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    The 20–22 February 2016 mineral dust event in Tehran, Iran: numerical modeling, remote sensing, and In Situ measurements

    , Article Journal of Geophysical Research: Atmospheres ; Volume 123, Issue 10 , 27 May , 2018 , Pages 5038-5058 ; 2169897X (ISSN) Najafpour, N ; Afshin, H ; Firoozabadi, B ; Sharif University of Technology
    Blackwell Publishing Ltd  2018
    Wind erosion raises mineral dusts from dry and semidry lands and produces dust storms. Such dust masses have created numerous health and economic problems for the residents of southern, southwestern, and central parts of Iran. The main sources, movement, spread, and settlement of dust masses can be determined by solving the governing equations for aerosol transmission. Such information will be certainly useful in managerial decision-making. In this study, the dust event in Tehran on 20–22 February 2016 was studied using numerical model, Moderate Resolution Imaging Spectroradiometer satellite data, and data of ground-based stations. A comparison between the numerical results and in situ... 

    The Implementation of an Operational MODIS Aerosol Retrieval Algorithm at High Spatial Resolution

    , M.Sc. Thesis Sharif University of Technology Heidary, Parisa (Author) ; Tajrishy, Masoud (Supervisor)
    Urmia Lake is one of the largest permanent hypersaline lakes in the world. Since Urmia Lake is faced with drying phenomena, the release of dust from its surface is expected. The most appropriate technique on dust storms is the remote sensing technique. One of the most popular parameter that provides the integrated information over a vertical column of unit cross section of this phenomenon is aerosol optical depth (AOD). Satellite remote sensing has been used to retrieve AOD over land and ocean at spatial resolutions of several to several tens of km. However, higher spatial resolution aerosol products for local scale areas have not been well-researched mainly due to the difficulty of... 

    Zoning of Dust Hotspots and Investigation of their Formation Factors

    , M.Sc. Thesis Sharif University of Technology Mohandes Samani, Sara (Author) ; Tajrishy, Massoud (Supervisor)
    Identification of dust storm hotspots using high resolution 1 km MODIS Aerosol Optical Depth (AOD) data obtained by MAIAC algorithm for a region including Iran and its neighbors, is one of the objectives of the present study. By implementing three important statistics on AOD and averaging over the last decade time period (2009-2019), dust sources of Iran, Iraq, Syria, Saudi Arabia, Oman, Afghanistan, and Pakistan were specified. These statistics include frequency of occurrence AOD>0.3, mean and coefficient of variation of aerosol optical depth. The membership rank of source zones in the set of hotspot areas has been obtained by applying the fuzzy logic approach on the three mentioned layers.... 

    Monitoring Urmia Lake area variation using MODIS satellite data

    , Article World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress ; 2012 , Pages 1917-1926 ; 9780784412312 (ISBN) Sima, S ; Ahmadalipour, A ; Shafiee Jood, M ; Tajrishy, M ; Abrishamchi, A ; Environ. Water Resour. Inst. (EWRI) Am. Soc. Civ. Eng ; Sharif University of Technology
    ASCE  2012
    Urmia Lake is a large hyper-saline lake located in the northwest of Iran. It plays an important role in the hydrology, climate and ecology of its surrounding regions. In recent years, the water level of Urmia Lake has been dropped significantly. This study investigates the seasonal and annual variations of the lake area from 2000 to 2011 using remote sensing data. MODIS imageries of Normalized Differential Vegetation Index (NDVI) were used to extract the water surface area of the lake. Results reveal a significant decline in the lake area during the last past 12 years. Analysis of the seasonal images shows that maximum and minimum areas of Urmia Lake usually occur in winter and autumn,... 

    Newly desertified regions in Iraq and its surrounding areas: Significant novel sources of global dust particles

    , Article Journal of Arid Environments ; Volume 116 , May , 2015 , Pages 1-10 ; 01401963 (ISSN) Moridnejad, A ; Karimi, N ; Ariya, P. A ; Sharif University of Technology
    Academic Press  2015
    Using the newly developed Middle East Dust Index (MEDI) applied to MODIS satellite data, we consider a relationship between the recent desertified regions, over the past three decades, and the dust source points identified during the period of 2001-2012. Results indicate that major source points are located in Iraq and Syria, and by implementing the spectral mixture analysis on the Landsat TM images (1984 and 2012), a novel desertification map was extracted. Results of this study indicate for the first time that c.a., 39% of all detected source points are located in this newly anthropogenically desertified area. Using extracted indices for Deep Blue algorithm, dust sources were classified... 

    Estimating ground-level PM2.5 concentrations by developing and optimizing machine learning and statistical models using 3 km MODIS AODs: case study of Tehran, Iran

    , Article Journal of Environmental Health Science and Engineering ; Volume 19, Issue 1 , 2021 ; 2052336X (ISSN) Sotoudeheian, S ; Arhami, M ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Purpose: In this study we aimed to develop an optimized prediction model to estimate a fine-resolution grid of ground-level PM2.5 levels over Tehran. Using remote sensing data to obtain fine-resolution grids of particulate levels in highly polluted environments in areas such as Middle East with the abundance of brightly reflecting deserts is challenging. Methods: Different prediction models implementing 3 km AOD products from the MODIS collection 6 and various effective parameters were used to obtain a reliable model to estimate ground-level PM2.5 concentrations. In this regards, the linear mixed effect model (LME), multi-variable linear regression model (MLR), Gaussian process model (GPM),... 

    Estimating Particulate Matter (PM10) Concentration using Satellite data and Meteorological data from Synoptic Stations and WRF in Tehran

    , M.Sc. Thesis Sharif University of Technology Ghotbi, Saba (Author) ; Arhami, Mohammad (Supervisor)
    Detetrmination of particulate matter (PM), as one of the most important pollutants in big cities, requires extensive system of monitoring stations. Remotely sensed atmospheric data due to their large spatial coverage and frequent observations are emerging as an important addition to conventional ground based atmospheric monitoring. In this regards this study presents an approach to analyze the relationship between PM10 (particles with aerodynamic diameter less than 10 μm) and the satellite product of aresol optical depth (AOD), which is the measurement of the extinction of light due to interferences with particulate matter. In the current study AOD is observed by Moderate Resolution Imaging... 

    Developing Models to Estimate Ground Level PM2.5 Concentrations Using Satellite Measurements

    , Ph.D. Dissertation Sharif University of Technology Sotoudeheian, Saeed (Author) ; Arhami, Mohammad (Supervisor)
    In this study different prediction models including linear mixed effect (LME), multi-variable linear regression (MLR), gaussian process model (GPM), artificial neural network (ANN) and support vector regression (SVR) were developed using satellite AOD product - with spatial resolution of 3 km – coupled with various auxiliary parameters to estimate ground-level PM2.5 over Tehran. The influence of site effect term on performance of LME models was evaluated using random intercept for monitoring sites. Results showed LME models without this term were able to explain variabilities of PM2.5 in ranges of 60 – 66% and 35 – 41% during model fitting and cross-validation (CV), respectively. By... 

    Dust concentration over a semi-arid region: parametric study and establishment of new empirical models

    , Article Atmospheric Research ; Volume 243 , 1 October , 2020 Najafpour, N ; Afshin, H ; Firoozabadi, B ; Sharif University of Technology
    Elsevier Ltd  2020
    In recent years, the city of Tehran, Iran's capital, has encountered numerous dust events so that the dust concentration of PM10 has reached even more than 800 μg m−3. This emphasizes the importance of the statistical study of dust in Tehran and the development of correlations for estimating dust concentration of PM10. In the present study, by evaluating the data measured during dust observations over the years 2013–2016 in Tehran, new statistical models are established for estimating PM10 concentration in terms of horizontal visibility and MODIS AOD. Firstly, simple nonlinear regression models between dust concentration of PM10 and horizontal visibility as well as MODIS AOD are developed.... 

    Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

    , Article Atmospheric Environment ; Volume 141 , 2016 , Pages 333-346 ; 13522310 (ISSN) Ghotbi, S ; Sotoudeheian, S ; Arhami, M ; Sharif University of Technology
    Elsevier Ltd  2016
    Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable... 

    The application of MODIS satellite remote sensing in estimation of particulate urban air pollution

    , Article 100th Annual Conference and Exhibition of the Air and Waste Management Association 2007, ACE 2007, 26 June 2007 through 29 June 2007 ; Volume 2 , 2007 , Pages 736-742 ; 9781604238464 (ISBN) Torkian, A ; Amid, F ; Keshavarzi, H ; Sharif University of Technology
    Air and Waste Management Association  2007
    Particulate matter (PM) pollution is a growing concern in urban areas in the developing countries because of its potential to aggravate cardiovascular and respiratory illnesses. Traditional approaches in monitoring urban pollutants have relied on ground-based networks even though they essentially provide point measurements and are inadequate for health alerts on large spatial and long temporal scales. Recent advances in satellite imagery has attracted managers to look into this new alternative as a predictive tool for improving air quality at urban and regional scales by providing necessary data in advance of the onset of actual severe conditions. Moderate Resolution Imaging... 

    METRIC and WaPOR estimates of evapotranspiration over the Lake Urmia basin: Comparative analysis and composite assessment

    , Article Water (Switzerland) ; Volume 11, Issue 8 , 2019 ; 20734441 (ISSN) Javadian, M ; Behrangi, A ; Gholizadeh, M ; Tajrishy, M ; Sharif University of Technology
    MDPI AG  2019
    Evapotranspiration is one of the main components of water and energy balance. In this study, we compare two ET products, suitable for regional analysis at high spatial resolution: The recent WaPOR product developed by FAO and METRIC algorithm. WaPOR is based on ETLook, which is a two-source model and relies on microwave images. WaPOR is unique as it has no limitation under cloudy days, but METRIC is limited by clouds. METRIC and WaPOR are more sensitive to land surface temperature and soil moisture, respectively. Using two years (2010 and 2014) of data over Lake Urmia basin, we show that in most areas, ET from METRIC is higher than WaPOR and the difference has an ascending trend with the... 

    Correlation between concentrations of chlorophyll-a and satellite derived climatic factors in the Persian Gulf

    , Article Marine Pollution Bulletin ; Volume 161, Part A , December , 2020 Moradi, M ; Moradi, N ; Sharif University of Technology
    Elsevier Ltd  2020
    Monthly mean satellite derived Chl-a, aerosols, wind, SST, PAR, and turbidity datasets were used to investigate the possible factors regulating phytoplankton variability in the Persian Gulf. The spatial correlation analysis revealed two distinct regions of SST and PAR, and a relatively uniform spatial correlation pattern of the other parameters. The cross correlation between aeolian dusts and Chl-a was significantly positive with 1–3 months offset. The pattern of spatial correlation between Chl-a and SST was positive in the shallow regions without time lag, and was negative with time offset of 3–5 months in deeper regions. The cross correlation between Chl-a and north-ward winds were... 

    Mapping surface temperature in a hyper-saline lake and investigating the effect of temperature distribution on the lake evaporation

    , Article Remote Sensing of Environment ; Volume 136 , 2013 , Pages 374-385 ; 00344257 (ISSN) Sima, S ; Ahmadalipour, A ; Tajrishy, M ; Sharif University of Technology
    Remote sensing is an effective tool for capturing spatial and temporal variations of water surface temperature (WST) in large lakes. The WST of Urmia Lake in northwestern Iran was examined from 2007 to 2010, using MODIS land surface temperature (LST) products. Spatial and temporal (diurnal, monthly, seasonal and inter-annual) variations of Urmia Lake WST were also investigated. Results indicate that the MODIS-derived WSTs are in a good agreement with the in situ data (R2=0.92 and bias=-0.27). Spatial analysis of WST revealed that there are three thermal zones along the lake: the shallow region in barriers of the causeway, islands and the shoreline; the south part; and the deep north parts.... 

    The lake urmia environmental disaster in Iran: a look at aerosol pollution

    , Article Science of the Total Environment ; Volume 633 , 2018 , Pages 42-49 ; 00489697 (ISSN) Hossein Mardi, A ; Khaghani, A ; MacDonald, A. B ; Nguyen, P ; Karimi, N ; Heidary, P ; Karimi, N ; Saemian, P ; Sehatkashani, S ; Tajrishy, M ; Sorooshian, A ; Sharif University of Technology
    Lake Urmia (LU) once was the second largest hypersaline lake in the world, covering up to 6000 km2, but has undergone catastrophic desiccation in recent years resulting in loss of 90% of its area and extensive coverage by playas and marshlands that represent a source of salt and dust. This study examines daily Aerosol Optical Depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) between 2001 and 2015 over northwestern Iran, which encompasses LU. Intriguingly, salt emissions from the LU surface associated with ongoing desiccation do not drive the study region's AOD profile, whereas pollution transported from other regions and emissions around LU are more important....