abdolreza karbassi

Photo-electro-catalysis process has received major attention in the past decade as a substitutional wastewater treatment technology. Photo-electro-catalysis process is widely employed for removing different pollutants (organic, and inorganic (cationic and anionic)) from wastewater. It has been recently developed by modifying the photo-reactor system, the experimental parameters, and the structure of photo-anodes during preparation to enhance the pollutants removal from wastewater, reduce their adverse health risk resulting from environmental accumulation, and give a chance to reuse the treated wastewater for a variety of applications. This review aims to summarize recent studies (especially in the last five years) that developed the photo-electro-catalytic degradation system of organic, heavy metal, and mixed pollutants under UV light, visible light, and sunlight. This review demonstrates the effect of experimental variables, photo-reactor arrangements, mass transfer, phase, length, and diameter of nanoparticles or tubes on the anode, type of deposition on the anode, and cathode characteristics (type and dimensions) on the photo-electro-catalytic technologies. The drawbacks of photo-catalysts, affecting the photo-electro-catalytic properties, are also discussed and solved. Finally, the review focuses on the photo-electro-catalysis enhancements by combining this process with other proven treatment processes. This review can provide perspectives on the important factors that evolve photo-electro-catalysis for the complete purification of polluted wastewater in the future.

Industrial plating wastewater contains various types of detrimental heavy metals in high concentrations. One of this toxic metal is Nickel that its discharge into the surface waters and soil is considered as an environmental problem. Hence removing of this metal from wastewaters is crucial and vital for protecting the environment and human health. Applying of nanotechnology in elimination of environmental contaminants is one of the methods which attracted a great deal of attention in recent years. In present research, nanographite was utilized as efficient adsorbent in order to remove Ni ions.

In order to investigate the adsorption process, nanographite with a purity of 99.9% and a specific surface area of ​​18-24 m2/g and a plate morphology was prepared from Pishgaman Iranian Nanomaterials Company and used as an adsorbent. Also, the wastewater used in the experiments was prepared from one of the plating workshops in Tehran, which contained 765 mg/L of nickel and a pH of about 1. The parameters of pH, time and amount of adsorbent were evaluated. In each experiment, one of the parameters was considered variable and the other two parameters were considered constant. The amount of nickel was determined before and after each test.

In this study, the parameters including pH, adsorption time and adsorbent dosage were investigated as effective factors on Ni adsorption process. In order to analyze the adsorption mechanism, the obtained results were examined by the Langmuir and Fruendlich isotherm models. In addition, pseudo-first-order and pseudo-second-order models were studied to investigate adsorption kinetics. According to the results, the Ni uptake by nanographite was enhanced significantly with increasing of the pH value from 5 to 7. Thus the pH of 7 was determined as optimum pH for Ni removal. Investigations also showed that increasing the time up to the first 80 minutes had a relatively good effect on nickel adsorption by the nanoparticle, and after that the adsorption almost reached equilibrium. Finally, it was observed that in a constant time, increasing the amount of adsorbent led to an increase in adsorption, and to achieve the maximum adsorption of nickel, the amount of 2g was chosen for the adsorbent. Based on the obtained results, 97.52% primary nickel was adsorbed by nanographite. Results also revealed that the data were best fitted to the Fruendlich models. After determining the amount of nickel adsorption at different times, the resulting data were analyzed by the kinetic model.Kinetic studies also indicated that the adsorption data were described well by pseudo-second-order model.

Examining the results showed that pH plays an important role in the adsorption process and the adsorption rate increases with increasing time until the equilibrium time is reached. One of the effective factors is the amount of adsorbent, which has a direct effect on adsorption. Following the Freundlich isotherm in this research indicates that the adsorption sites in the adsorbent have different energies. Also, the pseudo-second-order model in adsorption kinetics refers to the process of chemical adsorption in addition to physical adsorption.

Naphthenic acids are a group of polar organic carboxylic acids that are present in crude oil naturally. They are cycloaliphatic carboxylic acids which have 10 to 16 carbons, which gained importance since the early twentieth century because of corrosion in oil refineries. Moreover, they are the most important environmental pollutants caused by oil extraction from oil sand reserves. Heavy crude oils which have high concentration of naphthenic acids are usually considered as poor-quality oil and sold at a lower price. Often, the high concentration of naphthenic acids in crude oil reduces the life of the equipment which are used in the exploration and refining process because of corrosion. Hence, researchers are increasingly interested in the chemical properties of naphthenic acids and the acidic components of the crude oils. The most popular methods for the identification and analysis of naphthenic acids are liquid and gas chromatography (GC), liquid-liquid extraction, Fourier transform infrared spectroscopy (FTIR), and solid-phase extraction (SPE). Naphthenic acids are the most important environmental pollutants caused by oil extraction from oil sand reserves. Previous studies have revealed that naphthenic acids can be absorbed by fish, but their distribution in different tissues of fish has not been specified. Experimental samples showed the highest toxicity to fish, while there was less toxicity to invertebrates and algae. Moreover, naphthenates have various industrial utilizations; they are used in synthetic detergents, corrosion inhibitors, lubricants, fuel and oil additives, wood preservatives, insecticides, fungicides, pesticides, wetting agents, napalm thickening agents, and oil desiccants that are utilized in painting and treating wood surfaces.

An accurate estimation of air quality and meteorological conditions is required to make the sound air pollution management decisions. Thus, the data analysis from monitoring stations is unavoidable in air pollution research.  The present study uses the statistical tests to survey the homogeneity of meteorological factors and air quality station data in Mahshahr.

At first, a decade's worth of meteorological station data and the data from air quality stations in Mahshahr were collected over 2016-2019. The minimum and maximum values, standard deviation, variance, skewness, and kurtosis of parameters were then calculated, and heterogeneities and improbable fluctuations in the data were examined.

The results indicated that an average of 12% of data from the meteorological station in the special region were invalid, and that the data from this station had a non-normal distribution. Moreover, 98% of meteorological data collected at Mahshahr airport were valid which had a normal distribution. Statistical analysis of pollutant concentration data from air quality stations revealed that among 21 pollutants monitored across four air quality stations in the study region, only PM2.5 in Mahshahr station, NO2 in the mobile station, and CO, O3 in the special region fix station yielded normal distributed data.

Consequently, when compared to other regional stations, the data from special zone's fixed air quality station, and Mahshahr meteorological station were the most reliable, with an average invalid data percentage of 16.4 and 0.48, respectively. Finally, it is recommended that the data should be adjusted to a more normal distribution over the desired period before using the data from other stations.

The present research has been performed to investigate the opportunities and challenges facing the Iran’s renewable energies development to reduce climate change and improve health and represent managerial solutions in power generation sector by SWOT-AHP analysis models.

Using literature reviews and survey, the SWOT was applied to identify internal factors includeding strengths (S), and weaknesses (W), and external factors includeding opportunities (O), and threats (T). The strategies were drived to develop renewable energy in Iran. The proposal strategies were ranked by using the SWOT matrix and analytic hierarchy process (AHP) model.

According to the SWOT matrix calculations, total scores of internal and external factors were found as  4.1 and 4.4 of 5, respectively, which show high potentials of internal factors and opportunities. The most importannt factor of strengths (S) was found to be the great potentials of solar energy sources in Iran. The main priority of opportunities (O) is supportive laws to encourage the private sector. The most important weakness (W) was lack of comprehensive knowledge of managers and politicians about the benefits of renewable energy. The main threats (T) were low tendency of private invests, unpredictable inflation in Iran, and low prices for fossil fuels.

The results of this research represent in four categories of SO, ST, WT, WO strategies. The important SO strategy is increasing guaranteed electricity purchase tariffs (GEPTs), and creating the renewable energy market. The most important strategies of ST were establishment of the renewable energy fund and assessment of exporting electricity by the private sector. The most dominant strategy of WT was modifying guaranteed electricity purchase contracts. The strategies of WO were found to be as following; convincing government agencies to provide the necessary infrastructure and support for knowledge-based companies.

In recent years, due to limited water resources and the extraordinary increase in nitrates in the environment, efforts to remove and control in order to benefit from the natural adsorbents have been made. Although according to the negatively charged surface of bentonite particles, absorbent needs improvement.

In the current study, the adsorption of nitrate columns by the modified calcium montmorillonite adsorbent was investigated. Furthermore, In order to change the surface load and increase the adsorption efficiency, three-step acid leaching, oxidation layering, and loading of the cationic surfactant hexadecyltrimethylammonium bromide on the adsorbent were performed. Molecular interaction and crystallography of pure montmorillonite and synthetic nano-adsorbent (ACZ) were characterized by Fourier transform infrared spectroscopy and X-ray analysis. Moreover, the morphology of ACZ nano adsorbents was evaluated using Transmission electron microscopy and scanning electron microscopy.

Nanoparticle compaction and less access to pores and cavities in the fixed bed column reduced the adsorbent capacity inside the column compared to the discontinuous system.The results showed that an increase in inlet concentration from 80 to 150 mg/L increased the adsorption capacity from 67.39 to 88.25 mg/g. Reducing the inlet flow rate increased the penetration time, interaction, and greater access to the binding sites for nitrate ions and finally improved the column performance and increased the inlet flow rate reduced the adsorption capacity and breakthrough time. Therefore, the adsorption of nitrate ions by the stage of internal mass transfer is controlled and depends on the duration of interaction and the possibility of penetration into the active sites. With increasing the bed height from 4.2 to 9 cm, there was a significant increase in adsorption capacity from 60.608 to 77.167 mg/g. The effect of detergents and recovery showed an absorption column; After 3 leaching steps, acid leaching played an important role in increasing column recovery. Experimental data with correlation coefficients of R2>0.95 corresponded to Thomas and Yoon-Nelson kinetic models.In this study, the ACZ nano adsorbent column for rapid removal of nitrate ions from aqueous solutions was introduced and for use in reusable systems was proposed.

Ordinary Kriging (OK) has been widely used for prediction and spatial distribution study of surface water quality parameters. This method uses a constant mean to capture the trend in the model. In this method, the prediction can be poor if there are strong trends. To overcome this problem, an alternative model called Blind Kriging (BK) was developed. The mean function in BK is polynomial and the unknown mean function parameters are obtained using the Bayesian variable selection technique which requires a lot of calculations. To solve these problems, in the present study, OK was modified based on BK. In the modified method, the polynomial mean function parameters were determined using linear Regression instead of Bayesian inference method. Then, the performance of OK and modified Kriging in the estimation of trophic indices and water quality parameters in Anzali Wetland was evaluated using different statistical criteria (the coefficient of determination, the root mean square error and the mean absolute error). For this purpose, the concentrations of 14 parameters in six sampling points of Anzali Wetland water were analyzed during 2018. Subsequently, the modified and Ordinary Kriging were applied to water parameters and trophic indices. The results showed that the modified Kriging had the best results. In addition, the improvement of the modified Kriging compared to OK is achieved up to 88%. The results of the present study can be useful in the planning of the future monitoring program in Anzali Wetland.

The HVO production unit is one of the refineries' pollutant units, which often has a CO, THC, NOx, SOx and CO emissions higher than the standard limits. By investigating the operational parameters and determining their effect on pollutants, the viscosity of the feed was determined as one of the important parameters and evaluation measure. The emitted amount of CO pollutant was measured in several feeds with different viscosity characteristics, by decreasing the pollutants temperature, changing combustion chamber temperature(energy consumption)and adjusting other process and production conditions in two product categories: HHVO, LHVO. The amount of CO pollutant emission from LHVO production process is far less than the HHVO production and this amount is reduced by increasing the viscosity of the feed and reducing the outlet pollutant temperature of the reactor. For example the amount of CO emission in same operational condition is 1280 mg/nm3 for LHVO process but for HHVO process is 1740 mg/nm3 and the amount of this pollutant is 1619 mg/nm3 for HHVO process in normal emission process but decrees of pollutants temperature has resulted in decrease of emission to 690 mg/nm3. Finally, the results was analyzed and reported in accordance with the specified parameters.

Monitoring the magnetic properties of suspended particles in the air deposited on the leaves of trees provides useful information on the spatial distribution of the suspended particles in urban and industrial areas. This study was carried out to extend and develop the application of peripheral magnometry method to investigate environmental pollution and metal contaminants resulted from vehicle traffic in some areas of Tehran with heavy traffic. The leaves of Platanus Orientalis in the inland areas of Chitgar Park as a clean area and Azadi Square and Geisha Bridge as crowded areas were collected. Magnetic components such as natural magnetic residual, mass magnetic susceptibility, isothermal magnetic residual and saturated induction magnetic residual were measured in the samples. The concentration of copper, iron, lead and cadmium was measured by mass spectrometry and the relationship between magnetic components and metals was investigated. The results showed that the highest value of susceptibility and magnetic residual of leaf saturation was associated with heavier traffic of vehicles in Azadi and Geisha. The study of the composition of particles in the Chitgar showed a combination of hard ferromagnetic minerals such as hematite with high concentration and soft ferromagnetic minerals with low concentration, which are the result of the activities of the peripheral industries and traffic in Tehran-Karaj highway. The presence of soft magnetic minerals in both Azadi and Geisha regions was higher than Chitgar. In Azadi, the size of particles was larger and the mineral behavior indicated a combination of the presence of soft and hard minerals, while the size of particle was smaller in Geisha.

The application of kriging in the field of environment is focused on four main sections: mapping of precipitation, quantitative and qualitative status of groundwater, quantitative and qualitative evaluation of surface water and spatial forecasting of air quality (Hanefi Bayraktar,2005; Nas, 2009; Chen et al., 2016; Sharma et al., 2017; Yang et al., 2018).
Different types of kriging have been developed, but the most popular of these is ordinary kriging (OK). The most important disadvantages of OK is that it assumes the mean of modelled variables to be constant and the prediction is only based on the spatial structure of the studied points. In addition, the effect of important parameters does not take into account the estimation result, and in some cases the predicted values by OK may be out of the studied range (Mukhopadhyay et al., 2017; Montero and Matthew, 2015). To overcome these problems, the universal kriging and blind kriging have been developed. Blind kriging (BK) is a more complete version of universal kriging and is based on Bayesian variable selection technique which is complicated and takes a lot of time to identify the unknown mean function.
In this research, due to the complexity of the Bayesian computation, we will combine the regression technique with blind kriging as the unknown mean function is defined by variable selection techniques that are used in linear regression analysis such as forward selection, backward elimination, and step-wise regression. The residuals at the known points are calculated from the difference of the observed values and the values of the selected function. Then the residual mean at the unknown point is solved by OK method.
Tajan River is one of the most important rivers in Mazandaran province. This permanent river is about 140 kilometers long and originates from the mountainous area on the northern slopes of Alborz Range. Tajan River runs to the plains carrying the water from various tributaries in the mountains and then drains into the Caspian Sea. Dodangeh, Lajim, Chahardangeh and Zarem rivers are the most important branches of it. The area of Tajan River watershed in the Aldehil region (before entering the Caspian Sea) is 4700 square kilometers. There are different land uses including agriculture, aquaculture, dam construction and industrial activities around the river. The necessity to perform a systematic study of the river water quality is, therefore, a need and of prime importance.
The objective of this study is to evaluate water quality parameters in different sites on Tajan River. This study also attempts to propose a modified kriging method, in which the unknown mean function is defined by using linear regression in order to simplify the computations of blind kriging. The proposed method and ordinary kriging were used to model the spatial variability of heavy metals and water quality index and their results were compared. This case study may be counted as an initial effort to study the spatial variability of water quality parameters, which may have many practical implications

The water sampling took place in spring of the year 2018. Sampling sites were selected based on natural conditions and accessibility to Tajan River by taking into account natural and human impacts, including river sub-branches, changes in the polluting sources such as agricultural lands, residential centers, existing industries, etc. Sampling sites were named 1 to 10 from downstream (near the Caspian Sea) to upstream (the Shahidrajae Dam). Water samples were collected by Nansen bottles and transferred into 1-liter bottles previously cleaned by nitric acid (0.1 N). The temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), redox potential (Eh), and turbidity (Turb) of each water sample were directly measured at the sampling points. The biochemical oxygen demand (BOD5) was determined by the Winkler Azide method and chemical oxygen demand (COD) by the dichromate reflux method. Phosphate (PO4-P) and Nitrate nitrogen (NO3-N) were analyzed by spectrophotometric method, and fecal coliform (Fcoli) were measured by multiple tube method.
For measuring metals, each water sample was filtered through Whatman filter (0.45 μm) and about 5 mL of HNO3 (0.1 N) was added to the samples (until pH<2). Then, the samples were stored in the refrigerator at a temperature below 2 °C until being transferred to the laboratory. The measured elements included Arsenic (As), Barium (Ba), Calcium (Ca), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Nickel (Ni), Lead (Pb) and Thorium (Th). Metal measurements were done by inductively coupled plasma optical emission spectrometry (ICP-OES). Analysis of the samples was done based on the instructions recommended by (APHA, 2005).
All mathematical and statistical computations were made using EXCEL 2016, SPSS 22 and ArcGIS 4.10.1.
The proposed method and ordinary kriging method were applied to interpole and predict IRWQI, Fe, Ni, Co, Th, Ba, As, Pb and Cr and their results were compared.

IRWQI had low values in midstream (sites 5, 6 and 7) near Sari City and its value increases by moving away from the city to show an improvement in the water quality status. This is due to the effect of anthropogenic pollutants in Sari city which are negatively associated with the water quality index. The average range of pH was from 7.6 to 8.11. pH values of water samples indicated that it was slightly alkaline. The relatively higher pH in water are probably due to the presence of pollution and eutrophication status. The mean values for Eh ranged from 142 mV to 201 mV. The water of Tajan River (excepting in site 1 near the sea) is non-saline.
The mean function for each variable (IRWQI, Fe, Ni, Co, Th, Ba, As, Pb and Cr) was created by multiple linear regression. The coefficient of determination (R2) and adjusted R2 were used to check regression model adequacy. t-Test and residual analysis were used in testing the regression coefficients verifying of the applicability of the regression model. The coefficient of determination (R2) ,Coefficient of Variance (C.V.) and Root Mean Square Error (RMSE) were used to evaluate the results of the ordinary kriging and proposed method. The proposed method showed 8.8 percent improvement for Cr, 34 for Co, 56 for Pb, 62 for As, 44 for Ba and 169 for IRWQI. In addition, both methods for prediction of thorium and nickel were almost identical. While ordinary kriging performance was good in predicting iron and better than the proposed kriging, because for parameters whose correlation is strong with distance and spatial distribution, ordinary kriging method can work well in modeling them. the mean concentration of elements in the water followed the following pattern: Ca> Fe > Ba > Ni > As > Cr > Cu >Th> Co > pb. The mean concentration of elements (Co, Cr, Ni, Cu, pb and Th) demonstrate a similar pattern with a decreasing trend from the upstream to the downstream. This will strongly show a similar process and origin. while the mean concentration of Ba and As was increased at various sites from the upstream to the downstream.

This study was conducted to investigate organoclay prepared using montmorillonite clay with zinc oxide (ZnO) nanoparticles and a long-chain organic surfactant hexadecyltrimethylammonium bromide for the removal of nitrate ion from aqueous solutions. Adsorbents were evaluated by X-Ray Diffraction (XRD), Fourier Transform Infra-Red (FT-IR), Transmission Electron Microscopy, Brunauer-Emmett-Teller, Emission Scanning Electron Microscopy, Energy Dispersive X-ray (EDX) spectroscopy devices and adsorption isotherms of nitrate ion on the best adsorbent were measured at the aqueous concentrations of 40 to 150 mg/25 mL. Activated montmorillonite-ZnO showed a much higher adsorption capacity than other materials. The laminated ZnO and modified surfactant enhanced nitrate ion, thus retaining silicates capacity, montmorillonite (17.24 mg/g) < montmorillonite by laminated ZnO (54.05 mg/g) ˂ montmorillonite modified by a surfactant (86.95 mg/g) < montmorillonite loaded by ZnO and surfactant (119.92 mg/g). The adsorbents for the removal of nitrate ion were studied and then regenerated with HCl solution (0.1 M) to be reused in adsorption. Adsorption data of nitrate ion could be interpreted using Langmuir isotherm and pseudo-second-order kinetic model. Therefore, activation of Montmorillonite/ZnO could be used as a suitable adsorbent to separate nitrate ion from wastewater and groundwater.

The present study aimed to evaluate the health risk of heavy metals (iron, zinc, cadmium, arsenic, nickel, lead, and mercury), benzene, toluene, ethylbenzene and xylene (BTEX), and polycyclic aromatic hydrocarbons (PAHs) in the workplace in a secondary oil re-refining factory. In this descriptive, cross-sectional study, samples were collected and analyzed using the NIOSH 1501 method at eight sampling points with determined concentrations of BTEX, 16Ʃ PAHs, and heavy metals. The concentration of each pollutant was evaluated based on the type of workers (packaging/filtration). The risk assessment of the contaminants was carried out using the RAIS software, and the risk of non-carcinogenic compounds was estimated based on the reference respiratory concentration (mg/m3). The results showed that the lifetime cancer risk index (LCR) cumulative risk of the heavy metals was within the definitive risk range at all the sampling points. The highest carcinogenic risk of LCR belonged to arsenic at sampling point H (filtration chamber), and the highest cumulative carcinogenic risk of the total contaminants in the environmental sampling points belonged to sampling point H. At all the sampling points, the LCR carcinogenic risk accumulation for the hydrocarbon compounds was within the definitive range. The maximum cumulative lifetime cancer risk for the hydrocarbon compounds was evaluated in filtration (point B), and the most hazardous carcinogens were arsenic, benzo(a)pyrene, and naphthalene. The proposed risk assessment method was observed to be comprehensive, and its results could be used for corrective and controlling measures and the prioritization of risk reduction resources.

Drought is an integral part of natural hazards. It usually occurs gradually and without any warning. Moreover, this phenomenon is usually created over time and does not disappear quickly Recently, some factors such as climate variability and the impact of climate change have influenced drought frequency and intensity in many parts of the world. Various definitions have been provided for drought but in general the lack of water resources in a specific period in a geographical area is considered as drought which implies this phenomenon as a regional hazard. IRAN is located in an arid and semi-arid region in which it experiences drought frequently. There are different types of drought such as meteorological, hydrological, agricultural and social-economic. These types are differentiated based on the factor which is rainfall, river flows, soil moisture, and social-economic consequences. There are many indices proposed for measuring drought severity; among them Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI) and Surface Water Supply Index (SWSI) could be mentioned. Each of these indices has its own pros and cons and is suitable for a particular type of drought. Therefore knowing the types of drought can provide a better understanding of shortages and their characteristics. Various factors are utilized for measuring these indices including precipitation, reservoir storage, discharge, temperature and potential evapotranspiration. In this study the three main aforementioned indices were first calculated for Aharchay watershed, located in East Azerbaijan province. Next based on combining these three indices with another two important parameters, groundwater level and solar radiation, a combined drought index is developed and calculated for the studied region. Considering the fact that the aforementioned parameters and indices have different level of importance in combined index, different weights based on expert opinions are assigned to the parameters considering how critical each parameter is in the overall drought analysis. This combined index demonstrated various climatic, hydrological and agricultural aspect of the region. In the next step, bivariate analysis of the two variables, intensity and duration, is carried out using copula. This is done by first checking the dependency between intensity and duration using Pearson, Spearman, and Kendall correlation coefficients. Second, various copula functions were fitted such as Gaussian, T, Clayton and Gumbel functions. Third, based on the Ordinary Least Square (OLS) and Kolmogorov–Smirnov (K-S) tests, the best copula functions were used. Lastly, based on the chosen copula the joint probability distributions were obtained. Two cases named “OR” and “AND” were defined for joint probability of the two variables and different return period curves is drawn. The results showed that the most severe drought in this watershed occurred in June 2004. Moreover, by assessing correlation coefficient between the considered indices it is shown that analysis of the drought in a region based solely on one index would neglect other imperative aspects in drought determination which necessitates a more integrated indicator. Furthermore, in bivariate analysis, return periods of “AND” cases were more than “OR” case. The results of this study could be utilized in preparedness and monitoring drought.