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Links between Meteorology, Air Quality, and Wind Energy along the U.S. East Coast.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Links between Meteorology, Air Quality, and Wind Energy along the U.S. East Coast./
作者:	Golbazi, Maryam.
面頁冊數:	1 online resource (164 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-03, Section: B.
Contained By:	Dissertations Abstracts International84-03B.
標題:	Atmospheric sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29261116click for full text (PQDT)
ISBN:	9798351459769

Links between Meteorology, Air Quality, and Wind Energy along the U.S. East Coast.
Golbazi, Maryam.

Links between Meteorology, Air Quality, and Wind Energy along the U.S. East Coast. - 1 online resource (164 pages)

Source: Dissertations Abstracts International, Volume: 84-03, Section: B.

Thesis (Ph.D.)--University of Delaware, 2022.

Includes bibliographical references

Air pollution is considered a leading threat to human health in the US and worldwide. In a world with a growing industry, it is of the utmost importance to control the emission levels to ensure that the pollution levels stay below harmful levels for human health. Air pollution also contributes to global warming and climate change. It is essential to recognize and utilize clean energy sources for a clean world. The wind is one of the most abundant sources in nature, making it an excellent resource for creating sustainable energy for a sustainable world. Using wind energy is essential for mitigating and reversing anthropogenic global warming, as wind turbines do not emit emissions that contribute to atmospheric pollutants compared to other fossil fuel power plants. Wind energy is undeniably beneficial to humanity since wind farms replace fossil fuel power plants and their associated air pollution and greenhouse gas emissions while generating clean, renewable, and inexhaustible electricity. However, building large wind farms offshore might alter the atmospheric conditions near the surface not only offshore but also onshore in highly-populated coastal areas. This dissertation is based on two main topics; are air quality and offshore wind modeling. The motivation behind both topics is to contribute to the scientific understanding of the mechanism behind physical and chemical phenomena in the atmosphere and improve our understanding of the impacts of different factors on air quality and meteorology in highly populated areas. Factors include large-scale offshore wind energy installation, shipping activities near the coastal areas, and personal/passenger car transportation and air traffic during the pandemic. According to the White House, the US is positioning itself to deploy 30 gigawatts of offshore wind energy along the east coast by 2030, and 110 GW by 2050 on the East Coast or the West Coast. Future offshore wind farms worldwide will be built with wind turbines of size and capacity never seen before onshore. We conduct high-resolution numerical simulations using a mesoscale model and compare scenarios with and without offshore wind farms equipped with these "extreme-scale" wind turbines. The results improve our understanding of the impacts of large-scale offshore wind farms with on atmospheric properties. In addition, we provide an analysis of the sensitivity of surface impacts to turbine hub height, as well as the cumulative impacts of the large US wind energy areas, including their potential impacts on coastal areas. We find that the size and the hub height of the turbine play a significant role in their impacts near the surface. Nevertheless, the surface meteorological impacts of large offshore wind farms equipped with extreme-scale turbines appear to be negligible. We extend this work by using an air quality model and simulating the pollution concentrations in the presence and absence of the farms. We found that the effects of the farms on pollution concentrations are also negligible in magnitude. The surface properties such as the surface roughness (SR) length can alter the model calculations for factors such as the wind speed in higher elevations. Furthermore, with the growing wind industry on the East Coast of the US, measurements of wind speed and other meteorological factors are required. So far, only a few wind measurements are available in the region and none at hub height (around 120 m today); thus, extrapolations are needed to estimate wind speed as a function of height and these estimations require a deep understanding of the SR. A common method to estimate wind speed at hub height is the log-law, based on surface roughness length (z0). To this end, we conducted a study to analyze the performance of various methods used in the literature for SR calculations and to better understand the concept of the SR and its physical and mathematical definitions of it. We use surface measurements from two field campaigns that were conducted in the Nantucket Sound, MA. We tested three different methods in the literature to calculate z0: 1) analytical, dependent on friction velocity u∗ and a stability function "Psi"; 2) the Charnock relationship between z0 and u∗, and 3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. The findings are discussed in detail in section 2.2.After exploring the concept of offshore wind, as a clean energy source, and its impacts on atmospheric factors, we investigate the factors contributing to air pollution along the East Coast of the US. Due to the utmost importance of the air quality topic, there have been many studies investigating the contribution of many sectors to pollution levels in the US. While ship traffic is increasing globally and is becoming an important source of air pollution, especially in the coastal areas, none of the studies have focused on the net contribution of the ships on the East Coast in a high resolution. Here we explore the impacts of the ocean-going shipping emissions on the air quality of the region. Personal transportation and air traffic, are two other significant contributors to air pollution. During the year 2020, due to the novel coronavirus disease (COVID-19 hereafter) and a global pandemic announcement, personal transportation, and air traffic decreased dramatically, especially in large cities in the US. With that significant reduction in traffic levels, did the air quality improve? If so, what pollutants decreased/increased in the US? In section 3.6 we answer these questions and quantify the magnitude and spatial variability of air quality changes during the COVID-19 pandemic. We take a modeling approach to quantify the impact magnitude on regulated pollutants in the domain of study for both of the air quality topics.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798351459769Subjects--Topical Terms:

3168354
Atmospheric sciences.
Subjects--Index Terms:

Air qualityIndex Terms--Genre/Form:

542853
Electronic books.

Links between Meteorology, Air Quality, and Wind Energy along the U.S. East Coast.
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Wind energy is undeniably beneficial to humanity since wind farms replace fossil fuel power plants and their associated air pollution and greenhouse gas emissions while generating clean, renewable, and inexhaustible electricity. However, building large wind farms offshore might alter the atmospheric conditions near the surface not only offshore but also onshore in highly-populated coastal areas. This dissertation is based on two main topics; are air quality and offshore wind modeling. The motivation behind both topics is to contribute to the scientific understanding of the mechanism behind physical and chemical phenomena in the atmosphere and improve our understanding of the impacts of different factors on air quality and meteorology in highly populated areas. Factors include large-scale offshore wind energy installation, shipping activities near the coastal areas, and personal/passenger car transportation and air traffic during the pandemic. According to the White House, the US is positioning itself to deploy 30 gigawatts of offshore wind energy along the east coast by 2030, and 110 GW by 2050 on the East Coast or the West Coast. Future offshore wind farms worldwide will be built with wind turbines of size and capacity never seen before onshore. We conduct high-resolution numerical simulations using a mesoscale model and compare scenarios with and without offshore wind farms equipped with these "extreme-scale" wind turbines. The results improve our understanding of the impacts of large-scale offshore wind farms with on atmospheric properties. In addition, we provide an analysis of the sensitivity of surface impacts to turbine hub height, as well as the cumulative impacts of the large US wind energy areas, including their potential impacts on coastal areas. We find that the size and the hub height of the turbine play a significant role in their impacts near the surface. Nevertheless, the surface meteorological impacts of large offshore wind farms equipped with extreme-scale turbines appear to be negligible. We extend this work by using an air quality model and simulating the pollution concentrations in the presence and absence of the farms. We found that the effects of the farms on pollution concentrations are also negligible in magnitude. The surface properties such as the surface roughness (SR) length can alter the model calculations for factors such as the wind speed in higher elevations. Furthermore, with the growing wind industry on the East Coast of the US, measurements of wind speed and other meteorological factors are required. So far, only a few wind measurements are available in the region and none at hub height (around 120 m today); thus, extrapolations are needed to estimate wind speed as a function of height and these estimations require a deep understanding of the SR. A common method to estimate wind speed at hub height is the log-law, based on surface roughness length (z0). To this end, we conducted a study to analyze the performance of various methods used in the literature for SR calculations and to better understand the concept of the SR and its physical and mathematical definitions of it. We use surface measurements from two field campaigns that were conducted in the Nantucket Sound, MA. We tested three different methods in the literature to calculate z0: 1) analytical, dependent on friction velocity u∗ and a stability function "Psi"; 2) the Charnock relationship between z0 and u∗, and 3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. The findings are discussed in detail in section 2.2.After exploring the concept of offshore wind, as a clean energy source, and its impacts on atmospheric factors, we investigate the factors contributing to air pollution along the East Coast of the US. Due to the utmost importance of the air quality topic, there have been many studies investigating the contribution of many sectors to pollution levels in the US. While ship traffic is increasing globally and is becoming an important source of air pollution, especially in the coastal areas, none of the studies have focused on the net contribution of the ships on the East Coast in a high resolution. Here we explore the impacts of the ocean-going shipping emissions on the air quality of the region. Personal transportation and air traffic, are two other significant contributors to air pollution. During the year 2020, due to the novel coronavirus disease (COVID-19 hereafter) and a global pandemic announcement, personal transportation, and air traffic decreased dramatically, especially in large cities in the US. With that significant reduction in traffic levels, did the air quality improve? If so, what pollutants decreased/increased in the US? In section 3.6 we answer these questions and quantify the magnitude and spatial variability of air quality changes during the COVID-19 pandemic. We take a modeling approach to quantify the impact magnitude on regulated pollutants in the domain of study for both of the air quality topics.
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