fazel amiri

Iran stands out as one of the world's biodiversity hotspots. Simultaneously, river fish species within the country face imminent threats from various human activities. Climate change, among other challenges, poses a significant risk to the biodiversity of Iran. Consequently, there is a critical need to anticipate potential habitat changes for freshwater fish species in response to climate change. This study focuses on evaluating the impact of climate change on the habitats of the Song fish, a species with economic value and conservation significance. The Song fish is currently classified as Vulnerable (VU) by the International Union for Conservation of Nature (IUCN), making the examination of climate change effects crucial for the future population of this species.

This study employs the MaxEnt model to predict the spatial distribution of the Song fish at two different time scales (2050 and 2080 AD) under both optimistic (RCP2.6) and pessimistic (RCP8.5) climate scenarios. The R software environment was used for the analysis. Environmental variables, including slope, annual temperature range, flow accumulation, annual precipitation, annual mean temperature, and upstream drainage area, were considered. The data related to the observations of this species have been collected from sampling and various library sources. Modeling performance in predicting species distribution has also been evaluated by the AUC (Area Under the Curve) criterion.

The model demonstrated excellent performance in predicting species distribution, as indicated by the high AUC (Area Under the Curve) criterion value of 0.989. Among the environmental variables, annual average temperature and slope emerge were the most influential factors in determining the distribution of the Song fish. Furthermore, the study revealed a projected decrease in the distribution range of this species under both optimistic and pessimistic scenarios for 2050 and 2080.

To safeguard the Song fish, it is imperative for managers to identify and implement appropriate measures. These measures should aim to mitigate the effects of climate change and alleviate threats associated with these changes.

Petrochemical industries are among the basic-heavy industries which produce variety of important products. They have significant potential to affect air, soil and water quality. This paper studied a number of air pollutants in Shiraz Petrochemical Complex in order to determine their potential adverse health, environmental and costs effects. Dispersion of air pollutants from Shiraz Petrochemical Complex has been studied in area of 50×50km. Inhalation risk and environmental impact assessment have been evaluated with AIRQ and SIMAPRO software. Economic costs related to air pollution also investigated with BENMAP software. The results show that Shiraz Petrochemical Complex could contributes to a wide variety of long and short term adverse health effects. It also has a significant contribution (about 39%) to PM2.5 concentration in MARVDASHT city. The healthcare costs related to air pollution could be rise to 750 thousand dollars per year.  Emission of gaseous pollutants in Shiraz Petrochemical Complex are low, however it needs more control over particulate matter PM2.5 specially in Ammonia and Urea units. Even if air pollution will disperse throughout the Persepolis area, but characteristics of their adverse effects needs wider discussion.

Aloe vera L. is one of the oldest and most traditional medicinal plants in history, which is more than a thousand years old. Today, its biological activity is not limited to therapeutic purposes. The expansion of the Aloe vera L. industry became evident during the 90s when the development of this product began due to the global demand from consumers for a healthier lifestyle. Considering this plant's relationship with agriculture, industry, and the economy, the present work examined   chemical, biological, and nutritional properties of Aloe vera and its processing methods, innovations, and biosynthesis of nanoparticles, and industrial applications. Applications of this plant are detailed in pharmaceutical, cosmetic, and food industries, and the global vision of the million-dollar market around this product is discussed. Also, the biosynthesis method of nanoparticles using Aloe vera L. as a reducing agent is presented. Aloe vera L. has been used to produce nanomaterial through biosynthesis. This plant has many unique properties and is known for its antioxidant, anti-inflammatory, anti-diabetic, sunburn relief, immune system strengthening, anti-aging, and anti-cancer properties. The study concludes that biosynthesized nanoparticles with Aloe vera L. are environmentally friendly, simple, economical, and safe.

Remote sensed information on growth, vigor, and dynamics from terrestrial vegetation can provide useful insights for applications in environmental monitoring, biodiversity conservation, agriculture, forestry, urban green infrastructures, and other related fields. Specifically, these types of information applied to agriculture provide not only an objective basis (depending on resolution) for the macro- and micro-management of agricultural production but also on many occasions the necessary information for yield estimation of crops. Vegetation indices (VIs) obtained from the vegetation canopy in remote sensing are simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications. These indicators are used in remote sensing applications and satellite systems. To date, there is no unified mathematical expression that defines all VIs due to the complexity of different combinations of light spectra, instrumentation, platforms, and resolutions used. Therefore, special algorithms have been developed for different applications according to the specific mathematical expressions in the range of the visible light radiation spectrum, mainly the green spectrum region, from vegetation, and invisible spectra to quantitatively determine the level of vegetation cover. In this article, the spectral characteristics of vegetation and vegetation indices, the advantages and disadvantages of various developed indices, and their application are discussed according to the characteristics of vegetation, environment, and accuracy of implementation.

Remote sensing of vegetation is primarily performed by getting the electromagnetic wave reflectance data from canopies utilizing passive sensors. It is well known that the reflectance of light spectra from plants changes with plant sort, water substance inside tissues, and other natural components. The reflectance from vegetation to the electromagnetic range (spectral reflectance or emanation characteristics of vegetation) is decided by chemical and morphological characteristics of the surface of organs or clears out. Most applications for inaccessible detecting of vegetation are based on the taking after light spectra: (i) the bright locale (UV), which goes from 10 fr 380 nm; (ii) the apparent spectra, which are composed of the blue (450–495 nm), green (495−570 nm), and ruddy (620–750 nm) wavelength districts; and (iii) the close and mid-infrared band (850–1700 nm). The emissivity rate of the surface of takes off (equivalent to the absorptivity within the warm waveband) of a completely developed green arrange.

Many studies have constrained this translation by extricating vegetation data utilizing person light spectra groups or a bunch of single groups for information investigation. Hence, analysts regularly combine the information from near-infrared (0.7–1.1 m) and ruddy (0.6–0.7 m) groups in numerous ways concurring with their particular targets. These sorts of combinations display many disadvantages (e.g., need for affectability) by employing a single or restricted gathering of groups to detect, for case, vegetation biomass. These impediments are especially apparent when attempting to apply these sorts of VI on heterogeneous canopies, such as green tree ranches. A blended combination of soils, weeds, and cover crops within the interrow. The plants of intrigued make the segregation locales of intrigued and extraction of straightforward VI exceptionally troublesome, particularly, when the vegetation of intrigued has distinctive VIs due to spatial inconstancy, or VIs compared to other vegetation (weeds and cover edit), which can be compared to those of intrigued. The last mentioned will complicate imaging denoising and sifting forms. A few picture examination procedures and calculations have been created to go around these issues, which can be depicted afterward. Indeed in spite of the fact that there are numerous contemplations as portrayed sometime recently, the development of a straightforward VI calculation seems numerous times to render basic and compelling apparatuses to degree vegetation status on the surface of the soil. Vegetation data from remotely detected pictures is primarily translated by contrasts and changes within the green clears out from plants and canopy ghastly characteristics. The foremost common approval preparation is through coordinate or backhanded relationships between VIs gotten and the vegetation characteristics of intrigued measured in situ, such as vegetation cover, leaf area index (LAI), biomass, development, and vigor evaluation. More set-up strategies are utilized to evaluate VIs utilizing coordinate and georeferenced strategies by checking sentinel plants to be compared with VIs gotten from the same plants for calibration purposes.

Basic vegetation records combining obvious and near-infrared groups have essentially moved forward the affectability of green vegetation discovery. Diverse situations have their variable and complex characteristics that must be considered when utilizing distinctive plant lists. Hence, each vegetation list has its claim definition of green vegetation, its reasonableness for particular applications, and a few restricting variables. Subsequently, for commonsense applications, the choice of a particular vegetation file ought to be done carefully by considering and comprehensively analyzing the points of interest and confinements of existing vegetation records and after that combining them for application in a particular environment. In this way, the utilization of plant markers can be custom-fitted to particular applications, instruments, and stages. With the advancement of hyperspectral and multispectral further detecting innovation, it is conceivable to create unused plant markers that grow investigative areas.

Land use/cover information is vital to the dynamic monitoring, planning and management, and the reasonable development of land. Recently, due to human activity, land cover information has changed dramatically. Furthermore, construction, land has become increasingly scarce, and the non-agriculturalization of arable land has been highlighted. Therefore, it has become increasingly significant to timely, and accurately monitor land use and land cover for the reasonable development and utilization of urban land resources in city regions. It is significant to timely, accurate, and effectively monitor land cover for conservation, reasonable development and land resources. The remotely sensed dynamic monitoring of covered land in rapidly developing regions has increasingly depended on remote-sensing data on temporal and spatial resolutions. In many cases, it is difficult to acquire enough time-series images with high quality at both high temporal and spatial resolution from the same sensor.In this research, Landsat images and an object-oriented method were used to eliminate errors using the visual interpretation method to prepare a land cover map and achieve acceptable accuracy and classification results. Landsat 8 data was used to prepare the land cover map using spatio-temporal integration model. In addition, through an object-oriented classification method, land cover was extracted, which was used to provide a more accurate and efficient technical method for effectively extracting land cover information in Bushehr province.

In this paper, we proposed a method for mapping land use and land cover in a Bushehr province area with high spatial-temporal resolution using fusing Landsat 8 time series. The method has three steps, 1) Enhance the spatial-temporal adaptive reflectance fusion model (ESTARFM), 2) Determination the optimal data combined for the extraction of cover type, 3) Image segmentation and Land cover extraction and the accuracy assessment based on the field sample method was used. In many cases, it is difficult to acquire enough time-series images with high quality at both high temporal and spatial resolution from the same sensor. This study used the temporal-spatial fusion model ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) to blend Landsat 8 and MODIS data and obtain Landsat 8 images. Then, the cover lands information of Bushehr province is extracted using an object-based classification method.

In this paper, an object-oriented LULC mapping method using time series Landsat 8 images was proposed. Based on the time-series Landsat 8 data (red band, NIR band and NDVI), the land cover types. In this study, the proposed method was used in a case study of Bushehr province. The results of the object-based method show that the overall accuracy and Kappa coefficients were 93.34% and 0.86, respectively, and the user/producer accuracies of cover lands in the pixel-based method were all over 80%. The approach presented an accurate and efficient technical method for effectively extracting land use information in heterogeneous regions. In this paper, we have achieved an acceptable classification result using Landsat 8 image. There are still some potential factors affecting the accuracy. The first factor is the uncertainties of the fused images by the ESTARFM fusion model. The second is the mixed pixel problem, the Landsat image pixels are always informed with several land cover types, which will affect the classification accuracy. Remote sensing images with high spatial resolution may be a feasible way to achieve higher accuracy.

In the present study, based on the combined data of Landsat 8 and object-oriented classification, the land cover map of Bushehr province was extracted. Types of pasture and desert land cover were clearly presented. In this research, an object-oriented method was presented for the preparation of pasture cover type map using the images generated from ESTARFM time-spatial integration model. Based on Landsat 8 data (red band, near-infrared band and normalized vegetation difference index), the types of pasture cover in Bushehr province were extracted using visual and object-oriented methods.The use of Landsat 8 images and the object-oriented method improved the classification. But there are some factors that affect the accuracy of preparing land use and land cover maps. The first uncertainty factor is the fusion images by the enhanced spatio-temporal adaptive reflectance model (ESTARFM). The second problem is the existence of heterogeneous pixels. In heterogeneous areas, the presence of small polygons in which the pixels of the Landsat image of vegetation cannot be separated in these polygons, which affects the classification accuracy. Remote sensing images with high spatial resolution may be a practical way to achieve higher accuracy. Therefore, the object-oriented method combined with spectral integration analysis can be improved to achieve land cover information extraction. The results of this research showed that the overall accuracy and Kappa coefficients in the object-oriented method were 93.34% and 0.86, respectively, and the accuracy of the land cover user/producer in the pixel-oriented method was more than 80%. The object-oriented algorithm analyzes images as objects by merging neighborhood information, which enhances the analysis and increases the classification accuracy. The object-oriented algorithm has shown its potential in identifying land cover and preparing land cover in heterogeneous areas.

Groundwater is the sole source of water for drinking, irrigation, and industrial uses in many arid and semi-arid regions of the world. Groundwater can be contaminated by natural as well as anthropogenic influences. Residential, municipal, commercial, industrial, and agricultural activities can all affect groundwater quality. Groundwater contamination results in poor drinking water quality, loss of water supply, high cleanup costs, high costs for alternative water supplies, and/or potential health problems. In Iran, dependence on groundwater has increased tremendously in recent years. Groundwaters can be contaminated by natural as well as human influences. Land use changes, residential and agricultural activities can affect the quality of groundwater. Groundwater contamination can lead to poor drinking water quality, loss of water resources, high cleanup costs, high costs for alternative water sources, and problems for watershed health. In Iran, dependence on underground water in most watersheds has increased greatly in recent years. Therefore, the evaluation, protection and proper management of underground water resources is very necessary for optimal and sustainable use of water resources. Water quality assessment includes the assessment of the physical, chemical and biological nature of water in relation to its natural quality, human effects and intended uses, especially uses that may affect human health and the health of the water system itself. The use of geographic information system technology has greatly simplified the assessment of natural resources and environmental concerns, including groundwater. In groundwater studies, GIS is commonly used to analyze site suitability, manage watershed assessment data, estimate groundwater vulnerability to contamination, model groundwater flow, model solute transport and leaching, and integrate groundwater quality assessment models with spatial data to create Spatial decision support systems are used. This study attempts to assess the influence of changing land-use patterns on the groundwater quality in the Dehram, Fars province. The study area is an agricultural developing region with land development progressing at a fast pace. The objective of this article is to demonstrate the influence of land-use transformations, land-use transition, on the quality of groundwater using geographical information systems. The study also aims at evaluating the significance and applicability of a groundwater quality index (GQI) generated using geographical information system (GIS) approach for the assessment of groundwater quality in a medium sized catchment. Moreover, a simple methodology for the preparation of a groundwater quality sustainability map, for use in planning and management decisions by local government authorities, is developed in this work.

The water samples were collected from 6 wells in the study area in 2021, which are added to the urban water system for drinking purposes. For 2014, the available data were used to observe the general changes in the quality of underground water during this period. Sampling in the summer season, due to the lack of water in this season, by taking water from wells in the area and injecting it into the drinking water system, in three repetitions for the year 1400 according to the standard method of the American Public Health Association (APHA) with field sampling and the available data of year 2013 were used to show seasonal changes in different water quality parameters during both years. Therefore, samples were taken from each well of the available data three times in 2013 and three times in summer (July to August) 1400. The geographic coordinates of the sampling wells were recorded manually using a Garmin e-Trex GPS receiver. The hydrochemical data obtained from the laboratory analysis of the water samples were linked to the spatial database of the sampling points. Spatial data shapefiles were prepared in vector format showing the locations of sample wells along with associated hydrochemical data. To evaluate the location of the sampling wells according to the potential sources of groundwater pollution, these shapefiles were placed on the land use map. Then, point shape files were used to prepare variable concentration maps by applying Kriging interpolation method. The GQI proposed was used for quality assessment. To generate the index, seven parameters listed in World Health Organization guidelines for drinking water quality were selected from the main dataset. Six parameters (Cl-, Na+, Ca+2, Mg+2, SO4-2, and TDS) can be categorized as chemically derived contaminants that could alter the water taste, odor, or appearance and affect its ‘‘acceptability’’ by consumers. NO-3 was categorized under chemicals that might inflict ‘‘potential health risk’’ and a guideline value of 50 mg/l was assigned. The GQI integrates the different water quality parameters to give a quantitative index value that can be used for spatio-temporal provides in groundwater quality. In the present study, the land use/cover map for two different periods (2013 and 2014) was prepared to evaluate land use and land cover transition patterns using Landsat satellite images from ETM+ sensors (2013) and OLI (2014).

The land-use pattern has changed drastically with the increased agricultural and built-up area at the expense of other land uses. The analysis reveals a rapid deterioration of groundwater quality related mainly to the increase in built-up land, drought and land-use change in agricultural lands and uncontrolled withdrawal of water by farmers from wells in the region. Mean GQI decreased from 86.42 to 57.36 over a period of 7 years from 2014 to 2021, which indicates a decrease in water quality. The quality of groundwater in the region in 2014 has a desirable quality and is in a very suitable range. But in 2021 the water quality changed from very good and good to poor and bad.

GQI and land use were integrated into GIS to yield groundwater quality, in terms of water quality. Zones of sustainable and unsustainable groundwater use were demarcated for better decision making related to land use allotment in this rapidly changing region. The GQI index provides the possibility of mapping the spatial changes of groundwater quality in the study area, which shows that the water quality of the area is generally good, but the deterioration has started with the onset of urbanization. The main sources of pollution identified in this study are agricultural and residential activities. Although agricultural activities and the application of fertilizers related to it have been the main factor in reducing the quality of groundwater, in addition, this study showed that the increase in urbanization has a dominant contribution to pollution in the region. Agricultural activities must comply with methods that ensure minimal impact on groundwater. This study also shows the effectiveness of GIS in groundwater quality assessment. Similarly, GIS-based assessment techniques can be used to characterize groundwater contamination preferably in large watersheds. Of course, the selection of parameters and weights may be different in each location depending on the prevailing land use conditions.

Background and Objective :

Land surface temperature (LST) has become an important issue in the world today, as it affects the climate and environment at the local, regional and global levels, and these changes in land surface temperature are mainly caused by it arises from urbanization, and human activities and extreme Landuse and Land-cover (LULC) changes. Due to the limitations of meteorological stations, remote sensing can be used as the basis of many meteorological data. One of the most important practical aspects of remote sensing in climate studies is the estimation of surface temperature. In this research, the temperature of the earth's surface between 1990 and 2018 was extracted from the images of TM and OLI sensors of the coastal lands of Bushehr, using the Stefan-Boltzmann method.

Materials and Methods:

 The land study area of Bushehr city, which is on the northern coast of the Persian Gulf, with dimensions of 20×8 km2 an area of 1011.5 km2 and with an average minimum temperature of 18.1oC and an average maximum temperature of 33 oC, relative humidity between 58-75% and the average annual rainfall is 272 mm, it’s located in the geographical location of 50°50' to 10°51 E longitude and 28°40' to 29°00' N latitude. The data used in this research include; Landsat 8 (OLI) data in 2018 and TM data in 1990, which were downloaded from the United States Geological Survey (USGS) data center (https://earth explorer.usgs.gov). In order to calculate the parameters related to temperature extraction, the meteorological data of the synoptic stations located in the studied area were used. After taking the images, due to the larger range of the images, the images were cut (Resized) and then the geometric correction of the images was done using topographic maps on a scale of 1/25000 and all the images were adjusted to the UTM coordinate system of the 39 N were adapted. In geometric correction, the RMS error of all images was less than 0.5 pixels. In order to compare the results of Stefan-Boltzmann method for extracting LST with ground data, thermal map data obtained was compared with soil temperature data (obtained from meteorological stations in the selected area). In order to evaluate the Stefan-Boltzmann method from ground data, the Mean Absolute Error (MAE) index statistical method was used.

Results and Discussion: 

 The average minimum and maximum Land surface temperature (LST) extracted from the 1990 TM image was 26.5 and 45 °C, respectively, and for the 2018 OLI image, it was 30.1 and 48.6 °C, respectively. The results showed that the Mean Absolute Error (MAE) index values for TM and OLI sensors are to 7.1 and 5.6, respectively. The results of the research showed that the Stefan-Boltzmann method provided a reliable result in estimating the Land surface temperature.

Conclusion:

 This research aims to extract LST by Stefan-Boltzmann method. The results of this method were estimated using the Mean Absolute Error (MAE) statistical index for the study period (1990-2018). Applying the MAE on the produced thermal maps, it was found that the Stefan-Boltzmann method is suitable for future research in the fields of thermal remote sensing by observing the results of using the MAE index on thermal maps. Therefore, we conclude that the Stefan-Boltzmann method is suitable for estimating the surface temperature of the land in coastal areas. Finally, it is suggested that for quantitatively describing LST patterns a GIS/RS-based method, and methods such as spatial autocorrelation and semivariance are used.

Given the potential negative environmental impacts linked with wild landfills in the central part of the Kangan Region, there is a significant need to accelerate the development of controlled inter-municipal landfills. The study area with daily production of 92 tons of waste, due to lack of recycling equipment and incorrect locating landfill is faced with numerous environmental, health and social problems in open sites and unsafe. This study is aimed at identifying suitable sites for solid waste disposal by considering all essential factors and rating criteria by integrating Fuzzy-AHP and GIS with multi-criteria decision analysis (MCDA) in Kangan county. Standards for siting a landfill formulated by the Environmental Protection Agency (EPA) were employed in this study. The criteria that are considered herein are land use, slope, elevation, distance to drainage, groundwater and dams, distance to faults, soil, geology, distance to the residence and road, industrial and infrastructure accessibility. These criteria were assigned fuzzy membership classes based on their importance in siting a landfill. The fuzzy members of all criteria were overlaid to generate the final landfill site suitability map which was classified into five: not suitable (53.3%), less suitable (39.1%), moderately suitable (5.4%), suitable (1.4%) and highly suitable (0.6%). The Analytical Hierarchy Process (AHP) technique was employed in the selection of the landfill site with reverence to multiple criteria and the fuzzy membership classes in accordance with the standards of the EPA. The results of this research in the management of the urban environment and also in the plans of the optimal disposal of urban solid of this area will be useful.

Groundwater quality assessment can be very important in managing these resources and planning for the future. This research aims to monitor the groundwater quality of the Dehroud-Tange Eram plain in Bushehr province in southern Iran using the water quality index (WQI). Therefore, 10 groundwater sources in the plain have been selected and their water quality has been measured from the years 2013 to 2020 in two seasons, dry and wet. The water quality index has been calculated using pH, TDS, total hardness, nitrate, sulfate, bicarbonate, chloride, calcium, sodium, potassium and magnesium. The results of the study showed that the best water quality index with an average of 142 belongs to well number 5 (close to Tange Eram village) and the worst water quality index with an average of 789 belongs to well number 10 (near Dehroud village). A comparison of zoning maps drawn using the Kriging method shows that wells near Tange Eram have better quality. As we move towards the village of Dehroud in the southeast of the aquifer, the quality of groundwater has decreased.

The purpose of this work is to study degradative removal of gentamicin antibiotic from aqueous media that a trace amount of it may present a human health risk. To this aim photocatalytic process using a recyclable magnetic titania photo-catalyst was utilized. The Nano-catalyst was synthesized, characterized, and utilized to remove gentamicin antibiotic. The process modeling and optimization were performed by a second order polynomial model using design of experiment software. According to the model prediction, the process can remove gentamicin antibiotic up to 94.7% in the optimum condition. The introduced optimum conditions were; initial pH = 6.9, [gentamicin] = 20 ppm, [Catalyst] = 195 mg, and time = 63 min. Mineralization of the gentamicin was also investigated such that in the optimum condition 51.3% mineralization efficiency was obtained in optimum condition. Kinetic study results showed that the data was well fitted by pseudo first order kinetic model. Also, the effect of sulfate and chloride ions as radical scavenger on removal efficiency was assessed and process efficiency was reduced by using chloride and sulfate.

Pars special economic energy zone (PSEEZ) in Iran is the second largest energy zone in the world with more than 60,000 operational and non-operational personnel. Considering the nature of the activities being done in PSEEZ, it is rational to expect that a wide range of hazardous materials be present in the air composition of this area. It is shown in this research that Benzene-Toluene-Ethylbenzene-Xylene (BTEX) are the most challenging in PSEEZ and benzene concentration violates the standards in all sampling points. The study area is divided into three subzones of gas refineries, petrochemical complexes and non-operational areas. In the gas refineries, benzene concentration is recorded to be 480 times higher than the standard for exposure limit. The concentration of benzene in petrochemical complexes is also about 160 times higher than the standard limit. Considering the vicinity of the petrochemical complexes the cumulative impacts of BTEX will also worsen the situation regarding BTEX cancer risk. In non-operational areas, benzene concentration reaches 40 times higher than the standard limit which is a serious health challenge. Comparing the data of BTEX distribution with AQI proves that AQI solely is not an appropriate index for assessing the air quality in PSEEZ and defining local indices for air quality assessment with taking hazardous chemicals such as BTEX into account. Moreover, some other pollutants such as heavy metals and H2S are detected in the air quality in significant amounts which raise the need to a reconsideration in location of unprotected non-operational personnel.

The development of industry has recently led to the release of 2 × 105 tons of colored wastewater into the environment. The presence of these solutions due to their toxicity and carcinogenic potential can be a threat to human health. The aim of this study was to investigate the efficiency of MWCNTs-CuNiFe2O4 nanocomposite in activating peroxymonosulfate (PMS) for degradation of reactive black 5 dye (RB5).

In this study, nanocomposites were characterized by diagnostic techniques of SEM, TEM, FTIR, and XRD. Influence of operating parameters such as pH (2-11), nanocomposite concentration (10-750 mg/L), PMS concentration (0.25-8 mM), dye concentration (10-250 mg/L), and reaction time (0-60 min) was evaluated. Stability and scavenging tests of reactive species under optimal conditions were studied.

The results showed that the MWCNTs-CuNiFe2O4/PMS system has a high performance in RB5 degradation compared to systems such as PMS, MWCNTs-CuNiFe2O4 and CuFe2O4/PMS.  RB5 degradation complete was obtained at pH of 7, the composite concentration of 250 mg/L, the PMS concentration of 4 mM, and the reaction time of 15 minutes. Suitable treatment of real solutions due to the presence of interfering materials requires a reaction time above 240 min. Stability tests for 5 reaction cycles showed that MWCNTs-CuNiFe2O4 could be a recyclable catalyst in PMS activation.

The synthesized composite can be used as a catalyst to activate PMS in RB5 dye removal due to its recyclability and high efficiency.

Using wastewater as a renewable water source to irrigate plants is a safe and effective solution. In contrast, the accumulation of heavy elements in soil and plants is one of the concerns of the use of wastewater in agriculture. This study was conducted to investigate the effects of urban wastewater use on the most important physiological parameters related to the growth of corn (Zea mays L., KSC 704) and the accumulation of heavy metals lead and cadmium in the soil in a field Bushkan area of Dashtestan, Bushehr in a pot.

This study was performed in 4 treatments: wastewater of the treatment plant, wastewater diluted with drinking water (1/2), Irrigation one on one with wastewater and drinking water and drinking water treatment, in 3 replications in a completely randomized design. Lead (Pb) and cadmium (Cd) content in soil and plants were measured by ICP. pH and Electrical conductivity (EC) of soil and wet and dry weight of the Corn organs were measured. The means were compared using one-way analysis of variance (ANOVA), and the Duncan test was used to determine the differences between groups (p <0.05).

The results of this study showed that irrigation with EC wastewater increased the soil by 1.1 (ds.m-1), also increased soil cadmium by 0.03 (mg.kg-1) and lead by 0.02 (mg.kg-1). Dilution of the wastewater reduced the negative effects of the wastewater on the soil. The highest wet weight added of 1500 g was related to irrigation treatment with diluted wastewater. The highest dry weight added was observed with 600 g of irrigation treatment with diluted wastewater. The lowest total wet weight added of 1100 g and total dry weight added of 400 g were observed in the wastewater treatment.  The accumulation of lead and cadmium in the corn seed was (0.6 lead, 0.5 cadmium) <stem (0.9 lead, 0.8 cadmium) <root (lead 1.9, 0.95 cadmium), respectively. The highest accumulation of lead and cadmium was related to wastewater treatment and the lowest was related to drinking water treatment.

The higher the cadmium levels in the soil, the higher the concentration and content of cadmium in the roots and shoots. The results showed that the corn plant has a high ability to absorb and transport cadmium and lead. Due to the pattern of accumulation of heavy elements of lead and cadmium in the roots of corn, this plant can be used for accumulation of fields irrigated with wastewater. The continuation of this study is recommended to evaluate the long-term effects of municipal treated wastewater on the concentration of heavy elements in soil and plants, and soil properties, although it should be noted that based on technical recommendations, the use of treated wastewater are not recommended, however, in necessary cases, diluting of wastewater by reducing the destructive effects and providing the necessary elements for the growth of the Corn can be used as an indicator treatment in irrigation. Also, it is suggested that in order to use the wastewater in corn cultivation, while increasing growth and yield, the risk of using the wastewater in corn cultivation should be evaluated from an environmental point of view.

Land surface temperature (LST) and its relationship with land use /cover change are significantly considered in environmental studies. The aim of this study was to retrieve the LST of Bushehr land and explore its spatial relationships with LULC. Landsat images of August of the summer season for three years with fifteen years time intervals were analyzed. The result showed a gradual rising (1.4 °C during 1990–2005 and 2 °C during 2005–2020) of LST during the whole period of study. The mean LST value for three study years was the lowest (30.86 °C) on green vegetation and the highest (49.07 °C) on bare land and built-up areas. The spatial distribution of NDVI and LST reflects an inverse relationship. The best (-0.97) and the least (-0.80) correlation, respectively, whereas a moderate (-0.89) correlation was noticed. This LST-NDVI correlation was strong negative (-0.80) on the vegetation surface. The LST is greatly controlled by land-use characteristics. This study can be used as a reference for land use and environmental planning on coastal land.

The complicated relationship between land use (LU) and environmental factors influences human livelihood; hence, it is essential to monitor LU changes and to prepare pertinent maps due to their relevance to such vital fields as urban planning, climate change, and environmental monitoring. In this study, a supervised classification was applied to three Landsat images collected over time (1990, 2000, and 2018) in order to derive the data on land use changes in Bushehr region. The supervised classification results were further improved by employing image enhancement and classification accuracy of the Landsat images was enhanced by visual interpretation to enhance. Finally, eight LU categories were identified and mapped. It was found that land reclamation projects over the last three decades had had drastic effects on LU changes throughout the study area. Land use changes during the study period show increasing trends as evidenced by the 29.19 hectares of agricultural land with a rise of 30.19% and the 15.78 hectares of urban and rural residential land with a rise of 16.39%. In contrast, declines are observed in barren land covering 4.15 hectares with a change of -4.31%, salty land covering 11.66 hectares with a negative change of -12.11, and sandy land covering 5.21 hectares with a change of -5.41. Hence, agricultural land area as well as urban and rural residential areas show significant increases whereas barren, salty, and sandy land areas show decreases. These changes in LU reflect regional policies and the dynamics of human impacts (agricultural and construction activities) on land use changes in the study region. Identifying the causes underlying these changes, the present article tries to formulate policy recommendations toward improved land use management.

The present study evaluated the effect of the integration of electro-kinetic (EK) oxidation with sonication degradation of diesel in a hydrocarbon contaminated wastewater. The effect of operational parameters including initial pH (3 - 9), sonication (100 - 300 W), voltage (0.5 - 3 V/cm), and reaction time (60 - 150 min) were studied consecutively. The highest total petroleum hydrocarbon (TPH) destruction rate of 40% was achieved at pH 5. Also, increasing the sonication intensity up to 300 W improved the removal rate to 70%. The pseudo-first-order kinetic model was selected due to higher correlation coefficient. Considering the obtained integration of EK oxidation with sonication is a viable and efficient technology for treatment of diesel contaminated wastewaters.

Limited water resources in arid and semi-arid regions are one of the major limiting factors in agricultural production. Thus, unconventional water resources, such as urban treated wastewater, may be used for irrigation. Application of wastewater to the soil may cause accumulation of heavy metals (HMs). Soil pollution causes uptake of these metals by plants and their entrance to the food chain. In the present greenhouse research, concentration variations of HMs (lead (Pb) and cadmium (Cd)( in soil and sweet pepper (Capsicum annuum) plant were investigated.

The experiment was conducted as a completely randomized design with three replications and irrigation with different wastewater treated (well water, wastewater treatment and diluted wastewater). To evaluate the effects of different irrigation treatments on soil, parameters of acidity (pH), electrical conductivity (EC), the concentration of heavy metals Pb and Cd in soil were studied.  Additionally, for the effects of irrigation treatments on sweet pepper plant, parameters of biomass weight, fresh and dry weight and Pb and Cd concentrations (in branches, fruits and roots) were measured. The amount of Pb and Cd in the pepper were measured by ICP-OES. The obtained average concentrations were compared using one-way analysis of variance (ANOVA), and the Duncan test was used to determine the differences between groups (p <0.05). The independent t-test was also used to investigate the difference in concentrations of Pb and Cd in soil and water (p <0.05).

The results of chemical analysis of soil and pepper showed that irrigation with wastewater did not cause a significant increase in the concentration of Pb and Cd in the soil and in the branches, fruits and roots of the pepper. The concentration of Pb and Cd in the soil and in the branches, fruits and roots of the pepper was within the allowable and standard concentration range. The difference in lead and cadmium concentrations in the soil before planting was not significant; however, at the end of the study period, the Pb concentration in pepper was higher than the Cd concentration. The use of wastewater increased the fresh and dry weight of branches, fruits and roots of the pepper.

The results showed that Pb and Cd concentration in roots and aerial parts of pepper plant was not increased significantly as a result of wastewater irrigation (p <0.05). The results of this study are limited to one growing season and by the continued use of municipal wastewater, the concentration of Pb and Cd in the soil and then in the plant may exceed the standard. Especially in the case of Pb, which seems to have shown a slight tendency to increase relative to the primary soil and the pepper. Therefore, the continuation of this study is recommended to evaluate the long-term effects of Bushehr municipal treated wastewater on the concentration of heavy elements in soil and plants, and soil properties. Overall, it should be acknowledged that based on technical recommendations, the use of treated wastewater are not recommended.

Trihalo-methanes have been identified by the Cancer Research Institute as a carcinogen for humans. Considering that in Haft Rousta project, the source of drinking water supply is groundwater and water of Darood Zan dam and disinfection used is chlorine, this study was conducted to determine the concentration of trihalomethanes in drinking water of Haft Rousta project. The present study was conducted in the spring and summer of 2017. For this purpose, three villages (Abbasabad, Majd Abad, Kemar Zard) from Marvdasht city of Fars with a total of 9 stations were selected and the amounts of chlorine, pH, temperature, total organic carbon and trihalo methane were measured with three replications in water samples. The average concentration of trihalomethane compounds in this study was estimated to be 39 mg / l for Abbasabad village, 38.6 mg / l for Kemar Zard village and 39.7 mg / l for Majd Abad village. The highest recorded concentration was calculated in Majd Abad village with a concentration of 73 mg / l. The mean concentrations of chloroform, bromoform, bromodium chloromethane and dichloromethane and totality of halo methanes in network water in spring 1996 were 22.25 7 7.98, 11.42 90 3.90, 7.43 7 2.72, 51, respectively. 5.95 2 2.2, 47.06 15 15.70 mg / l in summer 96 are equal to 14.69 4 4.11, 7.55 99 1.99, 4.93 51 1.51, 1.49 3.95 ،, 31.13 97 7.97 mg / l were calculated. Due to the concentration of trihalomethane in the drinking water of the study area, the possibility of trihalomethane compounds due to the consumption of the studied waters is very low and the presence of this pollutant in this danger does not affect consumers in any age group.

In this study the difference between physiological and morphological growth of Yucca Elephantipes with irrigation by sanitary wastewater and drinking water was investigated. Morphological variables such as height from the crown to the tail end of the plant, number of leaves, number of stems, leaf length, total leaf dry weight, stem dry weight, number of roots and root size and physiological variables of the plant including Catalase enzyme activity (CAT), Ascorbate peroxidase enzyme activity (APX), Glutathione peroxidase enzyme (GPX) have examined. Irrigation treatments include drinking water and sanitary wastewater. The results show a significant difference in the studied variables between the two treatments at the level of 5%. The highest number of leaves and roots were 64 and 6, respectively, in the treatment of irrigation with wastewater. The number of stems in both treatments was equal to 1. APX in sanitary irrigation and drinking water was 0.62 and 0.71, respectively. The best performance of GPX was related to drinking water irrigation at 0.17. The results also showed that irrigation with sanitary wastewater of Y. Elephantipes, morphological and physiological parameters of the plant had 8% and 2% better performance in the studied variables than similar samples irrigated with drinking water, respectively.

The aim of this research was to the feasibility of reuse of Bushehr wastewater treatment plant sewage in Conocarpus lancifolius irrigation. To evaluate the microbial and plant growth characteristics, two treatments including irrigation with wastewater and irrigation with drinking water were used. 120 C. lancifolius samples, 90 samples with wastewater and 30 samples with drinking water, were irrigated for 6 months by sprinkler irrigation. Growth indices (stem length and diameter) and leaf microbial quality were measured at the end of each irrigation month. pH was measured using pH meter, electrical conductivity was measured using EC meter. Calcium and magnesium were determined using titrimetric tests. The concentrations of iron and manganese were determined using flame atomic absorption spectrometer and the concentrations of phosphorus phosphate, nitrogen nitrite and nitrogen nitrate were determined using ultraviolet spectrophotometer, total coliform and fecal coliform using MPN standard method. The results showed that due to irrigation with urban wastewater, growth indices of C. lancifolius are significantly higher than irrigation with drinking water (P <0.05). The microbial contamination of the wastewater used was less than the standard of the Environmental Protection Agency of Iran for reuse in irrigation of urban green spaces.

One of the most important problems of dams is thermal layering which directly affects the water quality. This study was performed to propose a solution to increase the water quality of the Esteghlal Dam reservoir in Minab, Hormozgan.

The water quality of Esteghlal Dam was evaluated from 2016 to 2018. During this period, 18 samples were collected from three different points of the dam. The parameters of water temperature, electrical conductivity, total dissolved solids, total suspended solids, dissolved oxygen (DO), pH, nitrate, phosphate, turbidity, biochemical oxygen demand, chemical oxygen demand, total hardness, anions and cations, total phosphorus, physicochemical, and microbial parameters were measured according to the method recommended in the standard method book. The obtained data were used as the input for the model of reservoir water quality (CE-QUAL-W2) to simulate reservoir water quality and predict the thermocline cycle. Finally, by plotting hypolimnion oxygen content against time and finding the slope of regression line using the data, the hypolimnetic oxygen demand (HOD) was obtained.

The findings showed that the anaerobic condition occurred in the hypolimnion layer during summer. Furthermore, it was revealed that the HOD of Esteghlal Dam is about 6 g of oxygen per square meter per day in the current situation.

Considering the dam’s conditions and its anaerobic problems, a hypolimnetic oxygenation system is proposed as a structural solution for this reservoir. Then, conductivity-temperature-depth (CTD) profiles and monitoring data were used for the oxygen supply model of plume. The reservoir was predicted after calculating the amount of oxygen required using the equations governing linear oxygen supply systems and the plume model.

 The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between land use/land cover composition and land surface temperature (LST) gives insight into how to effectively reduce the temperature in urban environments. In recent years, the expansion of Bushehr city has resulted in an increase in impervious surface, the decrease of green space and a significant change in the temperature. It is also essential to determine the influence of green spaces on the surrounding environment in urban planning of Bushehr.

 In order to reveal the comprehensive effects of green space on the urban thermal environment in the severely hot regions, this paper adopts remote sensing technology to extract and analyze green space, land surface temperature (LST), and land cover (LC) from the Landsat spectral imaging data (August 2018) with clear-sky conditions. A field survey was carried out in August 2018 and temperature and relative humidity was recorded for 13 selected green spaces in the Bushehr city. To analyze the field data, a multivariate linear regression model between temperature and relative humidity with three variables of direction, distance, and the size of green spaces was determined and interactions between variables were investigated. By applying a multivariate regression model, the relationship between temperature and relative humidity data was calculated for each point. Tukey test was carried out between the averages of temperature variations and relative humidity for each of the three variables at a 95% confidence level.

 The results of the R2 correlation coefficient from the linear regression model between normalized difference vegetation index  (NDVI) and land surface temperature equal to 0.72 indicated a high correlation between temperature and NDVI variations. The results of the temperature variation analysis with NDVI changes indicated that NDVI variations, which are actually plant frequency indices, were one of the most important factors in reducing temperature or in improving the most important ecological function of urban green space. The results of the recorded data at different intervals and directions from the green spaces indicated a gradual decrease in temperature and an increase in relative humidity by reducing the distance from the green spaces. Accordingly, the effect of green spaces on temperature and relative humidity was significant up to a distance of 60 meters (p≤0.05). The western direction had the lowest temperature and the highest relative humidity and the eastern direction had the highest temperature and the lowest relative humidity. The R2 correlation coefficient obtained from the linear model between temperature and relative humidity with the interactions between the three variables (direction, distance, and the size of green spaces) were also 0.88 and 0.95, respectively.

 The results indicated that urban green space plays a significant role in improving the urban thermal environment. By using remote sensing technology and comparing the thermal environments, we conclude that the location and distance of urban green spaces affect the thermal pattern in an urban environment. We can establish certain rules on the distribution of the urban green space and the cooling ranges in hot seasons in the surroundings of urban green spaces.

Range inventory is the recognition and evaluation of potential and actual production in order of optimal utilization of this valuable natural resource. Determination of range suitability for medical and industrial plants, considering sustainable utilization and creating models for medical and industrial plants use in Ghareh Aghach of Semirom watershed by FAO (1991) and GIS, was the main objective of this research. Determination of range suitability for medical and industrial plants use, in Ghareh Aghach of Semirom watershed based on a method suggested by FAO and GIS was the main objective of this research. Two criteria’s of vegetation cover and accessibility to water resources were integrated to determine suitability model of medical and industrial plants on rangeland. In vegetation cover criteria, the samples were randomly collected along 3 two hundred meter transects in each vegetation type. Vegetation cover percentage, composition, abundance, and the presence or absence, diversity, production, application and consumption of medicinal plants and industrial were measured using 1m2 quadrates. Accessibility to road and slope determine and by integrating these two criteria, suitability maps based on FAO method were prepared. The results showed that from 7158.69 hectares of study rangelands, 3.69% ha (0.05%), 1761.1 ha (24.6%), 3217.7 ha (44.95%) and 2176.17 ha (30.4%) of the area were classified to S1, S2, S3 and N suitability classes for medical and industrial plant utilization.

The state of groundwater pollution in Torghabeh-Shandiz watershed of Khorasan County has become a major problem, particularly in respect of the increasing population, and the agricultural, industrial and commercial development. The present work attempts to interpret the groundwater vulnerability of this watershed using the DRASTIC model together with the geographic information system (GIS). The data which correspond to the seven parameters (depth to water level, net recharge, aquifer media, soil media, topography, the impact of vadose zone and hydraulic conductivity) of the DRASTIC model were collected and converted into thematic maps with GIS. The study showed that the DRASTIC index shows lies in the range of 68 to 225 which were classified into five zones, very low, low, moderate, high, and very high-risk zone of groundwater contamination. The DRASTIC map illustrates that an area of 15.9% is a very low vulnerability, 20.29% low vulnerability, 26.33% moderate vulnerability, 24.34% high vulnerability and 13.14% very high vulnerability in the study area. The river flows from the northeast region of the watershed allows more recharge of water, which may drain the fertilizers from the surrounding agricultural lands along with it to the groundwater and hence leads to groundwater vulnerability of this region. To check the reliability of the DRASTIC index map in the field condition, groundwater samples were collected for the analysis of nitrate (NO3) which is found as one of the pollutants in groundwater resulting due to use of fertilizers during agriculture. The presence of high nitrate concentration over high to moderate risk pollution zone in the study area validated satisfactorily.

Aquaculture is a rapidly growing industry in developing countries. In Sistan and Balouchestan, the land area used for marine aquaculture increased rapidly in recent years due to a steadily rising demand. The purpose of this research was conducted to identify appropriate sites for shrimp farming development in coastal of the Sistan va Balouchestan province using geographical information systems (GIS) based on creating a database of information layers of effective criteria and alternative. Data layers (Digital elevation model, slope, land use, soil thickness, distance to sea, soil type, soil pH, soil texture, distance to hatchery sites, distance to roads and distance to local markets) were gathered. The weight of criteria and alternatives were determined using an analytical hierarchy process (AHP) in EC2000 software. For modelling, spatial analysis and integration layers ArcGIS setting were used and the zoning map was obtained. By consolidation and overlaying data layers, the final map was drawn in order to classify the aquaculture development in the area in four various zones (highly suitable, suitable, moderately suitable, not suitable). The study revealed 1718 ha (1.2%) is the highly suitable, 12547 ha (9.4%) is suitable, 103164 ha (76.8%) is moderately suitable and 17059 ha (12.6%) is not suitable. This study shows that GIS databases of different formats and sources can be used effectively to establish spatial models in land evaluation for aquaculture. The land evaluation model developed in this study is useful to identify suitable areas for aquaculture in terms of efficient generation, effective conservation, and sustainable land management.