Workbook of Atmospheric Dispersion Estimates

Turner, D.B.

doi:10.1201/9780138733704

Cited by 155 publications

(65 citation statements)

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“…Recall that dust storms pick up most of their dust from the surface of lands that have seen extensive agricultural and other development that alters the soil (and rodent habitat availability), and they likely entrain far less from the subsurface of relatively unchanged desert soils that are presumably more favorable for rodent burrows. Regarding atmospheric dispersion, once arthroconidia are disturbed and become airborne, the suspended particles are subject to Gaussian dispersion (e.g., Turner, 1994 ). Their concentration decreases logarithmically in three dimensions (distance downwind, plume width, and plume height), leading to a rapid drop‐off of particle concentrations away from the source.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

No Consistent Link Between Dust Storms and Valley Fever (Coccidioidomycosis)

Comrie

2021

GeoHealth

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Dust storms, such as those associated with haboobs and strong regional winds, are frequently assumed to cause increases in cases of Valley fever (coccidioidomycosis). The disease is caused by inhaling arthroconidia of Coccidioides fungi that, after being disturbed from semi‐desert subsoil, have become airborne. Fungal arthroconidia can be transported in low‐wind conditions as well as in individual dust events, but there is no reliable evidence that all or most dust storms consistently lead to subsequent increases in coccidioidomycosis cases. Following a review of the relevant literature, this study examines the relationship between dust storms and coccidioidomycosis cases to determine if there is a consistent and general association between them. All recorded dust storms from 2006 to 2020 in and near the Phoenix area of Maricopa County, Arizona and the Bakersfield area of Kern County, California were used in a compositing analysis (superposed epoch analysis) of subsequent coccidioidomycosis cases in each area. Analyses of monthly and weekly disease case data showed no statistical differences in the patterns of coccidioidomycosis cases following dust storms versus non‐dust storm conditions, for the entire data set as well as for seasonal subsets of the data. This study thoroughly analyzes post‐dust storm coccidioidomycosis cases for a large set of dust storms, and it confirms and expands upon previous literature, including a recent study that measured airborne arthroconidia and found no consistent links connecting wind and dust conditions to increases in coccidioidomycosis.

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Section: Conclusion and Discussionmentioning

confidence: 99%

No Consistent Link Between Dust Storms and Valley Fever (Coccidioidomycosis)

Comrie

2021

GeoHealth

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“…Many past studies have evaluated AERMOD in a variety of environments, including complex terrain and urban environments. They found that AERMOD predicts maximum annual-average concentrations (at distances less than 1 km to the source) within 20–40%. ,, Additionally, Gaussian plume models are derived directly from the conservation of mass, and substantial work since the 1950s has gone into developing accurate parametrization of the dispersion parameters used in the model, , making AERMOD a robust model for predicting the high-resolution spatial variation in concentration.…”

Section: Methodsmentioning

confidence: 99%

EASIUR-HR: A Model To Evaluate Exposure Inequality Caused by Ground-Level Sources of Primary Fine Particulate Matter

Gentry

Robinson

Adams

2023

Environ. Sci. Technol.

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People of color disproportionately bear the health impacts of air pollution, making air quality a critical environmental justice issue. However, quantitative analysis of the disproportionate impacts of emissions is rarely done due to a lack of suitable models. Our work develops a high-resolution reduced-complexity model (EASIUR-HR) to evaluate the disproportionate impacts of ground-level primary PM2.5 emissions. Our approach combines a Gaussian plume model for near-source impacts of primary PM2.5 with a previously developed reduced-complexity model, EASIUR, to predict primary PM2.5 concentrations at a spatial resolution of 300 m across the contiguous United States. We find that low-resolution models underpredict important local spatial variation of air pollution exposure to primary PM2.5 emissions, potentially underestimating the contribution of these emissions to national inequality in PM2.5 exposure by more than a factor of 2. We apply EASIUR-HR to analyze the impacts of vehicle electrification on exposure disparities. While such a policy has small aggregate air quality impacts nationally, it reduces exposure disparity for race/ethnic minorities. Our high-resolution RCM for primary PM2.5 emissions (EASIUR-HR) is a new, publicly available tool to assess inequality in air pollution exposure across the United States.

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“…Commonly used for emergency response in atmospheric dispersion modeling, χ is the downstream concentration of pollutant and Q is either the rate of release, or total source strength. This dispersion parameter represents the relative concentration of the pollutant as it travels downstream from the release point (Turner 1994).…”

Section: Methodsmentioning

confidence: 99%

Inverse Aqueous Transport Modeling for Emergency Response

Turner

Werth

Buckley

2023

Preprint

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ALGE is a three-dimensional, finite-difference aqueous transport model that simulates pollutant fate and transport in lakes, rivers, bays, and estuaries by solving the prognostic equations of mass, momentum, and energy. Its current modeling capabilities include transport of dissolved tracer for a series of predefined basins across the continental United States. Recently, an inverse method (also known as backtracking) has been added to ALGE to provide a possible source of a pollutant should one be detected by a sensor in a body of water and a source is not known. This inverse method is a three-step process that uses an algorithm to inverse the flow. We demonstrate the new model’s capabilities through simulating the 2021 Piney Point spill in Tampa Bay, Florida (USA). This involves moving tracer backwards from its detection points, encompassing a potential source area, and applying Bayes’ Theorem and to reduce the area within which the true source could be located.

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Workbook of Atmospheric Dispersion Estimates

Cited by 155 publications

References 0 publications

No Consistent Link Between Dust Storms and Valley Fever (Coccidioidomycosis)

No Consistent Link Between Dust Storms and Valley Fever (Coccidioidomycosis)

EASIUR-HR: A Model To Evaluate Exposure Inequality Caused by Ground-Level Sources of Primary Fine Particulate Matter

Inverse Aqueous Transport Modeling for Emergency Response

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