The Impact of Offshore Wind Farms on Marine Ecosystems: A Review Taking an Ecosystem Services Perspective

The rapid increase in renewable energy generation from wind has increased concerns about the impacts that wind arrays have on the marine environment and what these impacts mean for society. One method for identifying the impacts of offshore wind farms (OWFs) on human welfare is through the assessment and valuation of ecosystem services. Using an ecosystem services approach, this paper reviews the impacts of OWFs on the ecosystem services delivered by marine environments. During the construction phase, supporting services such as reduced energy capture and nutrient cycling are changed due to the introduction of hard substrate and the reduction in soft sediment habitat at turbine bases. This may lead to changes in all other ecosystem services, both negative and positive. Quantifying these changes, however, is a challenge partly due to data limitations and a lack of clear understanding of the impacts of OWFs on the marine ecosystems. Scientific effort needs to quantitatively explore the impacts of OWFs on ecosystem functionality and the gathering of data that enables the assessment of changes to ecosystem services. Data needed to better quantify and value the impacts of OWFs on ecosystem services are suggested. The development of methods which integrate socioeconomic valuation of ecosystem services into the evaluation of renewable energy devices compliments efforts in assessing the environmental impacts and should enable a holistic assessment of the impact of renewable energy production and greenhouse gas mitigation technologies on the U. K. carbon footprint.

Air/sea DMS gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed

Shipboard measurements of eddy covariance dimethylsulfide (DMS) air–sea fluxes and seawater concentration were carried out in the North Atlantic bloom region in June/July 2011. Gas transfer coefficients (k660) show a linear dependence on mean horizontal wind speed at wind speeds up to 11 m s−1. At higher wind speeds the relationship between k660 and wind speed weakens. At high winds, measured DMS fluxes were lower than predicted based on the linear relationship between wind speed and interfacial stress extrapolated from low to intermediate wind speeds. In contrast, the transfer coefficient for sensible heat did not exhibit this effect. The apparent suppression of air–sea gas flux at higher wind speeds appears to be related to sea state, as determined from shipboard wave measurements. These observations are consistent with the idea that long waves suppress near-surface water-side turbulence, and decrease interfacial gas transfer. This effect may be more easily observed for DMS than for less soluble gases, such as CO2, because the air–sea exchange of DMS is controlled by interfacial rather than bubble-mediated gas transfer under high wind speed conditions.

Metocean Comparisons of Jason-2 and AltiKa—A Method to Develop a New Wind Speed Algorithm

As well as range, the AltiKa altimeter provides estimates of wave height, Hs and normalized backscatter, s0, that need to be assessed prior to statistics based on them being included in climate databases. An analysis of crossovers with the Jason-2 altimeter shows AltiKa Hs values to be biased high by only »0.05m, with a standard deviation (s.d.) of »0.1m for seven-point averages. AltiKa’s s 0 values are 2.5–3 dB less than those from Jason-2, with a s.d. of »0.3 dB, with these relatively large mismatches to be expected as AltiKa measures a different part of the spectrum of sea surface roughness. A new wind speed algorithm is developed through matchinghistogram of s0 values to that for Jason-2 wind speeds. The algorithm is robust to the use of short durations of data, with a consistency at roughly the 0.1 m/s level. Incorporation of Hs as a secondary input reduces the assessed error at crossovers from 0.82 m/s to 0.71 m/s. A comparison across all altimeter frequencies used to date demonstrates that the lowest wind speeds preferentially develop the shortest scales of roughness.