Fig. 5).
Fig. 5

Nominal capacity of ocean energy devices in the database

We assumed capacity factors of 34 % for tidal and 20 % for wave energy devices, which is in the range of values given by Esteban and Leary (2012).

3.4 LCI data and assumptions for upstream and downstream processes

3.4.1 Upstream datasets—materials and energy

For materials and energy carriers used to produce structural and PTO components, electrical connections and mooring and foundations, we used secondary data from databases, mainly from Thinkstep (2015b) (Table 2). We performed a sensitivity analysis as regards the type of steel assumed in the model (Section 4.3).
Table 2

Datasets used for materials and energy carriers

Material

Dataset used

Source

Steel

RER: stainless steel Quarto plate (316)

Thinkstep (2015b)

Plastic

DE: polycarbonate granulate (PC)

Thinkstep (2015b)

Composites

DE: sheet moulding compound resin mat (SMC)

Thinkstep (2015b)

Aluminium

EU-27: aluminium ingot mix

Thinkstep (2015b)

Water

EU-27: tap water

Thinkstep (2015b)

Copper

DE: copper mix (99.999 % from electrolysis)

Thinkstep (2015b)

Electronics

Modelled according to electronic component

Heck (2007)

Lead

EU-27: lead primary and secondary mix ILA

Thinkstep (2015b)

PVC

RER: polyvinylchloride injection moulding part

Thinkstep (2015b)

PE pipe

RER: polyethylene pipe (PE-HD)

Thinkstep (2015b)

Tin

RER: tin, at regional storage

Ecoinvent (2007)

Platinum

RER: platinum, at regional storage

Ecoinvent (2007)

Nickel

GLO: nickel, 99.5 %, at plant

Ecoinvent (2007)

Concrete

CN: prefabricated concrete part slab, 40 cm

Thinkstep (2015b)

Electricity

EU-27: electricity grid mix

Thinkstep (2015b)

Heat

EU-27: thermal energy from natural gas

Thinkstep (2015b)

Light fuel oil

EU-27: light fuel oil at refinery

Thinkstep (2015b)

3.4.2 Assembly and manufacturing

We modelled device assembly assuming an electricity input of approximately 1.5 kWh/kg with an assumed electrical energy/heat ratio of 2:1 (Sullivan et al. 2013)1 for the assembly of structural components, PTO components, mooring and foundations and the electrical connection.

Manufacturing processes for structural components (e.g. plastics injection moulding, steel sheet deep drawing, aluminium cast machining) were modelled using GaBi datasets (Thinkstep 2015b).

3.4.3 Transports

All transport was assumed to be by lorry (EU-27: articulated lorry transport). We assumed a distance of 500 km for the transport of structural and PTO components to the point of assembly and of the material for electrical connections and mooring and foundations to the harbour from which installation is carried out.

We assumed a distance of 1000 km for the transport of sub-components to the point where the components are assembled (e.g. rotor to the point of assembly of the structural components) and of upstream materials from the place of production to the place of sub-component manufacturing (e.g. transport of steel to the location where the rotor is built).

We did not include transport of the fully assembled device to the harbour since we assumed that it would be assembled at the harbour and transport distance would be negligible. We included transport of 1000 km to the final disposal site (landfill, incineration) after use.

The results show that the environmental impacts of transport are negligible as compared with other life cycle steps (Section 4.2) so the very generic assumptions on transport distances and means are justified.

3.4.4 Installation and maintenance

For installation and maintenance operations, the use of vessels and barges was modelled as described in Section 3.2.3. We used the ‘GLO: bulk commodity carrier’ and ‘EU-27: barge incl. fuel’ datasets (Thinkstep 2015b).

3.4.5 End of life

For modelling the end of life (EOL) of the ocean energy devices, we assumed no environmental impacts from disassembly processes. We assumed three different EOL routes for materials used—recycling, incineration and landfilling (Table 3) taking the proportional breakdown from Zimmermann (2012).
Table 3

Assumptions and datasets for EOL

Material

Recycling (%)

Incineration (%)

Landfill (%)

Ferrous metals

90

0

10

Non-ferrous metals

95

0

5

Plastics

80

20

0

Composites

0

100

0

Concrete

85

0

15

Sanda

0

0

0

Electronics

0

100

0

Source: Zimmermann (2012)

aUsed only as ballast, assumed to remain on the seabed after use

Since no one has any real experience of disposal of ocean energy devices, this can be considered a rough estimate. For the majority of materials (e.g. steel and other metals), the recycling quota could probably be higher. We applied no credits for recycling. For landfilling and incineration, we used the relevant datasets from Thinkstep (2015b). A credit was applied for energy recovery from incineration and recycling, using the datasets from Table 2 for electricity and heat.

4 Results

4.1 Mass flows

Figure 6 shows the average volume of material used to produce the device. Device weights vary considerably between device types: from about 190,000 kg for enclosed-tip devices to 1,270,000 kg for overtopping devices. On average, tidal device types have a lower mass than wave energy devices.
Fig. 6

Amount of materials for the production of ocean energy devices

For most device types, mooring and foundations contribute most to total device weight. For 12 types, the proportion is over 50 % and it can reach 86 % in the case of the vertical axis turbine. Structural components are also important, making up an average 26 % of the total weight. PTO components account for a relatively minor proportion (less than 10 % for 10 device types), but this can reach 36 % in the case of attenuators. The electrical connection contributes less than 10 % in all device types except oscillating hydrofoils.

We also calculated the specific mass of device types in terms of kilograms per kilowatt nominal capacity. Here, the difference between tidal and wave energy devices is small (Fig. 7). Specific weights range from about 470 kg kW−1 for enclosed-tip to about 3860 kg kW−1 for rotating mass devices. Interestingly, the relative weight contribution of structural components is much higher in wave energy devices than in tidal energy devices (38 and 12 %, respectively).
Fig. 7

Amount of materials for the production of ocean energy devices

As regards the mass of material used, we found that steel predominates. For all device types except overtopping devices, steel accounts for over 45 % of total weight (Table 4). Concrete is an important material in overtopping devices (about 55 %) and makes up between about 20 and 30 % of the weight of eight device types. Proportions of other metals (aluminium, iron, copper) and plastics can go up to 13 % but in general are less than 10 %. Electronics make up no more than 4 %.
Table 4

Share of material used to produce ocean energy device in % of total weight

Device type

Steel

Other metals

Electronics

Plasticsa

Concrete

Sand

Water

Horizontal axis turbine

50.24

6.38

0.86

6.98

32.69

0.78

2.07

Vertical axis turbine

88.40

5.52

1.47

4.60

0.00

0.00

0.00

Oscillating hydrofoil

76.99

9.70

1.81

11.21

0.30

0.00

0.00

Enclosed tips

77.82

8.02

2.85

10.86

0.45

0.00

0.00

Archimedes screw

54.52

12.52

0.34

7.59

25.03

0.00

0.00

Tidal kite

64.28

2.62

1.54

5.59

25.98

0.00

0.00

Other tidal

64.49

3.28

0.57

7.14

24.53

0.00

0.00

Attenuator

46.20

7.04

1.03

6.56

6.30

8.96

23.90

Point absorber

50.36

3.80

0.94

11.98

13.60

5.27

14.05

Oscillating wave surge

55.01

7.93

3.03

12.97

8.33

3.47

9.25

Oscillating water column

60.62

3.14

0.59

4.01

31.63

0.00

0.00

Overtopping

36.73

0.93

0.15

0.92

55.48

1.58

4.21

Submerged pressure differential

63.11

3.37

0.93

11.22

21.29

0.02

0.05

Rotating mass

46.11

2.81

0.34

4.87

20.56

6.90

18.40

Other wave

65.51

3.63

0.54

4.76

25.56

0.00

0.00

aIncludes also composites

4.2 LCA results: base case

A wealth of LCA results was obtained from the model calculations. We will look first at the environmental impacts of the most prevalent device types, i.e. horizontal axis turbine for tidal energy and point absorber for wave energy devices.

The environmental impacts of horizontal axis turbines are shown in Fig. 8. The individual components are displayed separately, while the processes for device assembly and installation have been grouped together. For almost all impact categories, mooring and foundations contribute the most environmental impacts. Depending on impact category, the electrical connection and PTO components account for significant proportions (over 25 %). Structural components and end of life contribute very little, while assembly, installation and use do not produce significant impacts.
Fig. 8

Environmental impacts of horizontal axis turbines according to life cycle step

Figure 9 shows the (somewhat different) results for point absorbers. Clearly, structural components dominate the environmental impacts; they account for over 40 % in all but two impact categories. Next, mooring and foundations but also PTO components (in two impact categories) play a significant role. Again, the impacts from assembly, installation and use are not significant.
Fig. 9

Environmental impacts of point absorber according to life cycle step

The LCA results for these two device types closely reflect the relative contributions of the various components to the overall weight of the device as shown in Fig. 7. We analysed the correlation between the volume of material used per component (structural components, PTO components, electrical connection, mooring and foundations) and the environmental impacts per component (including end of life). As shown in Table 5, environmental impacts are closely related to mass flows. For almost all impact categories except ionising radiation and freshwater eutrophication, there are positive correlations between component mass and the environmental impacts. Correlation coefficients are greater than 60 % for the majority of impact categories and ocean energy devices.
Table 5

Correlation between environmental impacts and device mass per life cycle step

Impact category

HAT

VAT

OHF

ETP

AQS

TKT

TOT

ATT

PTA

OWS

OWC

OVT

SPD

RMA

WOT

Global warming

0.99

1.00

0.98

0.93

1.00

0.98

1.00

0.68

0.97

0.80

0.99

0.99

0.98

0.94

1.00

Acidification

0.99

1.00

0.98

0.99

1.00

1.00

1.00

0.60

0.98

0.87

1.00

0.98

1.00

0.89

1.00

Ozone depletion

0.99

0.99

0.97

0.99

1.00

1.00

1.00

0.57

0.98

0.88

1.00

0.97

1.00

0.87

1.00

Particulate matter

1.00

1.00

1.00

0.99

1.00

1.00

1.00

0.60

0.99

0.88

1.00

0.98

1.00

0.90

1.00

Ionising radiation

−0.24

−0.18

−0.11

−0.20

0.13

−0.25

−0.20

0.41

−0.14

0.00

−0.25

0.36

−0.37

−0.30

−0.09

Human tox. cancer

0.99

1.00

1.00

0.98

1.00

1.00

1.00

0.58

0.98

0.83

1.00

0.98

1.00

0.89

1.00

Human tox. non-cancer

1.00

1.00

0.99

0.99

1.00

1.00

1.00

0.57

0.98

0.87

1.00

0.98

1.00

0.88

1.00

Summer smog

1.00

1.00

0.99

0.98

1.00

1.00

1.00

0.62

0.98

0.86

1.00

0.98

1.00

0.90

1.00

Freshwater eutroph.

−0.13

−0.02

−0.07

−0.16

0.31

−0.18

0.12

0.53

0.46

0.22

0.06

0.78

0.01

0.47

0.24

Marine eutroph.

1.00

1.00

1.00

0.99

1.00

1.00

1.00

0.96

1.00

1.00

1.00

1.00

0.99

0.99

1.00

Terrestrial eutroph.

1.00

1.00

1.00

0.99

1.00

1.00

1.00

0.70

0.99

0.90

1.00

0.99

1.00

0.93

1.00

Freshwater ecotox.

0.99

1.00

0.99

0.96

0.99

0.99

1.00

0.52

0.95

0.71

0.99

0.97

0.99

0.86

1.00

Resource depletion

0.34

0.76

0.33

0.76

0.57

0.82

0.82

0.20

0.88

0.33

0.80

0.84

0.83

0.63

0.82

HAT horizontal axis turbine; VAT vertical axis turbine; OHF oscillating hydrofoil; ETP enclosed tips; AQS archimedes screw; TKT tidal kite; TOT other tidal; ATT attenuator; PTA point absorber; OWS oscillating wave surge; OWC oscillating water column; OVT overtopping; SPD submerged pressure differential; RMA rotating mass; WOT other wave

Freshwater eutrophication impacts are dominated by some materials that have disproportionately high specific impacts: polycarbonate, copper (used for cables in the electrical connection) and stainless steel, which is used mainly in mooring and foundations (e.g. piles). High ionising radiation impacts stem from the electricity demand of manufacturing processes (e.g. production of electronics, assembly process). Resource depletion impacts are linked mainly to copper and steel.

We also quantified the proportion of environmental impacts stemming from transport processes. For both horizontal axis turbines and point absorbers, this is not significant. For no impact category do the impacts from transport exceed 0.2 % of total impacts.

Since ocean energy is considered by many as a technology that will contribute to a low-carbon energy system, we looked in detail at the LCA results for global warming. Figure 10 shows the global warming potential (GWP) of device types according to life cycle step. Total greenhouse gas (GHG) emissions range from about 15 g CO2-eq. kWh−1 for enclosed-tip devices to about 105 g CO2-eq. kWh−1 for point absorber and rotating mass devices. The average GWP for all device types is 53 ± 29 g CO2-eq. kWh−1.
Fig. 10

Global warming potential according to life cycle step

For almost all device types, mooring and foundations contribute most to GHG emissions (over 40 % for 12 out of 15 device types). With attenuator and oscillating wave surge devices, the PTO components account for the proportion of GHG emissions; with point absorbers, the structural components are responsible for the majority. Electrical connections are not a major source of GHGs; in general, they contribute less than 10 % and are responsible for a significant proportion only in the case of oscillating hydrofoils. The proportions for other life cycle stages (assembly, installation, use and end of life) are almost negligible (2.6 % and less) for all device types.

4.3 LCA results of sensitivity analysis

We performed a sensitivity analysis for one tidal (horizontal axis turbine) and one wave energy device (point absorber) in order to identify the model parameters that have the biggest influence on environmental impacts. Each parameter of the model was varied by ±50 % and the resulting variation of the environmental impacts was calculated for each impact category.

In total, 15 parameters have a big influence on the results, i.e. varying the parameter by ±50 % led to a change of over 5 % in at least one environmental impact category (Table 6). Depending on device type, the weight of various sub-components (e.g. nacelle, frequency converter, gravity base) has a great influence on the results. Naturally, parameters affecting the use phase have a significant influence, e.g. a 50 % decrease in lifetime will increase environmental impact by about 98 to 100 %.
Table 6

Range of changes in environmental impacts across impact categories for parameters; the model shows greatest sensitivity in percentage related to a change of the parameter by 50 %

Life cycle step

Component

Parameter

Horizontal axis turbine

Point absorber

Assembly

Structural component

Weight nacelle

0.75–5.60

n.a.

Weight float

n.a.

1.44–14.82

Weight other

n.a.

3.60–20.39

PTO component

Weight frequency converter

0.26–9.90

0.18–6.53

Weight control system

n.a.

0.22–7.71

Weight auxiliaries

0.48–18.29

0.57–20.11

Installation

Mooring and foundations

Weight of lattice support tower

0.86–8.98

n.a.

Weight of pontoon

n.a.

0.55–6.24

Weight of gravity base

2.16–18.77

0.57–5.09

Weight of pile

1.18–12.40

n.a.

Electrical connection

Weight of cable

0.00–10.11

n.a.

Weight of connector

0.06–8.85

n.a.

Use

n.a.

Nominal capacity

100.00

100.00

Capacity factor

100.00

100.00

Lifetime

98.87–100.00

98.49–100.00

Assembly, installation and EOL

Steel

Carbon steela

1.00–53.00

1.00–54.00

n.a. not applicable

aIn the case of the sensitivity analysis for steel, it was assumed that 100 % of stainless steel (see Table 2) is replaced with finished rolled coil steel

A sensitivity analysis was also carried out for the type of steel modelled, since the use of steel contributes significantly to the LCA results. In the base case, it was assumed that stainless steel is used in all parts of the device (Table 2). The alternative considered in the sensitivity analysis is finished cold-rolled coil steel (Thinkstep 2015b). This carbon steel shows lower environmental impacts per kilogram (1 to 85 % less than the stainless steel modelled, depending on the impact category). The LCA results for carbon steel for the horizontal axis turbine and the point absorber showed that the potential environmental impacts would be much lower (by 47 to 99 % for the horizontal axis turbine and 46 to 99 % for the point absorber, depending on impact category). Thus, the assumptions for the base case are very much a simplification and might be considered as representing a worst-case scenario.

4.4 LCA results: scenarios

We drew up a number of scenarios (Table 7) to model potential improvements in life cycle environmental impact, reflecting the importance of individual parameters or environmental hot spots (see Section 4.3) and the ways in which technology developers can change such device- and project-specific parameters. The horizontal axis turbine was again chosen to exemplify results for tidal energy devices and the point absorber for wave energy devices. We modelled the scenarios shown in Table 7. The bars in Fig. 11 give the range of environmental impacts as compared with the baseline scenario over all impact categories. One must keep in mind that the results are indicative and to some extent hypothetical. For example, higher capacity factors might be achieved only by changes in device design that also affect environmental impacts from manufacturing, which could offset some of the potential environmental gains. Such effects have not been taken into account in this study but represent an interesting field to pursue in future assessments.
Table 7

Scenarios modelled

Scenario

Description

Assumptions

Increased efficiency

Higher capacity factor

CF of 45 % instead of 34 % for tidal and 36 % instead of 20 % for wave

Increased durability

Higher lifetime

Lifetime of 30 years instead of 20 years

Other mooring and foundations

Using mooring lines instead of foundations

No piles, pontoon and support towers used for mooring but only anchors, mooring lines and gravity base. Values for average tidal/wave device used

Moving further offshore

Higher ocean energy resources but longer cable connection

Average distance from shore is about 2120 m for horizontal axis turbines and 260 m for point absorbers. An increased distance of 10 km is assumed in the scenario, allowing for reaching maximum capacity factors (see above, 45 and 36 % for tidal and wave energy devices, respectively)

Fig. 11

Range of environmental impacts over all impact categories relative to baseline. a Horizontal axis turbines. b Point absorbers

If technology developers could increase capacity factors to the maximum values stated in Carlsson (2014), the environmental impacts of horizontal axis turbines and point absorbers could be reduced to 76 and 56 %, respectively, for all impact categories (Fig. 11). Similarly, a 50 % longer device lifetime could reduce the life cycle environmental impacts of both devices by 33 % (for all impact categories), given that almost all impacts stem from assembly, installation and end of life and almost none occur during the use phase (Figs. 9 and 10).

The scenario for a change in mooring and foundations suggests that environmental impacts can be reduced for all impact categories. Reductions range from 6 to 58 % for horizontal axis turbines and from 1 to 14 % for point absorbers. The reduction potential for tidal energy devices is higher since they use heavier foundation systems (e.g. gravity bases) than wave energy devices. In the calculations, we did not take into account whether local (wave/tidal current climate) and device-specific circumstances allowed for a change of mooring and foundation system. Still, considering the large contribution that mooring and foundations make to environmental impacts, even small improvements will help to reduce overall impact.

The fourth scenario analysed the effects of moving devices further offshore, allowing for the use of greater ocean energy resources. This increases efficiency, but the gains in terms of environmental impact are offset by the longer cable connections to be installed in the sea. For point absorbers, there are still net environmental benefits for all impact categories, mainly thanks to high efficiency gains (Fig. 11). For horizontal axis turbines, benefits can be seen for all environmental impacts except freshwater eutrophication and freshwater ecotoxicity. Assumed increases in efficiency (capacity factor between 34 and 45 %) do not counterbalance additional impacts from the cable connection.

Another scenario we considered was the use of lightweight materials such as composites and aluminium. This could involve greater specific environmental impacts per kilogram of material but also a possible reduction in impacts due to the lower mass of material used. However, there are a number of uncertainties around this scenario, e.g. how much steel might be replaced and the extent to which the structural weight could be reduced. Also, the ‘lightweighting’ of ocean energy devices does not currently seem possible, for economic reasons. Due to the uncertainties, the results of this scenario cannot be considered robust enough for a solid conclusion; this might be analysed in a further study.

5 Discussion and conclusions

The results of this analysis have shown that there is still considerable divergence in design options for ocean energy (especially wave energy) devices, as also stated in Magagna and Uihlein (2015). There are great variations in weight/power ratios, with specific device weights varying by almost an order of magnitude (from about 470 to 3860 kg/kW). Compared with other renewable energy technologies, ocean energy devices seem to demand quite a high input of materials per installed capacity. For example, according to Krauter (2006), photovoltaic systems weigh 330 to 360 kg/kW and wind turbines about 340 to 770 kg/kW (Guezuraga et al. 2012). Of course, the material intensity of ocean energy devices can be reduced when they are deployed in arrays, since they can then share some components (e.g. cable connection to the shore, foundation systems). The high power density of tidal current or waves, for example, which in principle allows high efficiencies, also places high demands on devices in terms of reliability and survivability and thus in turn on material inputs.

As mentioned above, most LCAs on ocean energy have focused on energy use and carbon dioxide emissions, to the exclusion of other environmental impact categories. The results of the LCA for the base cases for GHG emissions are in line with the results from previous studies (Table 8). Greater deviations were found for other impact categories, such as eutrophication, possibly, because our impact assessment models differed from those used in previous studies.
Table 8

Life cycle impact assessment results from literature and this study

Device type

Impact category

Unit

Literature

This study

Attenuator

Global warming

g CO2-eq./kWh

22.8a–29.8b

43.7

Ozone depletion

g CFC-11 eq./kWh

2.3b

1.8

Freshwater eutroph.

mg P eq./kWh

9.84b

0.16

Marine eutroph.

mg N eq./kWh

21.0b

10.0

Oscillating wave surge

Global warming

g CO2-eq./kWh

25c

64

Point absorber

Global warming

g CO2-eq./kWh

39–126d

104.5

Ozone depletion

g CFC-11 eq./kWh

1.48–4.58d

4.2

Horizontal axis turbine

Global warming

g CO2-eq./kWh

15–20e

23.1

aParker et al. (2007)

bThomson et al. (2011)

cWalker and Howell (2011)

dDahlsten (2009)

eDouglas et al. (2008)

We concur with all previous studies that contain and disclose detailed information on the spread of impacts across life cycle phases (e.g. Walker and Howell 2011) in finding that the main environmental impacts from ocean energy devices from an LCA perspective are due to materials use, while installation, maintenance and operation do not show significant impacts.

Comparison with other renewables showed that energy and carbon intensity levels would be similar to those of large wind turbine installations (Walker and Howell 2011). For example, average GHG emissions for electricity production from other renewables are about 34 and 50 g CO2-eq./kWh for wind and solar PV, respectively (Nugent and Sovacool 2014), 20–80 g CO2-eq./kWh for concentrated solar power (Burkhardt et al. 2012) and 40–80 g CO2-eq./kWh for geothermal (Frick et al. 2010). Ocean energy devices thus offer the potential to limit environmental impacts to levels associated with other renewable technologies, especially as regards global warming. Certainly, they can contribute to a more sustainable energy supply as compared with fossil fuels (Lewis et al. 2011).

Environmental impacts from ocean energy devices can be further reduced, as the scenario calculations have shown (Section 4.3). Developers are already focusing on improvements such as increased efficiency, durability and reliability and better mooring systems, in order to advance ocean energy technologies and further reduce costs (Magagna and Uihlein 2015). One approach to increasing efficiency and reducing environmental impacts is to move further offshore in order to deploy devices in areas with greater resources (e.g. higher wave energy). However, environmental benefits could be offset by the longer cable lengths needed, so this option needs to be examined carefully.

In the future, ocean energy devices will also be installed in arrays or even ocean energy farms. This will clearly reduce the environmental impacts per kilowatt-hour of electricity produced, since some components (e.g. cable, electrical hubs, substation) could be shared. Future LCAs should thus focus on whole arrays of ocean energy devices. Since ocean energy resources are variable (although very predictable, e.g. in the case of tidal currents), studies taking into account the fluctuations in electricity production would also be very useful for assessing the environmental benefits of ocean energy.

Footnotes

  1. 1.

    Energy demand of machining, HVAC and lighting, heating and material handling according to Sullivan et al. (2013) have been included.

Notes

Compliance with ethical standards

Disclaimer

The views expressed in this paper are those of the writer only and may in no circumstances be regarded as representing an official position of the European Commission.

Supplementary material

11367_2016_1120_MOESM1_ESM.xlsx (26 kb)
ESM 1 (XLSX 26 kb)

References

  1. Anonymous (2011) Submarine cable solutions, laying and challenges. General Cable, Highland HeightsGoogle Scholar
  2. Burkhardt JJ, Heath G, Cohen E (2012) Life cycle greenhouse gas emissions of trough and tower concentrating solar power electricity generation. J Ind Ecol 16:S93–S109CrossRefGoogle Scholar
  3. Carlsson J (2014) Energy technology reference indicator (ETRI) projections for 2010–2050. Publications Office of the European Union, LuxembourgGoogle Scholar
  4. Dahlsten H (2009) Life cycle assessment of electricity from wave power. Swedish University of Agricultural SciencesGoogle Scholar
  5. Dalton G, Madden D, Daly MC (2014) Life cycle assessment of the wavestar. In: 2014 ninth international conference on ecological vehicles and renewable energies (EVER). IEEE, Monte Carlo. pp 1–9Google Scholar
  6. Douglas CA, Harrison GP, Chick JP (2008) Life cycle assessment of the Seagen marine current turbine. Proc Inst Mech Eng Part M J Eng Marit Environ 222:1–12Google Scholar
  7. Ecoinvent (2007) Ecoinvent data v2.0. Ecoinvent, DübendorfGoogle Scholar
  8. Esteban M, Leary D (2012) Current developments and future prospects of offshore wind and ocean energy. Appl Energy 90:128–136CrossRefGoogle Scholar
  9. Eyerer P (ed) (1996) Ganzheitliche Bilanzierung. Springer, BerlinGoogle Scholar
  10. Falcão AF de O (2010) Wave energy utilization: a review of the technologies. Renew Sustain Energy Rev 14:899–918CrossRefGoogle Scholar
  11. Frick S, Kaltschmitt M, Schröder G (2010) Life cycle assessment of geothermal binary power plants using enhanced low-temperature reservoirs. Energy 35:2281–2294CrossRefGoogle Scholar
  12. Guezuraga B, Zauner R, Pölz W (2012) Life cycle assessment of two different 2 MW class wind turbines. Renew Energy 37:37–44CrossRefGoogle Scholar
  13. Hauschild MZ, Goedkoop M, Guinée J et al (2012) Identifying best existing practice for characterization modeling in life cycle impact assessment. Int J Life Cycle Assess 18:683–697CrossRefGoogle Scholar
  14. Heck T (2007) Ecoinvent report no. 6-XIV. Wärme-Kraft-Kopplung. Data v2.0. Ecoinvent, VilligenGoogle Scholar
  15. Krauter SCW (2006) Solar electric power generation. Springer, HeidelbergGoogle Scholar
  16. Lewis A, Estefen S, Huckerby J et al (2011) Ocean energy. In: Edenhofer O, Pichs-Madruga R, Sokona Y et al (eds) IPCC special report on renewable energy sources and climate change mitigation. Cambridge University Press, Cambridge, pp 497–533CrossRefGoogle Scholar
  17. Lopez J, Ricci P, Villate JL, et al. (2010) Preliminary economic assessment and analysis of grid connection schemes for ocean energy arrays. In: 3rd international conference on ocean energy. BilbaoGoogle Scholar
  18. Magagna D, Uihlein A (2015) Ocean energy development in Europe: current status and future perspectives. Int J Mar Energy 11:84–104CrossRefGoogle Scholar
  19. Nugent D, Sovacool BK (2014) Assessing the lifecycle greenhouse gas emissions from solar PV and wind energy: a critical meta-survey. Energy Policy 65:229–244CrossRefGoogle Scholar
  20. Parker RPM, Harrison GP, Chick JP (2007) Energy and carbon audit of an offshore wave energy converter. Proc Inst Mech Eng Part A J Power Energy 221:1119–1130CrossRefGoogle Scholar
  21. Raventos A, Simas T, Moura A, Harrison G, Thomson C, Dhedin JF (2010) Life Cycle Assessment for marine renewables. EquiMar (Equitable Testing and Evaluation of Marine Energy Extraction Devices in terms of Performance, Cost and Environmental Impact). Deliverable D6.4.2. Grant Agreement number: 213380. http://tethys.pnnl.gov/sites/default/files/publications/EquiMar_D6.4.2.pdf
  22. Sullivan JL, Burnham A, Wang MQ (2013) Model for the part manufacturing and vehicle assembly component of the vehicle life cycle inventory. J Ind Ecol 17:143–153CrossRefGoogle Scholar
  23. Thinkstep (2015a) Gabi 6.4 LCA software. Leinfelden-EchterdingenGoogle Scholar
  24. Thinkstep (2015b) Gabi professional database, SP 27. Leinfelden-EchterdingenGoogle Scholar
  25. Thomson RC, Harrison GP, Chick JP (2011) Full life cycle assessment of a wave energy converter. In: IET conference on renewable power generation (RPG 2011). IET, Edinburgh. pp 63–63Google Scholar
  26. Uihlein A, Magagna D (2015) A review of the current state of research in the area of ocean energy. Renew Sust Energ Rev 58:1070--1081. doi: 10.1016/j.rser.2015.12.284
  27. Uihlein A, Magagna D, Raventos A, Silva M (2015) Wave and tidal energy in Europe: assessing present technologies. In: 11th European wave and tidal energy conference series. NantesGoogle Scholar
  28. Walker S, Howell R (2011) Life cycle comparison of a wave and tidal energy device. Proc Inst Mech Eng Part M J Eng Marit Environ 225:325–337CrossRefGoogle Scholar
  29. Zimmermann T (2012) Parameterized tool for site specific LCAs of wind energy converters. Int J Life Cycle Assess 18:49–60CrossRefGoogle Scholar

Copyright information

© The Author(s) 2016

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Institute for Energy and Transport, Joint Research CentreEuropean CommissionPettenThe Netherlands

Personalised recommendations