Surface impacts of large offshore wind farms

Golbazi, Maryam; Archer, Cristina L.; Alessandrini, Stefano

doi:10.1088/1748-9326/ac6e49

Cited by 10 publications

(10 citation statements)

References 44 publications

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“…2022). The simulations used here use wind turbines with a hub-height of 138 m, which resembles the "extreme-scale" turbine of Golbazi et al (2022). While they find cooling at the surface for extreme-scale turbines, we still find warming at the surface during stable conditions.…”

Section: Wind Plant Wake Impacts On 2-m Temperaturementioning

confidence: 89%

“…Wind farms can also cause changes in surface temperatures. Wind plants tend to cause a warming at the surface during stable conditions (Baidya Roy and Traiteur, 2010;Fitch et al, 2013;Rajewski et al, 2014;Siedersleben et al, 2018;Golbazi et al, 2022). The hypothesis proposed by Baidya Roy and Traiteur (2010) suggests that enhanced vertical mixing induced by wind turbine wakes causes this warming.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, during stable conditions when warmer air lies over cooler air, heat fluxes are negative (downward) (Stull, 1988). According to Golbazi et al (2022), the magnitude of the heat flux decreases in areas experiencing cooling. This weakening is indicated by a positive change when the atmosphere is stable and a negative change when the atmosphere is unstable.…”

Section: Introductionmentioning

confidence: 99%

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Meteorological Impacts of Offshore Wind Turbines as Simulated in the Weather Research and Forecasting Model

Quint,

Lundquist,

Bodini

et al. 2024

Preprint

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Abstract. Offshore wind energy projects are currently in development off the east coast of the United States and will likely influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants will change the local meteorology. We compared one year of simulations from the Weather Research and Forecasting model with and without wind farms incorporated, focusing on the lease area south of Massachusetts and Rhode Island. We assessed changes in wind speeds, 2 m temperature, surface heat flux, turbulent kinetic energy, and boundary layer height during different stability classifications and ambient wind speeds over the entire year. Because the wake behavior may be a function of boundary-layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary-layer height. Hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds. Wind speeds at 10 m increase within the wind plant area during stable conditions. Differences in 2 m temperatures and surface heat fluxes are small, but are largest during stable conditions and strong wind speeds. Turbulence kinetic energy (TKE) increases within the lease area with increasing wind speeds at both the surface and at hub height. At hub height, TKE increases do not depend on stability, but at the surface, TKE increases most during unstable conditions as the turbulence injected at hub height is mixed down to the surface. Boundary-layer heights increase within the wind plant, and decrease slightly downwind during stable conditions. Deeper boundary-layer heights, exceeding 100 m, tend to correlate with smaller wake areas and distances, though other factors likely also play a role in determining the extent of the wind farm wake.

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Section: Wind Plant Wake Impacts On 2-m Temperaturementioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Meteorological Impacts of Offshore Wind Turbines as Simulated in the Weather Research and Forecasting Model

Quint,

Lundquist,

Bodini

et al. 2024

Preprint

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“…This is while the percent contribution to PM 2.5 concentrations remains below 27% across the domain (Figure 2d). In a worst-case scenario, however, the maximum contribution of the ships to PM 2.5 concentrations within the 3 months is significantly high across the domain but due to the dominant southwesterly wind direction in the region (Golbazi et al, 2022), it mostly remains over the Atlantic Ocean (Figure 2b). The maximum impact on PM 2.5 during the 3 months reaches as high as 8 µg m −3 .…”

Section: Fine Particulate Matter (Pm 25 )mentioning

confidence: 99%

“…In CAMx, the plume rise calculations for point sources including the CMV emissions depend on meteorological conditions and atmospheric stability to determine what vertical layer the emissions are emitted in. In the summertime, various atmospheric stabilities have been found to be dominant over the Atlantic ocean depending on different locations (Golbazi et al, 2022;Golbazi and Archer, 2019;Archer et al, 2016). We use the WRF model to provide meteorological inputs to CAMx.…”

Section: Introductionmentioning

confidence: 99%

Impacts of maritime shipping on air pollution along the U.S. East Coast

Golbazi

Archer

2023

Preprint

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Abstract. Air pollution is considered a leading threat to human health in the United States (U.S.) and worldwide. An important source of air pollution in coastal areas is the globally increasing maritime shipping traffic. In this study, we take a high-resolution modeling approach to investigate the impacts of ship emissions on concentrations of various atmospheric pollutants, under the meteorological conditions and emissions of the year 2018. We utilize the Comprehensive Air Quality Model with extensions (CAMx) to simulate transport, diffusion, and chemical reactions, and the Weather Research and Forecasting (WRF) model to provide the meteorological inputs. We focus on four criteria pollutants – fine particulate matter with a diameter smaller than 2.5 μm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) – as well as nitrogen oxide (NO), and we calculate their concentrations in the presence and absence of the ship emissions along the U.S. East Coast, particularly in the proximity of major ports. We find that ship emissions increase the PM2.5 concentrations over the ocean and sparse areas inland. The 98-th percentile of the 24-hour average PM2.5 concentrations (the "design value'' used by the U.S. Environmental Protection Agency) increased by up to 3.2 μm m−3 in some coastal areas. In addition, ships contribute significantly to SO2 concentrations, up to 95 % over the Atlantic and up to 90 % over land in coastal states, which represents a ~45 ppb increase in the SO2 design values in some states. The 98-th percentile of the hourly NO2 concentrations also increased by up to 15 ppb at the major ports and along the shore. In addition, we find that the impact of shipping emissions on O3 concentrations is not uniform, meaning that ships affect ozone pollution in both positive and negative ways. Over the ocean, O3 concentrations were significantly higher in the presence of ships, but in major coastal cities, O3 concentrations decreased in the presence of ships. Our simulation results show that ships emit significant amounts of fresh NO in the atmosphere, which then helps scavenge O3 in VOC-limited areas, such as major ports. By contrast, over the ocean (NOx-limited regime), enhanced NOx (NO2 + NO) concentrations due to ships contribute to the formation of O3 and therefore enhance O3 concentrations. Overall, due to the dominant southwesterly wind direction in the region, the impacts of ships on air pollutants mainly remain offshore. However, in coastal states near major ports, the impacts are significantly important.

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