Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites

Dadashi-Roudbari, Abbasali; Ahmadi, Mehdi

doi:10.1007/s12517-020-5232-0

Cited by 18 publications

(8 citation statements)

References 81 publications

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“…The reason for the high concentration of PM 10 in 2015 is probably because of this phenomenon. Also, according to a study by Dadashi-Roudbari et al, the annual average AOD index from 2014 to 2015 has been increasing in the western provinces of Iran that it can be related to increasing in PM 10 concentration in these two years [52].…”

Section: Spatial-temporal Variations Of Pm 10 Concentrations In the S...mentioning

confidence: 98%

Ambient air particulate matter (PM10) satellite monitoring and respiratory health effects assessment

Mohebbichamkhorami

Arbabi

Mirzaei

et al. 2020

J Environ Health Sci Engineer

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Purpose Air particulate matter with an aerodynamic diameter of 10 µm or less (PM 10 ) is one of the main causes of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study explored the relationship between PM 10 by remote sensing and AECOPD in Chaharmahal-o-Bakhtiari province from 2014 to2018. Method PM 10 concentrations were predicted and validated based on aerosol optical depth (AOD) from 161 images processed by MODIS sensor and ground air quality monitoring station data. Demographic information and spirometric indices of 2038 patients with AECOPD were collected and analyzed from the hospital during the studied periods. SPSS software was used to analyze the relationships between these two categories of information. Results There was a significant negative relationship between PM10 and FVC, FVC%, FEV1, FEV1%, FEF25-75, FEV1/FVC, PEF, and FEF25FVC indices (p < 0.05). The results showed that over 2014-2018, the annual mean of PM10 concentrations varied from 35 to 52 µg/m3. The result of the regression model showed that the patient's age, body mass index (BMI), and PM 10 concentrations were the most affecting variables on the two important spirometric indices i.e., FVC% and FEV 1 %. The PM 10 concentrations and number of AECOPD patients had a similar pattern during the studied period. The women group, age group above 74 years, normal BMI, and non-smoking patients showed the most sensitivity to the PM 10 concentrations. Conclusions Our findings provide supplementary scientific information on PM 10 concentration related to the incidence of AECOPD and as a variable affecting the most important spirometry indicators by providing local decision-makers information needed to set a priority of air pollution control measures as well as health services.

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Section: Spatial-temporal Variations Of Pm 10 Concentrations In the S...mentioning

confidence: 98%

Ambient air particulate matter (PM10) satellite monitoring and respiratory health effects assessment

Mohebbichamkhorami

Arbabi

Mirzaei

et al. 2020

J Environ Health Sci Engineer

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“…Additionally, the slope of the mountain plays a crucial role in directing and accumulating dust over the lake. Dadashi-Roudbari et al (2020) [44] reported a negative correlation between dust dry deposition using MERRA-2 data and mountain height in Iran. The results demonstrate that dust dry deposition in the mountainous regions of the Zagros and Alborz ranges decreases with increasing altitude.…”

Section: Spatial Distribution Of Dustmentioning

confidence: 99%

“…Modern-Era Retrospective analysis for Research and Applications, version 2, also known as MERRA-2, has been widely used in dust research worldwide [35][36][37][38][39][40][41][42] and in Iran [43][44][45][46] in recent years.…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Variability of Dust in the Urmia Basin, 1990–2019

Mobarak Hassan,

Fattahi,

Habibi

2023

Atmosphere

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The living conditions in the Urmia Basin (northwestern Iran) face significant challenges due to dust events. This study investigates the spatial and temporal characteristics of dust phenomena in the Urmia Basin using MERRA-2 data and observational data from Tabriz, Urmia, Sarab, and Mahabad over a 30-year period (1990–2019). The findings reveal that despite several fluctuations, the annual number of dusty days increased from the 1990s to the 2010s in the Urmia Basin. The maximum number of dusty days was found to predominantly occur in May (spring) and October (autumn), driven by two distinct mechanisms. In early autumn, developing synoptic systems associated with increased wind speeds can cause dust emission from dry land sources. Consequently, an increase in dust wet deposition, precipitation, dust surface concentration, and the number of dusty days occurs in October. In contrast, a sharp decrease in precipitation from April to May leads to drying soil and dust emission in May. Among the studied cities, Tabriz experienced the highest number of dusty days (728) due to the combined effects of cross-border and local dust sources. The highest dust column density and dust dry deposition in the south and east of Urmia Lake indicate the impact of declining water levels, which resulted in a dry lakebed as the primary local dust source. The MERRA-2 spatial distribution reveals that dust surface concentration, and the number of dusty days decrease similarly from the southwest to the northeast of the Urmia Basin as the distance from cross-border dust sources increases. A positive correlation is observed between the number of dusty days and MEERA-2 data, including dust surface concentration, dust dry deposition, column mass dust, and total aerosol extinction, with coefficients of 0.74, 0.71, 0.69, and 0.68, respectively.

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“…The use of the Sen method is appropriate for evaluating trends in time series as it is not affected by outliers and gaps, making it a common method in literature (e.g. Buffoni et al, 1999;Da Silva et al, 2010;Dadashi-Roudbari and Ahmadi, 2020;Kodera et al, 2008;Kuo et al, 2020;Olmo & Alados-Arboledas, 1995;Zou et al, 2016). To perform these calculations the kbtau.m software developed by Jeff Burkey (Mann-Kendall Tau-b with Sen's Method (Enhanced), 2020) was used.…”

Section: Trend Analysismentioning

confidence: 99%

Aerosol radiative effects in photosynthetically active radiation and total irradiance at a Mediterranean site from an 11-year database

Lozano

Sánchez-Hernández

Guerrero-Rascado

et al. 2021

Atmospheric Research

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Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites

Cited by 18 publications

References 81 publications

Ambient air particulate matter (PM10) satellite monitoring and respiratory health effects assessment

Ambient air particulate matter (PM10) satellite monitoring and respiratory health effects assessment

Temporal and Spatial Variability of Dust in the Urmia Basin, 1990–2019

Aerosol radiative effects in photosynthetically active radiation and total irradiance at a Mediterranean site from an 11-year database

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