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Sprigg, W.A. (2016) Dust Storms, Human Health and a Global Early Warning System

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Sprigg, W.A. (2016) Dust Storms, Human Health and a Global Early Warning System

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Abstract

Arid regions, the source of most airborne mineral dusts, comprise a third of the Earth’s land surface, where some two billion people are exposed daily to the fine particles raised by wind. Crossing political borders and travelling on air currents around the world, these particles not only affect the health of local communities, but also put many other populations extant at risk for cardiovascular and respiratory illnesses and a host of other health problems. Risks of exposure are affected by climatic conditions and their local and regional weather characteristics. And today, because of advancements in science and technology we are at the threshold of significantly reducing these health problems. Examples of meningitis, asthma and Valley fever are used to illustrate how risks may be lowered through a Dust-Health Early Warning System. A little more than a half-century of dedicated measurements of particulate air quality and of environmental science enhanced by Earth-orbiting satellites reveal the truth of airborne dust extent, and much of its variability in time and space. These truths have been essential in advancing numerical, dynamical models of the atmosphere that mimic and predict weather systems that loft the airborne dusts that medical sciences and epidemiology are proving harmful. This union of scientific disciplines and services makes possible today a means to improve public health around the world through a Global Dust-Health Early Warning System.

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... It is also one of the main reasons for growing desertification and the building up of dust storm events in these regions. The wind erosion leads to the building up of dust storms causing enormous health problems like asthma attacks, bronchitis, and other lung diseases from the emission of fine-grained airborne soil particles (PM2.5, PM10) in the air during the transportation phase of the soil (Goudie, 2014;Middleton, 2017;Sprigg, 2016). Different methods have been proposed for wind erosion control and mitigation, such as mechanical methods (Sand fences and barriers), agronomic methods (Vegetation cover), and chemical sand fixing methods (Goudie and Middleton, 2006). ...
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A number of models for real-time predicting of the atmospheric dust life cycle has been developed over recent years. Driven by atmospheric models, they are capable to predict dust process with generally reasonable accuracy. Components of an operational regional dust forecasting model will presented in more details. However, there are several aspects that limit dust models to further improve the quality of dust forecasts. Research areas that offer new dust modeling developments will be discussed. For example, significant improvements could be expected by model assimilation of lidar-based observations. Another promising application is improved treatment of dust-productive soil sources, (including their seasonal variability) by use of very high-resolution data on vegetation cover and soil features. Being coupled on-line and with two-way dust-radiation feedback interactions with the atmospheric model drivers, future dust models will be capable to improve conventional weather forecasts as well. The approach of such model coupling will be elaborated, considering it as a component of future more complex integrated environmental modelling systems.
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Reports of coccidioidomycosis are on the rise in the southwestern US. However, the ecology of the pathogen, Coccidioides, remains obscure and there is limited knowledge of the environmental antecedents of disease outbreaks. Detection of the fungus in the environment remains a critical challenge to modeling the source of disease. Using BALB/c mice as a biosensor, 8.9% of soils analyzed from the Tucson area (Pima County, Arizona) were found to contain the pathogen. The genotypes of 66 Coccidioides strains, recovered from 11 soils, were determined with diagnostic microsatellite loci. Comparison of these genotypes to clinical isolates revealed all were Coccidioides posadasii and they grouped with Arizona isolates. Among sites where multiple strains were recovered, two indicated a clonal population, while others yielded a diversity of genotypes. A secondary goal of this research was to assess applicability of PCR, with its potential for high-throughput screening, as a method for identifying Coccidioides-containing soils.
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Dust storms are common during the summer season over the Indo-Gangetic basin and are considered to be a major health hazard to millions of people living in the basin. In countries like India, there is no early warning made for dust outbreaks and as a result the day-to-day life is affected by these dust events. In this paper, efforts have been made to utilize multi sensor data to study the char-acteristics of dust storms. Moderate Resolution Imaging Spectroradiometer and Multiangle Imaging SpectroRadiometer images clearly show dust storm events over the Indo-Gangetic basin. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index and the Advanced Microwave Sounding Unit (AMSU) data over the western end of the Indo-Gangetic basin have been analyzed. These data show characteristic behavior of brightness temperature and Aerosol Index due to dust, which change significantly as dust migrates towards east over Kanpur. The TOMS Aerosol Index and the AMSU brightness temperature (T b) show a characteristic anti-correlation, which confirms the presence of a dust storm over Indo-Gangetic basin.
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Saharan dust intrusions make a major contribution to levels of particulate matter (PM) present in the atmosphere of large cities. We analysed the impact of different PM fractions during periods with and without Saharan dust intrusions, using time-series analysis with Poisson regression models, based on: concentrations of coarse PM (PM10 and PM10-2.5) and fine PM (PM2.5); and daily all-, circulatory- and respiratory-cause hospital admissions. While periods without Saharan dust intrusions were marked by a statistically significant association between daily mean PM2.5 concentrations and all- and circulatory-cause hospital admissions, periods with such intrusions saw a significant increase in respiratory-cause admissions associated with fractions corresponding to PM10 and PM10-2.5.
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Exposure to fine particulate matter (PM) is generally acknowledged to increase risk for human morbidity and mortality. However, particulate matter (PM) research has generally examined anthropogenic (industry and combustion by-products) sources with few studies considering contributions from geogenic PM (produced from the Earth by natural processes, e.g., volcanic ash, windborne ash from wildfires, and mineral dusts) or geoanthropogenic PM (produced from natural sources by processes that are modified or enhanced by human activities, e.g., dusts from lakebeds dried by human removal of water, dusts produced from areas that have undergone desertification as a result of human practices). Globally, public health concerns are mounting, related to potential increases in dust emission from climate related changes such as desertification and the associated long range as well as local health effects. Recent epidemiological studies have identified associations between far-traveled dusts from primary sources and increased morbidity and mortality in Europe and Asia. This paper provides an outline of public health research and history as it relates to naturally occurring inorganic mineral dusts. We summarize results of current public health research and describe some of the many challenges related to understanding health effects from exposures to dust aerosols.
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An alternative approach to the design of nonhydrostatic numerical weather prediction (NWP) models is presented. Instead of extending mesoscale nonhydrostatic modeling concepts to the synoptic scales and beyond, a hydrostatic NWP model using the mass-based σ vertical coordinate has been extended to include the nonhydrostatic motions, preserving the favorable features of the hydrostatic formulation. In order to do so, the system of nonhydrostatic equations was split into two parts: (a) the part that corresponds to the hydrostatic system, except for higher-order corrections due to the vertical acceleration, and (b) the system of equations that allows computation of the corrections appearing in the first system due to the vertical acceleration. This procedure does not require any linearization or approximation. With this approach, the nonhydrostatic dynamics has been introduced through an add-on nonhydrostatic module. The separation of the nonhydrostatic contributions shows in a transparent way where, how, and to what extent relaxing the hydrostatic approximation affects the hydrostatic equations. The nonhydrostatic module can be turned on and off depending on resolution, so that the model can be run in the hydrostatic mode at lower resolutions with no extra cost. This also allows easy comparison of hydrostatic and nonhydrostatic solutions obtained using otherwise identical model. The nonhydrostatic model developed appears to be computationally robust at all resolutions and efficient in NWP applications. With the current coding, the extra computational effort needed due to the nonhydrostatic extension is of the order of 20% of that required by the hydrostatic dynamics, both in terms of computer time and memory. Compared to the hydrostatic version of the model, no additional computational boundary conditions are needed in real data runs. At lower resolutions, in the hydrostatic limit, the forecasts of traditional meteorological parameters obtained using the hydrostatic and the nonhydrostatic modes are almost indistinguishable. The model also demonstrated the presence of important two-dimensional nonhydrostatic effects at very high horizontal resolutions. At these scales, the nonhydrostatic model was generally more robust than the hydrostatic one and produced smoother solutions. The impact of the nonhydrostatic dynamics appears to be weak at the horizontal resolutions of about 8 km. However, a visible effect on the orographic precipitation was detected. In addition to that, the nonhydrostatic deviation of pressure made a significant small-scale contribution to the pressure gradient force at places. The proposed approach appears well suited for models designed for a wide range of horizontal resolutions, and in particular for unified global and regional forecasting systems. Being developed from an existing model, the new model requires only minimal changes to the existing preprocessing and postprocessing infrastructure.
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This paper discusses some of the differences between online and offline approaches for both air quality forecasting and numerical weather prediction, and argues in favor of an eventual migration to integrated modeling systems that allow two-way interactions of physical and chemical processes. Recent studies are used that directly compared online and offline simulations to discuss possible shortcomings for both air quality and weather forecasting. The disadvantages of offline approaches are easy to show for air quality forecasting. On the other hand, a positive impact on short to medium range weather forecasts that is significant enough to justify an implementation at operational weather forecasting centers is more difficult to prove, and may initially only come through an improvement of the meteorological data assimilation. Eventually though, a migration to an integrated modeling system will provide new opportunities for weather prediction modelers as well. The simulation of chemical species will allow identification of shortcomings in currently used forecast models as well as lead to better use of meteorological data assimilation.
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Arid areas in the Arabian Peninsula are one of the largest sources of global dust, yet there is no data on the impact of this on human health. This study aimed to investigate the impact of dust storms on hospital admissions due to asthma and all respiratory diseases over a period of 5 years in Kuwait. A population-based retrospective time series study of daily emergency asthma admissions and admissions due to respiratory causes in public hospitals in Kuwait was analyzed in relation to dust storm events. Dust storm days were defined as the mean daily PM(10)>200 μg/m(3) based on measurements obtained from all six monitoring sites in the country. During the five-year study period, 569 (33.6%) days had dust storm events and they were significantly associated with an increased risk of same-day asthma and respiratory admission, adjusted relative risk of 1.07 (95% CI: 1.02-1.12) and 1.06 (95% CI: 1.04-1.08), respectively. This was particularly evident among children. Dust storms have a significant impact on respiratory and asthma admissions. Evidence is more convincing and robust compared to that from other geographical settings which highlights the importance of public health measures to protect people's health during dust storms and reduce the burden on health services due to dust events.