Using Ecological Risk Assessment to Assess EMF Impacts to Marine Life From offshore Wind Infrastructure

Abstract

Abstract Offshore wind is a focal point of U.S. strategy for renewable energy, with several projects along the East, West and Gulf coasts slated to achieve a federal wind target of 30 gigawatts by 2030. Offshore wind projects will generate and transmit renewable energy, and certain components (e.g., buried cables) will generate both electric and magnetic fields, collectively referred to as EMF. Research has demonstrated that marine species across various taxa interact with EMF produced from both natural and anthropogenic sources. For species known to be sensitive to EMF (including certain finfish, the elasmobranch group, and benthic invertebrates), interaction with anthropogenically generated EMF may influence the detection of electric and magnetic fields used in foraging, avoidance, mate selection and migration. To evaluate the potential for impacts, we apply the standard framework for ecological risk assessment (ERA). This framework offers a systematic approach and appropriate context for assessing exposure and potential hazards to characterize risk. A conceptual model is used to describe sensitive species with the greatest potential for exposure, and the spatial and temporal scales of exposure. To estimate exposure, we use both open-source (EMF Python package) and commercially available software (COMSOL Multiphysics®) to mathematically model applicable direct current and alternating current EMF generated by various components (e.g., inter-array cables, export cables). Field strengths decline with distance from conductors but vary with parameters such as voltage, amperage, conductor diameter, and shielding. For each component, we then take predicted field strengths at different distances and compare them to effect screening levels for marine life. Application of the ERA framework dramatically improves the information used to inform preconstruction impact assessment for offshore wind. The method provides quantitative estimates of risk and allows for the comparison of how different management options, such as different burial depths and spacing of components, influence risks. An additional advantage of the approach is that it can be used to identify important areas where more information is needed, such as the need to better define the spatial and temporal scale of populations relevant to individual offshore wind projects and cumulative projects. We recommend the ERA framework be adopted more widely as a systematic process for capturing and integrating context-dependent information necessary for characterizing EMF risk for marine life.