Atmospheric Dispersion Modeling

Sugiyama, G.; Nasstrom, John S.; Pobanz, B; Foster, Kathryn A.; Simpson, Matthew; Vogt, P; Aluzzi, F J; Homann, Steve

doi:10.1097/hp.0b013e31824c7bc9

Cited by 35 publications

(13 citation statements)

References 10 publications

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“…Our estimates are generally conservative by a factor of two with respect to I-131 and in line with respect to Cs-137 compared with estimates made by the Japanese government, including the Nuclear and Industrial Safety Agency and the Japan Atomic Energy Agency. 11 The Japanese Nuclear Safety Commission estimated an emission of 1.5 Â 10 47 Stohl et al [2011] predicted a Cs-137 emission rate roughly twice our emission rate using a similar methodology incorporating dispersion modeling and CTBTO observations, 9 yet their estimate is higher than other published estimates. 11 During CTBTO measurements, large volumes of air pass through high efficiency filter paper used to collect particles over a 24 hour period.…”

Section: Estimating Radionuclide Emissions Based On Observationsmentioning

confidence: 66%

“…6 Several studies have tracked the emission, transport, and deposition of radionuclides from Fukushima using observational datasets and chemical transport models. 1,4,[7][8][9][10][11] Initial studies have suggested that less than one quarter of the radioactivity was deposited over land in Japan, and only 1% of the radiation reached Europe. 4 However, no study to date has examined the global health effects of such radioactivity or simulated the radioactivity with a model that treats sizeresolved aerosol particle microphysics or gas-aerosol-cloud interactions.…”

Section: Introductionmentioning

confidence: 99%

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Worldwide health effects of the Fukushima Daiichi nuclear accident

Hoeve

Jacobson

2012

Energy Environ. Sci.

277

124

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This study quantifies worldwide health effects of the Fukushima Daiichi nuclear accident on 11 March 2011. Effects are quantified with a 3-D global atmospheric model driven by emission estimates and evaluated against daily worldwide Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) measurements and observed deposition rates. Inhalation exposure, ground-level external exposure, and atmospheric external exposure pathways of radioactive iodine-131, cesium-137, and cesium-134 released from Fukushima are accounted for using a linear no-threshold (LNT) model of human exposure. Exposure due to ingestion of contaminated food and water is estimated by extrapolation. We estimate an additional 130 (15-1100) cancer-related mortalities and 180 (24-1800) cancer-related morbidities incorporating uncertainties associated with the exposure-dose and dose-response models used in the study. We also discuss the LNT model's uncertainty at low doses. Sensitivities to emission rates, gas to particulate I-131 partitioning, and the mandatory evacuation radius around the plant are also explored, and may increase upper bound mortalities and morbidities in the ranges above to 1300 and 2500, respectively. Radiation exposure to workers at the plant is projected to result in 2 to 12 morbidities. An additional $600 mortalities have been reported due to non-radiological causes such as mandatory evacuations. Lastly, a hypothetical accident at the Diablo Canyon Power Plant in California, USA with identical emissions to Fukushima was studied to analyze the influence of location and seasonality on the impact of a nuclear accident. This hypothetical accident may cause $25% more mortalities than Fukushima despite California having one fourth the local population density due to differing meteorological conditions.

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Section: Estimating Radionuclide Emissions Based On Observationsmentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

Worldwide health effects of the Fukushima Daiichi nuclear accident

Hoeve

Jacobson

2012

Energy Environ. Sci.

277

124

View full text Add to dashboard Cite

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“…Atmospheric Data Assimilation and Parameterization Techniques (ADAPT) / Lagrangian Operational Dispersion Integrator (LODI) models. The ADAPT model was initialized with 0.25 deg resolution Global Forecast Model fields 27,28 . Our modeling resolved North American near-surface influences up to seven days after flights with a 30.8 km horizontal resolution.…”

Section: Taxonomy Identification Metagenomic Sequences Were Analyzedmentioning

confidence: 99%

Sierra Nevada sweep: metagenomic measurements of bioaerosols vertically distributed across the troposphere

Jaing

Thissen

Morrison

et al. 2020

Sci Rep

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To explore how airborne microbial patterns change with height above the Earth's surface, we flew NASA's C-20A aircraft on two consecutive days in June 2018 along identical flight paths over the US Sierra Nevada mountain range at four different altitudes ranging from 10,000 ft to 40,000 ft. Bioaerosols were analyzed by metagenomic DnA sequencing and traditional culturing methods to characterize the composition and diversity of atmospheric samples compared to experimental controls. The relative abundance of taxa changed significantly at each altitude sampled, and the diversity profile shifted across the two sampling days, revealing a regional atmospheric microbiome that is dynamically changing. the most proportionally abundant microbial genera were Mycobacterium and Achromobacter at 10,000 ft; Stenotrophomonas and Achromobacter at 20,000 ft; Delftia and Pseudoperonospora at 30,000 ft; and Alcaligenes and Penicillium at 40,000 ft. Culturebased detections also identified viable Bacillus zhangzhouensis, Bacillus pumilus, and Bacillus spp. in the upper troposphere. to estimate bioaerosol dispersal, we developed a human exposure likelihood model (7-day forecast) using general aerosol characteristics and measured meteorological conditions. By coupling metagenomics to a predictive atmospheric model, we aim to set the stage for field campaigns that monitor global bioaerosol emissions and impacts. Aerosols (mostly desert dust, black carbon and ocean spray) regularly disperse across the Pacific Ocean with springtime atmospheric winds-in fact, models suggest that as much as 64 Teragrams of Asian aerosols can be transported to North America annually 1. Past studies have reported microorganisms co-transported with globally-dispersed aerosols, and that both DNA signatures and viable cells can be detected in air masses 2-4. For example, thousands of taxonomic signatures were measured in springtime Asian dust plumes delivering free tropospheric bioaerosols to an alpine research station in central Oregon 3. In a separate flight project surveying airborne microorganisms in the western region of the United States, several taxa were found to be enriched in the upper atmosphere, including bacterial families Lachnospiraceae, Ruminococcaceae and Erysipelotrichaceae 2. Despite harsh conditions in the atmosphere, viable bacterial isolates were recovered from the same study 2 , including Bacillus sp., Micrococcus sp., Arthrobacter sp. and Staphylococcus sp. Previous aerobiology campaigns using aircraft were flown at single altitudes in order to refine collection methods and demonstrate some of the first measurements of an atmospheric microbiome 2,5-7. To date, there are only a few studies that have examined microbiological changes across a vertical gradient in Earth's troposphere 8-10. More studies using advanced genomic techniques such as shotgun metagenomic sequencing will be essential to formulating predictive models of bioaerosols and how the atmospheric microbiome is influenced by meteorological

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“…Atmospheric transport and dispersion models are generally considered to be accurate when they can reproduce individual measurements paired in time and space to within a factor of ten (or better) for a variety of different terrains, downwind distances, and environmental conditions [226], [227]. For example, one modeling system (which is used in this study) is the LLNL ADAPT/LODI diagnostic wind field and Lagrangian particle models [228], [229]. The LLNL ADAPT/LODI models have been validated against a wide range of source terms, environmental conditions, and downwind distances (0.05 to 1,500 km) [230]- [233].…”

Section: Atmospheric Dispersion Modelsmentioning

confidence: 99%

Particle Based Model for Airborne Disease Transmission

Dillon

2020

Preprint

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Prior literature documents cases of airborne infectious disease transmission at distances ranging from ≥ 2 m to inter-continental in scale. Physics- and biology- based models describe the key aspects of these airborne disease transmission events, but important gaps remain. This report extends current approaches by developing a new, single-particle based theory that (a) assesses the likelihood of rare airborne infections (where individuals inhale either one or no infectious particles) and (b) explicitly accounts for the variability in airborne exposures and population susceptibilities within a geographic region of interest. For these hazards, airborne particle fate and transport is independent of particulate concentration, and so results for complex releases can be determined from the results of many single-particle releases. This work is intended to provide context for both (a) the initial stages of a disease outbreak and (b) larger scale (≥ 2 m) disease spread, including distant disease "sparks" (low probability, unexpected disease transmission events that infect remote, susceptible populations). The physics of airborne particulate dispersion inherently constrains airborne disease transmission. As such, this work suggests results that, a priori, may be applicable to many airborne diseases. Model Predictions: i. Modeling predictions of the single-particle transmission kernel suggest that outdoor airborne disease transmission events may occur episodically as the infection probabilities can vary over many orders of magnitude depending on the distance downwind; specific virus, prion, or microorganism; and meteorological conditions. ii. Model results suggest that, under the right conditions, an indoor infected person could spread disease to a similar, or greater, number of people downwind than in the building they occupy. However, the downwind, per-person infection probability is predicted to be lower than the within-building, per-person infection probability. This finding is limited to airborne transmission considerations. iii. This work suggests a new relative disease probability metric for airborne transmitted diseases. This metric, which is distinct from the traditional relative risk metric, is applicable when the rate at which the infectious agent losses infectivity in the atmosphere is ≲ 1 h-1.

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Atmospheric Dispersion Modeling

Cited by 35 publications

References 10 publications

Worldwide health effects of the Fukushima Daiichi nuclear accident

Worldwide health effects of the Fukushima Daiichi nuclear accident

Sierra Nevada sweep: metagenomic measurements of bioaerosols vertically distributed across the troposphere

Particle Based Model for Airborne Disease Transmission

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