Atmospheric analysis of dust storms in Sistan region

A review of literature on the impact of dust and sand storms on the air transport operation is presented. Observational data on dust storms at the aerodromes of European Russia for the period of 2001-2019 are analyzed. The seasonal variations in dust transport episodes at aerodromes and its relationship with visibility changes are discussed. The characteristics of dusty air masses and advection are given. It is concluded that the frequency of dust transfer episodes for the aerodromes under study has decreased over the past five years, except for Gumrak aerodrome (Volgograd). Keywords: dust storm, sand storm, aviation, visibility, seasonal variations, aerodrome оf European Russia

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Justification for Unscheduled Maintenance of Solar Panels Used as a Power Supply for Sprinkler Machines

Elektrotekhnologii i elektrooborudovanie v APK ◽

10.22314/2658-4859-2020-67-1-16-21 ◽

2020 ◽

Vol 67 (1) ◽

pp. 16-21

Author(s):

Sergey M. Bakirov ◽

Sergey S. Eliseev

Keyword(s):

Power Supply ◽

Power Loss ◽

Renewable Energy Sources ◽

Operating Mode ◽

Dust Storms ◽

Research Purpose ◽

Solar Panels ◽

Solar Module ◽

Empirical Observation ◽

Modern Level

The modern level of agriculture is described by the introduction of renewable energy sources. New generation sprinkler machines are being put into production, in the power system of which solar panels are used. One of the factors that negatively affect the performance of solar cells in an open field is their dusting, which is formed as a result of dust storms and wind. Cleaning of the battery panels is carried out in various ways: manual, semi-automatic and automatic. Dust cleaning is included in maintenance. (Research purpose) The research purpose is to determine the conditions for performing the maintenance, which consists in cleaning solar panels in the field. (Materials and methods) Theoretical (analysis, hypothesis design), empirical (observation, testing), experimental (ascertaining experiment) methods has been used during research. (Results and discussion) The article describes an introduced parameter for estimating the level of dusting. The power loss indicator shows the ratio of the power of the dusted module to the power of the clean module. Unscheduled maintenance is affected by the distance of the solar module from the repair point, the power of the solar module, the loss from dusting, the frequency of maintenance and cost indicators. (Conclusions) It has been found the dependence of maintenance period of the solar module of the sprinkler machine on the distance to the sprinkler machine, to the point of maintenance and repair, the power loss coefficient in case of dusting of the solar module, the cost of performing maintenance, as well as the frequency of maintenance. Article describes the boundaries of the choice of operating mode of the sprinkler between unscheduled maintenance for cleaning the solar module and the acceptance of additional power of the sprinkler power supply system according to the criterion of minimum operating costs.

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Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland

Remote Sensing ◽

10.3390/rs13132433 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2433

Author(s):

Shu Yang ◽

Fengchao Peng ◽

Sibylle von Löwis ◽

Guðrún Nína Petersen ◽

David Christian Finger

Keyword(s):

Machine Learning ◽

Weather Conditions ◽

Dust Storms ◽

Machine Learning Algorithms ◽

Lidar Data ◽

Data Sets ◽

Doppler Lidar ◽

Lidar Measurements ◽

Using Data ◽

Filter Noise

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.

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Global Health Impacts of Dust Storms: A Systematic Review

Environmental Health Insights ◽

10.1177/11786302211018390 ◽

2021 ◽

Vol 15 ◽

pp. 117863022110183

Author(s):

Hamidreza Aghababaeian ◽

Abbas Ostadtaghizadeh ◽

Ali Ardalan ◽

Ali Asgary ◽

Mehry Akbary ◽

...

Keyword(s):

Public Health ◽

Systematic Review ◽

Respiratory Health ◽

Dust Storms ◽

Health Impacts ◽

Public Health Issue ◽

Emergency Medical Dispatch ◽

Significant Public Health ◽

English Articles

Background: Dust storms and their impacts on health are becoming a major public health issue. The current study examines the health impacts of dust storms around the world to provide an overview of this issue. Method: In this systematic review, 140 relevant and authoritative English articles on the impacts of dust storms on health (up to September 2019) were identified and extracted from 28 968 articles using valid keywords from various databases (PubMed, WOS, EMBASE, and Scopus) and multiple screening steps. Selected papers were then qualitatively examined and evaluated. Evaluation results were summarized using an Extraction Table. Results: The results of the study are divided into two parts: short and long-term impacts of dust storms. Short-term impacts include mortality, visitation, emergency medical dispatch, hospitalization, increased symptoms, and decreased pulmonary function. Long-term impacts include pregnancy, cognitive difficulties, and birth problems. Additionally, this study shows that dust storms have devastating impacts on health, affecting cardiovascular and respiratory health in particular. Conclusion: The findings of this study show that dust storms have significant public health impacts. More attention should be paid to these natural hazards to prepare for, respond to, and mitigate these hazardous events to reduce their negative health impacts. Registration: PROSPERO registration number CRD42018093325

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Dust Transport from Inland Australia and Its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm

Atmosphere ◽

10.3390/atmos12020141 ◽

2021 ◽

Vol 12 (2) ◽

pp. 141

Author(s):

Emilie Aragnou ◽

Sean Watt ◽

Hiep Nguyen Duc ◽

Cassandra Cheeseman ◽

Matthew Riley ◽

...

Keyword(s):

Air Quality ◽

Dust Storm ◽

New South ◽

New South Wales ◽

The State ◽

Dust Storms ◽

Eastern Coast ◽

Storm Event ◽

South Wales ◽

Dust Storm Event

Dust storms originating from Central Australia and western New South Wales frequently cause high particle concentrations at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affected air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model—Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in the WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints, namely mortality, respiratory and cardiac disease hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. Generally, the health impact is similar in order of magnitude to that caused by biomass burning events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory disease hospitalisation for this dust event (161) compared to the fire event (24).

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Analysis of some factors related to dust storms occurrence in the Sistan region

Environmental Science and Pollution Research ◽

10.1007/s11356-021-13922-6 ◽

2021 ◽

Author(s):

Soodabeh Namdari ◽

Khalil Valizadeh Kamran ◽

Armin Sorooshian

Keyword(s):

Dust Storms

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Cloud Masks Derived from the Mars Daily Global Maps and an Application to the Tropical Cloud Belt on Mars

Geosciences ◽

10.3390/geosciences11080324 ◽

2021 ◽

Vol 11 (8) ◽

pp. 324

Author(s):

Huiqun Wang ◽

Gonzalo González Abad

Keyword(s):

Processing Technique ◽

Oscillatory Behavior ◽

Early Summer ◽

Dust Storms ◽

Transitional Period ◽

Image Processing Technique ◽

Kelvin Wave ◽

Blue Channel ◽

Zonal Wavenumber ◽

Shift Pattern

An image processing technique is used to derive cloud masks from the color Mars Daily Global Maps (MDGMs) that are composed from the Mars Reconnaissance Orbiter (MRO) Mars Color Imager (MARCI) wide-angle image swaths. The blue channel of each MDGM is used to select cloud candidates and the blue-to-red ratio map is compared with a reference ratio map to filter out false positives. Quality control is performed manually. The derived cloud masks cover 1 Mars year from the summer of Mars year (MY) 28 to the summer of MY 29. The product has a 0.1° longitude by 0.1° latitude resolution and is available each day. This makes it possible to characterize the evolution of the tropical cloud belt from several new perspectives. The tropical cloud belt steadily builds up during northern spring and early summer, peaks near the early- to mid-summer transitional period, and rapidly declines afterward. From the perspective of cloud occurrence frequency and time mean, the cloud belt appears meandrous and zonally discontinuous, with minima in the Amazonis Planitia and Arabia Terra longitudinal sectors. A pronounced cloud branch diverges from the main cloud belt and extends from the Valles Marineris towards the Noachis and Hellas region. The cloud belt exhibits noticeable oscillatory behavior whereby cloud brightening alternates between the western and eastern hemispheres near the equator with a periodicity between 20 and 30 sols. The cloud belt oscillation occurred each Mars year around Ls = 140°, except for the Mars years when intense dust storms made disruptions. The phenomenon appears to be associated with an eastward propagating equatorial Kelvin wave with zonal wavenumber 1. This wave has a much longer wave period than the diurnal and semidiurnal Kelvin waves discussed in most of the previous studies and may be an important factor for the intra-seasonal variability of the tropical cloud belt. The convolution of clouds’ local time variation with MRO’s orbit shift pattern results in a seemingly highly regular 5-day traveling wave in Hovmöller diagrams of cloud masks.

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