Diagnostic Alarm of Dew Point Temperature for the Occurrence of Middle Eastern Dust Storms

Goudarzi, Gholamreza; Sorooshian, Armin; Alam, Khan; Weckwerth, Tammy M.; Hamid, Vafa; Maleki, Heidar

doi:10.1007/s00024-022-03182-x

Cited by 5 publications

(3 citation statements)

References 49 publications

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“…While monitoring density is considered important to reduce bias, no definition of an adequate density was stated in any of the papers reviewed related to ANNs. For example, despite the low number of stations used in the studies of Goudarzi et al (2022), 4 stations across 530 km 2 and Mirzadeh et al (2022), 3 stations across 2,491 km 2 , the accuracy of the forecasting was not considered compromised.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…The large monitoring area required in Australia makes it difficult to extrapolate these studies from the Northern Hemisphere. Bias associated with geography can be associated with the proximity of monitoring stations to urban areas and industrial emission hot spots (Chianese et al 2019;Goudarzi et al 2022) or simply the need for local geographic area calibration (Zhang, Patuwo and Hu 1998). Routinely, these were described as biases to be aware of and not constraints to operational use.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…ANN or satellite), often multiple tools supported the early warning process. For example, Pearson coefficient 4 analysis to find what meteorological parameters were important for dust storm prediction was conducted by Goudarzi et al (2022) (Leys et al 2008). Riley (2021) also described the New South Wales air quality network that send automatic alerts to registered people via email or SMS, providing information about actions to take.…”

Section: Is Australia Ready?mentioning

confidence: 99%

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Developing an Australian dust early warning system

Clark,

Strong

2024

AJEM

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In Australia, the perception of large continental-scale dust storms has traditionally been restricted to aspects of ‘inconvenience’ or ‘novelty’. However, as the climate changes, there is an increased likelihood of dust storm activity that puts communities at increased risk. The aim of this study was to explore the need and possibility of developing a dust early warning system for Australia. Through a scoping review of internationally used sand and dust early warning systems, we found that an array of systems exist or were theoretically tested in the Northern Hemisphere. The sensor networks, one of which was operational, were of particular interest because Australia already has an operational air quality network that could be expanded to a dust early warning system. The need for a trans-boundary system is critical for Australia and, therefore, requires a combined approach of expanded sensor network with satellite-based systems to increase validation of any future modelling approach. This improved understanding could inform the development of a dust warning system for multi-socio-economic factors that account for cumulative exposure to small, localised and large continental-sized dust events.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Is Australia Ready?mentioning

confidence: 99%

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Developing an Australian dust early warning system

Clark,

Strong

2024

AJEM

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Toxic heavy metals in rainwater samples of Tehran

Malekei,

Sayadi,

Behrooz

et al. 2023

J Atmos Chem

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This study investigates the concentrations and spatial distribution of toxic heavy metals (Cd, Cu, Pb and Zn) through chemical analysis of rainwater samples, characterized by different land use, emission sources, tra c conditions and population density. The average concentrations at the ve sites were 52.9, 11.8, 14.6 and 0.93 µg l − 1 for Zn, Pb, Cu and Cd, respectively. The concentrations for all heavy metals were signi cantly higher (p < 0.05) at the central and south Tehran areas compared to the west and north, due to different urban characteristics, higher pollution emission rates from tra c and domestic sectors, and local winds patterns developed within the city. High tra c load in the central part of Tehran also escalates the heavy metal concentrations in this region. The signi cant correlations between the studied heavy metals at the ve sites indicate common, local anthropogenic sources. The heavy metal concentrations were higher in spring than in winter, likely associated with dilution processes in winter and the restriction measures due to COVID-19 pandemic. During the lockdown period, a drastic decrease in tra c load was observed in Tehran, con rming that motor vehicles is the main regulatory factor for air pollution and potential toxic elements in the city. be high, indicating common origin from local anthropogenic sources, mainly from the tra c and industrial sectors.Analysis of heavy metals not only in street (road) and airborne dust samples, but also in rainwater (wet deposition) is very important for identi cation of their sources, distribution, solubility and bio-availability characteristics, which determine ecological and human health risks. Current results provided essential preliminary knowledge of rainwater chemistry in Tehran, helping in establishing regulation and mitigation strategies for better control of air pollution and toxic heavy metals. More systematic analysis of wet deposition in Tehran, Iran and in the Middle East is needed for better assessment of rain chemistry, as a way to investigate atmospheric composition. Declarations AcknowledgementThis article was supported by the University of Zabol (Iran) with grant code (IR-UOZ-GR-0088).

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