Characteristics and composition of the falling dust in urban environment

Al‐Harbi, Meshari

doi:10.1007/s13762-013-0440-8

Cited by 22 publications

(11 citation statements)

References 69 publications

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“…The occurrence of sandThis article is part of the Topical Collection on DUST * Neelamani Subramaniam nsubram@kisr.edu.kw size particles is attributed to pick up from local recent surface deposits. Kuwait encounters higher dust fall during June and August (Al-Harbi, 2015), and the value ranges from 76.4 to 97.6 t/ km 2 /month. The major portion of the falling dust contains water-insoluble matter, such as ash (63 %), silica (19 %), and combustible items (17.8 %), and the three main soluble matters are nitrate, sulfate, and chloride (Al-Harbi, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Kuwait encounters higher dust fall during June and August (Al-Harbi, 2015), and the value ranges from 76.4 to 97.6 t/ km 2 /month. The major portion of the falling dust contains water-insoluble matter, such as ash (63 %), silica (19 %), and combustible items (17.8 %), and the three main soluble matters are nitrate, sulfate, and chloride (Al-Harbi, 2015). For a country like Kuwait, the dust can enter from the surrounding countries depending upon the season and the dominant wind direction.…”

Section: Introductionmentioning

confidence: 99%

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Probability distribution and extreme value analysis of total suspended particulate matter in Kuwait

et al. 2015

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Probability distribution and extreme value analysis were carried out on total suspended particulate matter (TSP) in Kuwait. The measured TSP data, available for about 10 years from three different locations in Kuwait, viz., Managhesh, Shuwaikh, and Kuwait City were used. For probability distribution analysis, four theoretical distributions were considered, namely Rayleigh, exponential, Gumbel, and log-normal distribution. Based on the study, it was found that log-normal distribution represented the measured daily average TSP value in Kuwait. The expected extreme daily average TSP values for 10-, 25-, 50-, and 100-year return periods were estimated based on Gumbel, exponential, and Weibull extreme value distributions for these three locations. For 100-year return period, the expected TSP values in Managhesh were 5270, 5920, and 4584 μg/m 3 , based on Gumbel, exponential, and Weibull extreme value distributions, respectively. For the same return period, the expected TSP values in Shuwaikh were 11,255, 12, 592, and 8771 μg/m 3 , and in Kuwait City, 7109, 8136, and 6494 μg/m 3 , based on Gumbel, exponential, and Weibull extreme value distributions, respectively. During an extreme dust storm in Kuwait, an extreme TSP of 9619 μg/m 3 was recorded on 25 March 2011. The results of this study are an important input to understand the probability distribution of TSP and also for the analysis on the impact of TSP on the socioeconomic development and on the respiratory health issues in Kuwait.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probability distribution and extreme value analysis of total suspended particulate matter in Kuwait

et al. 2015

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“…A study in Shuwaikh city [68] showed a similar pattern of monthly deposition rate in the summer (July and August 2009). Conversely, in western Taiwan [69] and north western Spain [70], observations showed unusually high winter deposition rates .…”

Section: Mapping Seasonal Gdr and Role Of Climatementioning

confidence: 78%

Investigation of Aeolian Dust Deposition Rates in Different Climate Zones of Southwestern Iran

2021

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Dust and atmospheric particles have been described in southwestern Iran primarily in terms of load, concentration and transport. The passive deposition, however, has been discussed inadequately. Therefore, the relationships between different climate zones in southwestern Iran and dust deposition rates were quantified between 2014 and 2017 using both space- (second modern-era retrospective analysis for research and applications, version 2 reanalysis model) and ground-based (eolian ground deposition rate) tools. In addition, the surface meteorological records, including the wind patterns favoring the occurrence of dust events, were examined. A hot desert climate (BWh), hot semi-arid climate (BSh), and temperate hot and dry summer climate (Csa) were identified as the three dominant climate regions in the study area, exhibiting the highest average dust deposition rates. In this study, correlations between the most relevant climate patterns and deposition rate weather parameters were found to describe a region’s deposition rate when a dust event occurred. Based on these results, the BSh and Csa regions were found to be associated with the seasonal cycle of dust events in March, April, and May, revealing that in the long run meteorological conditions were responsible for the varying dust deposition rates. Relatively, precipitation and temperature were the two major factors influencing dust deposition rates, not wind speed. Moreover, the peak seasonal deposition rates in the spring and summer were 8.40 t km−2 month−1, 6.06 t km−2 month−1, and 3.30 t km−2 month−1 for the BWh, BSh, and Csa climate regions, respectively. However, each of these climate types was directly related to the specific quantity of the dust deposition rates. Overall, the highest dust deposition rates were detected over the years studied were 100.80 t km−2 year−1, 79.27 t km−2 year−1, and 39.60 t km−2 year−1 for BWh, BSh, and Csa, respectively.

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“…Numerous studies focused on the spatial and temporal variations of primary (SO 2 , PM 10 , NO 2 , and CO) and secondary (O 3 ) air pollutants [8][9][10][11][12]. Substantial seasonal differences and long-term trends of air pollutant levels have been noticed in several regions around the world [9][10][13][14][15][16]. Seasonal and trend disparities among cities could be due to several factors including the spreading of local pollution sources, the existence of distant pollution sources that influence the city, and the meteorological and topographical conditions of the area [17][18].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variations and source apportionment of NOx, SO2, and O3 emissions around heavily industrial locality

Al‐Harbi

Al-majed

Abahussain

2019

Environmental Engineering Research

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The main objective of this study is to estimate the levels of pollution to which the community is presently exposed and to model the regimes of local air quality. Diurnal, daily, and monthly variations of NO, NO2, SO2, and O3 were thoroughly investigated in three areas; namely, residential, industrial, and terminal in Ras Al-Khafji. There is obvious diurnal variation in the concentration of these pollutants that clearly follows the diurnal variation of atmospheric temperature and main anthropogenic and industrial activities. Correlation analysis showed that meteorological conditions play a vital role in shaping the pattern and transportation of air pollutants and photochemical processes affecting O3 formation and destruction. Bivariate polar plots, an effective graphical tool that utilizes air pollutant concentrations' dependence on wind speed and wind direction, were used to identify prevailing emission sources. Non-buoyant ground-level sources like domestic heating and street transport emissions, various industrial stacks, and airport-related activities were considered dominant emission sources in observatory sites. This study offers valuable and detailed information on the status of air quality, which has considerable, quantifiable, and important public health benefits.

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Characteristics and composition of the falling dust in urban environment

Cited by 22 publications

References 69 publications

Probability distribution and extreme value analysis of total suspended particulate matter in Kuwait

Probability distribution and extreme value analysis of total suspended particulate matter in Kuwait

Investigation of Aeolian Dust Deposition Rates in Different Climate Zones of Southwestern Iran

Spatiotemporal variations and source apportionment of NOx, SO2, and O3 emissions around heavily industrial locality

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