Abstract
This Environmental Sensitivity Analysis (Study) was conducted to identify areas of biological importance within the offshore Area of Analysis (AoA) using a risk assessment and sensitivity model. The model incorporated information on marine resources, or “receptors;” impacts on these resources, or “stressors;” and the level of risk associated with the stressors on a particular receptor during each phase of wind farm development. Results of the model were used to facilitate the identification of areas for consideration for offshore wind development and will inform future developers, potentially reducing the uncertainty and costs of their proposals.
For this Study, environmental sensitivity is defined as the relative potential susceptibility to alteration or influence from activities associated with offshore wind development. For example, since fish are potentially sensitive to localized turbidity, which may result from turbine installation, areas where fish and turbine installation may co-occur may be regions with elevated sensitivity relative to areas where they would not co-occur.
This Study used existing seasonal and spatial data for marine species (i.e., predicted species density, core biomass, core abundance, essential habitat, and predicted habitat) to examine the sensitivity of these resources to potential stressors during the three phases of offshore wind development (i.e., pre-construction, construction, and post-construction) within the AoA. The AoA is a 14,569-square-mile area of the ocean extending from 15 nautical miles from the coast of Long Island and New York City to the continental shelf break, slope, and into oceanic waters to an approximate maximum depth of 2,500 meters. The marine resources were assessed as receptor groups (e.g., fish, benthic species, right whales, phocid seals, low-frequency cetaceans), which were expected to respond similarly to the identified stressors. Concurrent studies also appended to the New York State Offshore Wind Master Plan, and a study specific literature review informed the identification of receptors and stressors and the risk assessment.
A risk assessment was conducted, through which matrices were developed to differentiate relative risks. These risk matrices were constructed of defined criteria under which risk scores of 1 through 5 were assigned to the receptor groups for each potential stressor. This assessment process considered the probability of impact from an identified stressor and the vulnerability of the receptor group to the potential stressor. Based on the risk assessment described in the relative risk matrices, regulatory context, permitting requirements, Bureau of Ocean Energy Management (BOEM) recommendations, seasonality, and other additional factors, sensitivity weight values of 1 through 5 were determined for receptor groups for each phase of offshore wind development.
These sensitivity weight values were incorporated into a sensitivity model, through which a series of seasonal and annual comparative maps were produced of the potential sensitivity of receptor groups during each of the offshore wind development phases. A series of overlay analysis methods were examined to determine the best-suited modeling technique. After preliminary evaluation, the weighted sum model (also known as the linear weighted method) was chosen for the modeling process. The model used comprehensive data sets that represented relative occurrence and temporal trends of the receptor groups within the AoA. This selection of input data was informed by concurrent studies.
The mapping outputs from the modeling exercise, along with other studies and tools, informed New York State’s preliminary identification of wind energy areas in the AoA for BOEM’s consideration. The output maps displayed seasonal sensitivity shifts for all receptor groups. Specifically, in all phases of offshore wind development, sensitivity was lower throughout the AoA during the fall and higher during the spring. Sensitivity was also consistently greater along the continental shelf slope and Hudson Canyon.