Temporal Trends in Blowing Dust in Lubbock, El Paso, and Phoenix, 1948 to 2022, and the Effects of Drought and Wind Power

Blowing dust is a critical environmental and public health concern in arid and semi-arid regions of the Western United States. This dissertation investigates the temporal relationships between wind speed, drought conditions, and dust activity using long-term data from three NOAA weather stations. By examining these variables over time, the study aims to better understand the environmental conditions that contribute to dust events. Specifically, regression analysis is used to quantify the strength and nature of these relationships, offering a robust framework for modeling how changes in one variable may influence another. A key contribution of this research is the development of an adaptive monitoring framework—an adaptive method for assessing airborne dust conditions as new data becomes available. While the literature review compares various drought indices and dust measurement methods, the study itself focuses on applying a consistent methodology to quantify correlations across selected locations. By emphasizing natural drivers such as wind and drought, this work enhances our understanding of dust dynamics and supports efforts to mitigate their impacts on health, safety, and infrastructure.

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Publication Details

Journal
ThinkTech (Texas Tech University)
Published
2025-12-01
Primary Topic
Atmospheric aerosols and clouds
Type
article
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article

Temporal Trends in Blowing Dust in Lubbock, El Paso, and Phoenix, 1948 to 2022, and the Effects of Drought and Wind Power

Prudence Anne Venner
ThinkTech (Texas Tech University)
Atmospheric aerosols and clouds
article

Temporal Trends in Blowing Dust in Lubbock, El Paso, and Phoenix, 1948 to 2022, and the Effects of Drought and Wind Power

Prudence Anne Venner
article en

Abstract

Blowing dust is a critical environmental and public health concern in arid and semi-arid regions of the Western United States. This dissertation investigates the temporal relationships between wind speed, drought conditions, and dust activity using long-term data from three NOAA weather stations. By examining these variables over time, the study aims to better understand the environmental conditions that contribute to dust events. Specifically, regression analysis is used to quantify the strength and nature of these relationships, offering a robust framework for modeling how changes in one variable may influence another. A key contribution of this research is the development of an adaptive monitoring framework—an adaptive method for assessing airborne dust conditions as new data becomes available. While the literature review compares various drought indices and dust measurement methods, the study itself focuses on applying a consistent methodology to quantify correlations across selected locations. By emphasizing natural drivers such as wind and drought, this work enhances our understanding of dust dynamics and supports efforts to mitigate their impacts on health, safety, and infrastructure.

ThinkTech (Texas Tech University)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Atmospheric aerosols and clouds
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