the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Nov 2024
Life Cycle Assessment of New Jersey Offshore Wind
Abstract. As offshore wind gains momentum within US renewable energy goals, New Jersey’s ambitious targets for offshore wind development represent a significant opportunity to reduce emissions and transition towards cleaner energy sources. This study presents a life cycle assessment (LCA) of a planned offshore wind farm off of New Jersey’s coast, emphasizing the implications of a domestic supply chain. Key findings show the farm is projected to produce 0.0113 kg CO2 per kWh of electricity generated, reflecting a 98 % decrease in carbon emissions compared to natural gas derived electricity. Further, when compared to carbon emissions of other renewable energy technologies, offshore wind outperforms both solar and onshore wind by 81 % and 48 %, respectively. This finding highlights offshore wind’s role in emissions reduction, as well as the importance of a domestic supply chain to mitigate transportation-related impacts. Additionally, results indicate a need to address the environmental trade-offs of offshore, as steel-intensive materials used in turbines and infrastructure contribute heavily to toxicity-related impacts. This research underscores the potential of offshore wind to reduce greenhouse gas emissions, and offers insight into the environmental dynamics of offshore wind energy in the US.
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RC1: 'Comment on wes-2024-143', Anonymous Referee #1, 23 Jan 2025
General Comments/Overall Quality
This paper provides a current perspective on potential emissions reductions of the prospective New Jersey offshore wind leases. Using a developed infrastructure modeling scenario with regional supply chains, energy grids, manufacturing ports, and turbine technical details that have been deemed essential by government agencies and peer-reviewed literature that differentiates this study from other analysis. It is a rational starting point to reference as a framework for future iterative research. However, an important remark should be made pertaining to the political, economic, and temporal constraints that may occur over the next decade or more. The impactful and relevant data are concise and consistent in styling with other peer-reviewed publications. The life cycle assessment methodology is straightforward and conventional without novel allocation or system expansion. The results highlight necessary improvements in production and manufacturing upstream that should be targeted to measurably improve emissions from offshore wind now and in the future.
Individual Scientific Questions or Issues
Line 105: It is unclear if the reference to ‘minimal uncertainty’ is based on the use of ReCiPe itself or translation between midpoint and endpoint. For managing uncertainty, ReCiPe is well regarded for characterization and pollutant transport. Midpoint has lower uncertainty whereas the environmental relevance of endpoint may be of more interest. However, uncertainty may also be influenced by the goal & scope and life cycle inventory, both of which may be discussed briefly also.
There should be further clarification how OpenAI referenced in Line 179,180 was used, how the data was validated, or deemed of sufficient quality. Use of AI, machine learning, extrapolation, and approximate corollaries in life cycle inventories is often necessary but AI resources may not produce reliable data.
Further explanation or refining Line 259-261 may be warranted on the end-of-life, specifically with respect to concerns about double counting and the energy intensity of recycling. If possible, perhaps cite other literature that has taken the same approach. Designing the process in this manner will not generate emissions credits via system expansion but may be dismissive to trade-offs. Perhaps energy and labor intensity would be appropriately cited as research elsewhere that focuses on end-of-life.
Section 3.2, Lines 329-330 compares the carbon dioxide per kg emissions results produced from this study with those from the United States Energy Information Administration (USEIA). The fact that the USEIA emissions calculation method is unknown (Lines 341-344) should be stated following this initial comparison. The USEIA estimates have value but those calculated within the PJM network, using ReCiPe, may be more appropriate in the scope of this paper.
Section 3.2, Lines 360- 362 it is implied that the impacts to water quality and habitat destruction are externalities unrelated to elemental (chemical) emissions not included in this analysis. This should be made clearer. Analysis of these issues may be better calculated using an environmental impact statement. Similar acknowledgments could be made about implications and risks of nuclear energy including long-term storage/land use loss in Lines 344-347.
Technical Corrections
Line 78: The data or results produced from a life cycle assessment should inform sustainability initiatives. It may not unilaterally support them as stated.
Line 78-79: This may be broken into two sentences.
Line 79-81: Rephrase or break into two sentences.
Line 175: Revise HVDC to High Voltage Direct Current unless it is referenced earlier.
Line 259: There is a grammatical error ‘The recycled the process…’
Line 260: ‘…no costs or avoided costs’ is better referenced as emissions or impact unless there is a further economic implication being discussed in this paper or section.
Line 307: State the impact category that is influenced by diesel fuel needed. It is implied that it is natural resource scarcity derived from midpoints mineral resource scarcity and fossil resource scarcity.
Line 357: ‘… which makes sense’ expects the reader to draw conclusions and is informal. A finite statement can be made that acknowledges the impacts reflect the relative location of these compared technologies.
Figure 7, Figure 8: These figures are not a comparison of product stages as stated in the figure. It is a comparison of technologies/scenarios/energy sources.
Citation: https://doi.org/10.5194/wes-2024-143-RC1 -
RC2: 'Comment on wes-2024-143', Anonymous Referee #2, 22 Mar 2025
General comments
This paper presents a life cycle assessment of the Atlantic Shores offshore wind project in New Jersey. The authors provide clear explanations of their methods, assumptions, and conclusions. The analysis contributes to scientific understanding of offshore wind impacts by considering a new geographic region and adding to the relatively small body of studies of the technology at this scale (15 MW). The authors use well-established methods and provide documentation of their inputs and assumptions. The findings are presented clearly with informative figures and explanation.
Specific comments
- Lines 35-36 “Power densities…” The range of 3-5 MW/km2 describes the expected wind turbine spacing and is not indicative of the quality of the wind resource. Wind speed is more typically cited in this context.
- Line 57 “increased inflation” While inflation has been a challenge for offshore wind projects on the East Coast (and elsewhere), it would be more accurate to say that inflation has increased project costs rather than that international offshore wind supply chains have caused inflation.
- Lines 122-123 “40% efficiency” Do you mean capacity factor?
- Lines 136-138 “While the offshore substation is included…” I understand you’re limiting the scope, but some of the electrical equipment in the offshore substation is quite massive and may contain substances with high environmental impact potential, for example, SF6 in some gas-insulated switchgear. Have you done any analysis of how including substation equipment could affect your results?
- Lines 210-212 “Transportation” Why was land transportation assumed between the manufacturers and the NJ Wind Port? Major offshore wind components are too large for conventional land transport, which is why all the selected manufacturing sites are located at ports. Ship transport would be a more appropriate assumption here.
- Lines 246-250 “This LCA assumes regularly scheduled annual maintenance…” Eliminating all unscheduled maintenance and major replacements is not very realistic. It would be helpful to provide readers with an idea of how much this could affect results, for example Allekotte and Garrett (2024) “Life Cycle Assessment of electricity production from an offshore V236-15 MW wind plant” finds that doubling or halving replacement parts changes impact indicators by <2%.
- Lines 308-309 “This finding further highlights…” This conclusion reaches beyond the evidence presented here. Without comparative data for domestic and international supply chains, there is no support for the statement that one has lower impacts.
- Lines 376-378 “Steel manufacturing…” Given the importance of steel manufacturing in your results, it would be informative to discuss the relative impacts of steel produced by electric arc furnace (predominant in U.S. steelmaking) versus basic oxygen furnace (represented in the Ecoinvent Steel, low-alloyed, hot rolled {GLO} dataset).
Technical corrections
- Line 233 “consumes 14 tops/day” should be tons/day
Citation: https://doi.org/10.5194/wes-2024-143-RC2
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