Elham Pourmaafi Esfahani; Ali Almodaresi; Mohammad Mousaei Sanjerehei; Hamed Hghparast
Abstract
Introduction: Today, dust phenomena are among the most important environmental hazards and pose a serious threat to human health and the environment. Dust in barley as one of the pollutants has various adverse effects and negative consequences, among which can be reduced growth and yield of agricultural ...
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Introduction: Today, dust phenomena are among the most important environmental hazards and pose a serious threat to human health and the environment. Dust in barley as one of the pollutants has various adverse effects and negative consequences, among which can be reduced growth and yield of agricultural products, intensification of damage caused by pests and plant diseases, increased road accidents due to reduced visibility, The cancellation of flights and the resulting financial losses, increased treatment costs, closure of industrial units, pollution of water resources, increased erosion of buildings, decreased efficiency of solar photovoltaic systems due to turbidity.Objective: Therefore, due to the importance of dust and in order to predict how dust is spread, the artificial neural network model was used. This model can be useful and cost-effective information for future implementation of air pollution control strategies and cost reduction.Material and methods: To model the dust distribution using artificial neural network model, statistics and meteorological information of Kashan synoptic station, which were recorded daily by the Environment Department in 1996, were used. The proposed neural network model has four input layers that include humidity, temperature, wind speed, wind direction and an output layer, the daily concentration of suspended particles is 2.5 micrometers per cubic meter. The model training process was performed using multilayer perceptron neural network and post-diffusion rule and using sigmoid membership function in Matleb software environment. In the neural network model, the number of neurons in the hidden layer and the appropriate number of rounds or IPAC to achieve the best neural network structure, with the least error for each model, were determined using trial and error. The number of neurons and apex for the model in 2017 is 15 and 37,000, respectively.Results and discussion: The correlation coefficient of the model for predicting PM2.5 concentration is equal to 0.80 which is obtained by comparing real data with simulated data. The validation results of the model with real data are close to 80%, so the neural network model can be used to predict PM2.5 concentration. According to the average regression diagram, the predicted values obtained from the model are closer to the diagonal axis and have no dispersion. Also, based on the results of the step-by-step regression method, it was determined that among the four variables used for relative humidity modeling, it has the most impact and importance in dust emission modeling.Conclusion: According to the accuracy and the results, this method can be used to predict the air pollution of Kashan caused by suspended particles. Due to the high capability of the perceptron neural network in predicting the concentration and distribution of dust, the application of this model can be a suitable and fast solution for predicting the amount and spread of dust.
Elahe Ghasemi; Alireza Taab; Emanuele Radicetti
Abstract
Introduction: Dust is an atmospheric pollutant that is considered as one of the major environmental problems all over the world. This phenomenon is problematic, especially in agriculture, health, and transportation sections. Dust causes considerable environmental problems for agriculture and human health ...
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Introduction: Dust is an atmospheric pollutant that is considered as one of the major environmental problems all over the world. This phenomenon is problematic, especially in agriculture, health, and transportation sections. Dust causes considerable environmental problems for agriculture and human health in Iran every year and so attention must be paid to the negative consequences of this phenomenon. Therefore, this study was conducted to quantify the effects of dust on growth and yield of red bean, weeds growth, and the competitive balance between weeds and the crop. Material and methods: A greenhouse experiment was conducted in a replacement series based on a complete randomized design with three replicates in Ilam University, Ilam, from late October 2017 to early March 2018. The treatments consisted of soil dust (with and without), two weed species (Echinochloa crus-galli and Chenopodium album), and mixtures of 100% crop, 75% crop+25% weed, 50% crop+50% weed, 25% crop+75%weed, and 100% weed. The speed of photosynthesis, amount of chlorophyll α, chlorophyll b, total chlorophyll and carotenoids content of leaves, number of pod per plant, one thousand seed weight, and crop seed yield, crop and weed biomass were measured. Results and discussion: The results showed that the speed of photosynthesis amount of chlorophyll α, chlorophyll b, total chlorophyll content of leaves, carotenoids, number of pod per plant, one thousand seed weight, biomass, and seed yield of the red bean as well as biomass of weeds were significantly affected by dust. In addition, the effect of weeds on crops was increased by an increase in the weed proportion in the mixtures, which was worsening by the dust. The dust caused a 39.7% reduction in the yield and 52.8% in biomass of bean on average. The bean yield (gr/plant) in the 50% mixture in competition with C. album with and without dust effect were 7.5 and 4.7 gr/plant, respectively, while the corresponding values for E. crus-galli were 16.9 and 8.4 gr/plant , respectively. On the other hand, E. crus-galli as a narrow leave species was less affected by dust than C. album as a broad leave species and thus biomass reduction due to dust in C. album and E. crus-galli were 10.6% and 7.1% in comparison with the control , respectively. Moreover, the red bean was affected by dust more than weeds. Conclusion: The growth and yield of red bean were significantly affected by competition with weeds and also the competitive effect of C. album was more than E. crus-galli. In addition, the dust had significant effects on the growth of red bean and weeds (C. album more than E. crus-galli). This might be due to the morphological characteristics of each species, because the broader leaves of the red bean and C. album may have caused more absorption of dust particles. In general, the dust phenomenon caused a reduction in crop growth and yield and also affected the competitive balance between weeds and crops.
Faezeh Alizadeh; Samereh Falahatkar; Afsaneh Afzali
Abstract
Introduction: In the past three decades, dust has become a global concern for global societies. Due to Iran’s location in an arid region, it is severely influenced by this phenomenon. This phenomenon usually carries a huge mass of particle matters that can be clearly detected by satellite images. ...
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Introduction: In the past three decades, dust has become a global concern for global societies. Due to Iran’s location in an arid region, it is severely influenced by this phenomenon. This phenomenon usually carries a huge mass of particle matters that can be clearly detected by satellite images. The purpose of the present study was to investigate the time series changes of absorbing aerosol index using satellite images at a national scale. Material and methods: In order to study the trend of monthly changes in dust phenomena in Iran, the data of Absorbing Aerosol Index (AAI) of SCIAMACHY sensor, which was taken during 2002-2012, and GOME-2 during 2007-2017 were evaluated using non-parametric Man-Kendall test. The variation rates for different sectors were estimated using Theil-Sen slope. Results and discussion: The results showed an increasing trend in the western, southwest, center, and northeastern regions of Iran during 10 years based on Z statistics SCIAMCHY. The results also showed an increasing trend of GOME-2 Aerosol Absorbing Index in some parts of Markazi, Isfahan, Hamedan, and Fars provinces, and Lake Urmia and completely in Chaharmahal & Bakhtiari, and Kohgilouyeh & Boyerahmad provinces. Also, Golestan and Semnan provinces didn’t show any specific trends. According to P statistic, the trend of change in most regions of Iran was significant. Based on the results of Theil-Sen slope, the western, southern and central regions of Iran showed the most changes in atmospheric aerosol concentration. Conclusion: The high compatibility between the present results and the reports of meteorological stations showed the high capability of satellite data, which we used in this study, in order to identify the areas that encountered to dust phenomenon at a national scale. Accordingly, it is recommended that this technology be used for the macro-management of the natural resources in Iran.
Mehdii Jafari; Gholamreza Zehtabian; Hasan Ahmadi; Tayebeh Mesbahzadeh; Ali Akbar Norouzi
Abstract
Introduction: The phenomenon of dust in Iran is a serious risk that caused major problems for the environment and human health. Research has shown that the frequency and severity of these storms have increased in recent years. In addition, numerical weather models alone are not capable of storm detection, ...
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Introduction: The phenomenon of dust in Iran is a serious risk that caused major problems for the environment and human health. Research has shown that the frequency and severity of these storms have increased in recent years. In addition, numerical weather models alone are not capable of storm detection, which requires the use of dust detection methods based on data remote sensing. The purpose of this research was to analyze the statistical data and identify the days with dust, the source of dust entering the Isfahan area, and identify the route of its movement. Material and methods: For data analysis of dust, data from dust collecting data was collected from the selected station in the study area with a suitable statistical period from the meteorological organization on a daily basis for 8 hours, in the form of special codes for the period of 2010 to 2013, which were processed and analyzed using statistical methods. In order to zoning the dust abundance in the province, the IDW method was used to interpolate and transform point-to-area data. The dispersion zonation map for the 2010-2013 period was mapped using the GIS software. In order to visualize the dust phenomenon, after the geometric correction of the images, the radian values of the images were converted to brightness temperature using the Planck function. Corrections and processing of images were done in ENVI software. Due to the large influence of dust particles on the reflection and brightness temperature of the 31 and 32 bands of the material, the difference between the two bands' brightness was used to represent the dust mass. Also, to prevent the detection of cloud areas, the threshold of 290 K was applied to the 12-micron range. HYSPLIT Lagrangian model was used to trace the dust particles' path. Results and disscussion: The results of this study indicated that a total of 1467 days of dust phenomena were reported for selected stations from 2010 to 2013, in which the Naein station was the largest with 634 days and the Kashan station had the least frequency of dust with 50 days. The results also indicated the greatest frequency percentage occurred in May, June and April and the lowest frequency percentages in December and January. The frequency of monthly dust data showed that 44.57% of the total dust incidence occurred in April, May and June and 32.4% in December and January. Accordingly, it can be concluded that monthly dust changes occur frequently in the region consistent with the regional climate during all months of the year. The zoning results showed that during the study period, the southeast of the province, especially Naien station, had the highest incidence of dust. The application of brightness temperature and temperature threshold in order to separate the dust from the terrain, especially in areas with backlight, was helpful in the detection of dust. The results of the tracking showed that the main route for the transfer of dust to the studied area was southwest-northeast. Conclusion: In general, according to satellite images on the first and the peak day of dust, the main sources of dust in the region were northern Arabian deserts. Based on the results obtained from image processing and the output of the model, the northern part of Saudi Arabia and the southwest-northeast route were the origin and main route of dust entering Isfahan.
Azar Faryabi; Hamid Reza Matinfar; Seyyed Kazem Alavi Panah; Ali Akbar Norouzi
Abstract
Introduction: A dust aerosol index (DAI) algorithm based on measurements in deep blue (412 nm), blue (440 nm), and shortwave IR (2130 nm) wavelengths using Moderate Resolution Imaging Spectroradiometer (MODIS) observations has been developed. Measurements made in the short-wavelength segment, such as ...
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Introduction: A dust aerosol index (DAI) algorithm based on measurements in deep blue (412 nm), blue (440 nm), and shortwave IR (2130 nm) wavelengths using Moderate Resolution Imaging Spectroradiometer (MODIS) observations has been developed. Measurements made in the short-wavelength segment, such as the deep blue or ultraviolet section, are well-detectable in the desert area. Using short-range waves, the visual retention of fine-grained mass data, especially in desert areas, was carefully monitored. The western and southwestern Iran are always exposed to dusty systems due to its vicinity to the deserts of neighboring countries. With regard to the fact that most of the spectral indices proposed for the identification of dust have been tested and implemented based on satellite indicators for desert areas, these indicators and their related thresholds for complex topography areas need more accurate analyses. Therefore, in the western and southwestern Iran, which are mountainous with a diverse vegetation, it is necessary to test and evaluate dust detection methods. Material and methods: The study area included Khuzestan, Ilam and Kermanshah provinces, which is about 107307 square kilometers. In this study, MODIS L1B data from the Aqua satellite was used for dusty days on May 18 and June 25, 2013 and 2015. Before performing spectral calculations on various products, the data of this sensor was preprocessed, which included geometric correction of images, mask cloud and water masks with ENVI and the conversion tool module. After preprocessing (georges, separating the study area, and water mask, and cloud cover) the satellite data, the retrieved spatial radiance of TOA was normalized using satellite data considering the sun's conditions for each wavelength. Results and discussion: In general, it was found that all AOD maps generated from the direct method showed a very good spatial distribution of the local aerosol pattern compared to other methods. As expected, the retrieved AOD map from the L1B spectrum showed that the spatial distribution of the local AOD was very clear. The DAI index algorithm simulates the high-spectral dependence of the atmosphere in the blue wavelength for different surface and atmosphere conditions with a fully tested copy of the radiation-transfer code of -6 S, which is a trusted tool for measuring particle pumping over the oceans, different surfaces of the earth, and clouds. Conclusion: Unlike some of the dust detection algorithms that are carried out using measurements in the infrared thermal band, the advantage of this algorithm to detect dust is the use of spectral scattering, reflection of the surface, and absorption of dust in the air. The advantage of using measurments in the blue wavelength (410 to 490 nm) is to recover the optical properties of the aerosol.
Amir Ansari; Reza Jamshidi
Volume 16, Issue 1 , April 2018, , Pages 101-110
Abstract
Introduction: The mega-city of Arak being located in a semi-arid and dry region and proximity to major wind erosion centers especially Meighan desert and wetland is facing the problem of air pollution.The main objective of this study is Identification of Sources and Tracking Dust Storm Routes Entering ...
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Introduction: The mega-city of Arak being located in a semi-arid and dry region and proximity to major wind erosion centers especially Meighan desert and wetland is facing the problem of air pollution.The main objective of this study is Identification of Sources and Tracking Dust Storm Routes Entering from Domestic Sources to Arak Metropolitan Using HYSPLIT Model. Materials and methods: The present study was carried out using HYSPLIT model, NAAPS model, MODIS satellite imageries and GADS weather data from NECEP weather prediction center for June 22nd, 2016 (Tir 2nd). Modeling was performed using retroviral tracking method for identifying motion direction of dust particles in three stations with a height of 10, 200, and 500 meters, respectively. Results and discussion: The research results demonstrated that most obtained motion directions not only cross Kashan desert and Qom dessert lands and are a source of dust storms but also Meighan dessert wetland and its surrounding dessert lands are the main source of dust particles of the Mega City of Arak. The forward direction of dust particles transporting from Meighan dessert wetland, Kashan dessert and Qom dessert lands in a distance more than 400 km towards north-west of Iran influences the Air Quality Index (AQI) of cities such as Arak, Shazand, Hamedan and even Sanandaj. Conclusion: These findings are in agreement with the optical depth of dust particles and the amount of surface dust in terms of NAAPS model and the suspended particles concentration in the cities located on the direction of particles dissipation. Also, these results which are in accordance with the previous studies in terms of erosion assessment indicating that the numerical models have the ability for tracking and identifying sources of dust storms satisfactorily.
Hadis Ghanavati; Ahmad Fatahi Ardakani; Akram Neshat
Volume 16, Issue 1 , April 2018, , Pages 141-158
Abstract
Introduction: One of the air pollution that has been witnessed in western and southwestern regions of recent times is the dust and dust phenomenon. Dust is one of the atmospheric phenomena that has adverse environmental effects and impacts. Dust storms have had many negative effects on health, economics, ...
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Introduction: One of the air pollution that has been witnessed in western and southwestern regions of recent times is the dust and dust phenomenon. Dust is one of the atmospheric phenomena that has adverse environmental effects and impacts. Dust storms have had many negative effects on health, economics, society and the environment, resulting in huge damage to human resources, health, industry, and especially agriculture. The purpose of this study is to quantify the tangible (market) and intangible (non-market) damages caused by the dust phenomenon in the city of Ardakan. Materials and methods: The data required in this study were obtained from the statistics and data recorded in Ardakan offices, as well as the completion of 244 double bounded dichotomous choice questionnaires in agricultural sector and 509 questionnaires in the air pollution and urban green area using 30 pre-tests and Michels And Carson in 2016. In this study, the tangible and intangible damages of dust are valued using the conditional valuation method and market price. Using the logit model, the factors that affect the willingness to pay are estimated for each section using Shazam 9 and math calculations using Maple Version 18 software. Results and discussion: The results of this study showed that income and education variables have a positive and significant effect on people's willingness to pay for air pollution and urban green space. The variables of age, number of households and gender have a negative and significant effect on people's willingness to pay for air pollution and urban green space against dust phenomena. In agricultural sector, variables such as age, number of employed people, education and income have a positive and significant effect on farmers' willingness to pay for agricultural products against dust phenomena. The total value of the damages against the dust phenomena to maintain air pollution is 33185478480 Rials, the maintenance of agricultural products 50431570000 Rials and the maintenance of green space against dust of 30736160140 Rials per year for the city of Ardakan. Also the tangible losses of dust phenomena in terms of increasing water consumption due to washing in dusty days is 2762736640 Rials, negative effect of dust on physical health and treatment costs and mortality due to asthma and bronchitis diseases 15548414040 Rials and negative effect The livestock sector and treatment costs and the lost cattle were calculated 131451400000 Rials using a market approach. Conclusion: The results indicate that the total value of intangible damages is 114353208620 Rls and the tangible value of 149762550680 Rls in 2016 for the city of Ardakan. The value of willingness to pay people in agriculture was higher than other sectors. The livestock and poultry sector also has the highest figure among other tangible costs. Therefore, this estimate provides policy makers and authorities with the necessary guidance for controlling the effects of dust on human environments.
Fariba Jafari; Hossein Khademi
Volume 12, Issue 3 , October 2014
Abstract
Dust deposition phenomenon is an important climatic and environmental issue in arid to semi-arid regions which causes great losses for human. This study was carried out to compare the concentration of selected heavy metals in soil samples with that of dust and also to identify the possible sources of ...
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Dust deposition phenomenon is an important climatic and environmental issue in arid to semi-arid regions which causes great losses for human. This study was carried out to compare the concentration of selected heavy metals in soil samples with that of dust and also to identify the possible sources of heavy metals in dust of Kerman city. A total of 245 dust samples were monthly collected from 35 study sites during the months of May to November 1391, using glass traps. To compare the results of atmospheric dust with those of soil, 60 surface soil samples (0-10 cm) from outside Kerman and 35 soil samples from urban areas were also collected. After sample preparation, the total concentration of major heavy metals including Cu, Pb, Zn, Ni, and Mn was determined by an atomic absorption spectrometer following the digestion of soil and dust samples with 6N HNO3solution. Cluster analysis and principal component analysis were performed to identify possible sources of heavy metals in dust. The results showed that heavy metal concentrations in atmospheric dust samples were higher than those in soil samples indicating the influence of human factors. There was a highly significant correlation among Cu, Pb, and Zn and also among Cu, Mn, and Ni indicating different sources for these 2 groups of heavy metals. Also, principal component analysis and cluster analysis confirmed the results and further indicated that Ni and Mn derived from natural sources while Cu, Pb, and Zn had an anthropogenic origin. Since the role of human activities on increasing the concentration of pollutants is evident, it is necessary to take appropriate management measures to reduce the amount of pollutants produced in factories and various industries.
