Energy and GHG emissions management of agricultural systems using multi objective particle swarm optimization algorithm: a case study

In the recent centuries, one of the most important ongoing challenges is energy consumption and its environmental impacts. As far as agriculture is concerned, it has a key role in the world economics and a great amount of energy from different sources is used in this sector. Since researchers have reported a high degree of inefficiency in developing countries, it is necessary for the modern management of cropping systems to have all factors (economics, energy and environment) in the decision-making process simultaneously. Therefore, the aim of this study is to apply Multi-Objective Particle Swarm Optimization (MOPSO) to analyze management system of an agricultural production. As well as MOPSO, two other optimization algorithm were used for comparing the results. Eventually, Taguchi method with metrics analysis was used to tune the algorithms’ parameters and choose the best algorithms. Watermelon production in Kerman province was considered as a case study. On average, the three multi-objective evolutionary algorithms could reduce about 30 % of the average Greenhouse Gas (GHG) emissions in watermelon production although as well as this reduction, output energy and benefit cost ratio were increased about 20 and 30 %, respectively. Also, the metrics comparison analysis determined that MOPSO provided better modeling and optimization results.     

Tracing water resources flows by complementary use of hydrological and water accounting models

Historically, there has been a dispute over water allocation between users and policymakers in Iran's Zayandeh-Roud Basin (ZRB). In this study, we used the “System of Environmental-Economic Accounting for Water” (SEEAW) framework in combination with the hydrologic model “Soil and Water Assessment Tool” (SWAT) to achieve the water balance in ZRB. We used SEEAW to combine a wide range of water-related statistics across stakeholders and SWAT to evaluate the unknown agricultural water use. The SWAT model is calibrated based on the stream flows and crop yields in the basin. The model assess the renewable water of the basin into two components, about 363 and 70 mm as green and blue water, respectively. Also results from the physical water supply and water use tables demonstrates that the agricultural sector uses 78% of the total renewable freshwater, followed by the residential, 16%, and the industrial sector, 6%. The flows of water from source to services in ZRB are traced based on the water supply and water use tables. The flow diagram shows that 8 MCM of industrial reused water was transferred to the agricultural sector, and 137 MCM and 18 MCM of water from the wastewater treatment plants to the agricultural and industrial sectors, respectively. Furthermore, the results show that the index of the basin dependence on groundwater resources is high (61%), the value of water stress is high (0.88) and the dependence of the basin on transboundary water resources is 30%. Therefore, this method is highly beneficial for achieving a conceptual water balance in disputed basins without enough agricultural water uses data.     

A comprehensive analysis of physiologically equivalent temperature changes of Iranian selected stations for the last half century

As a preliminary and major step for land use planning of the coming years, the study of variability of the past decades’ climatic conditions with comprehensive indicators is of high importance. Given the fact that one of the affected areas by climatic change includes variability of thermal comfort, this study uses the physiologically equivalent temperature (PET) to identify and evaluate bioclimatic conditions of 40 meteorological stations in Iran. In this study, PET changes for the period of 1960 to 2010 are analyzed, with the use of Mann-Kendall non-parametric test and Pearson parametric method. The study focuses particularly on the diversity in spatio-temporal distribution of Iran’s bioclimatic conditions. The findings show that the mean frequency percentage of days with comfort is 12.9 % according to the total number of selected stations. The maximum and minimum frequency percentage with values of 17.4 and 10.3 belong to Kerman and Chabahar stations, respectively. The findings of long-term trend analysis for the period of 1960–2010 show that 55 % of the stations have significant increasing trend in terms of thermal comfort class based on the Pearson method, while it is 40 % based on Mann-Kendall test. The results indicate that the highest frequency of days with thermal comfort in the southern coasts of Iran relates to the end of autumn and winter, nevertheless, such ideal conditions for the coastal cities of Caspian Sea and even central stations of Iran relate to mid-spring and mid-autumn. Late summer and early autumn along with late spring can be identified as the most ideal times in the west and northwest part of Iran. In addition, the most important inhibiting factors of thermal comfort prove to be different across the regions of Iran. For instance, in the southern coasts, warm to very hot bioclimatic events and in the west and northwest regions, cold to very cold conditions turn out to be the most important inhibiting factors. When considering the variations across the studied period, an increase in the frequency of thermal comfort condition is observed in almost half of the stations. Moreover, based on Pearson and Mann-Kendall methods, the trend of changes in monthly averages of PET has decreased in most stations and months, which can lead to different consequences in each month and station. Thus, it is expected that due to PET changes in recent decades and to the intensified global warming conditions, Iran’s bioclimatic conditions change in a way that transfers the days with comfort to early spring and late autumn.     

Electrokinetic remediation of perchloroethylene-contaminated soil

One large group of persistent and toxic contaminants is the hydrophobic organic contaminants. Among them, perchloroethylene (PCE) has been recognized as a representative group of these pollutants with low solubility. This study reports on the effects of electrokinetic remediation with non-ionic surfactant on PCE-contaminated soil. The performance of electrokinetic process was investigated in the treatment of clay soil that artificially contaminated with two levels: 10,000 and 30,000 mg/kg PCE and 0.33 g/kg Triton X-100. A DC power supply with electric voltage (1 V/cm) was used for 8–16 days. A negatively charged soil surface resulted in a more negative zeta potential and greater electroosmotic flow toward the cathode. The PCE was measured after extraction using n-hexane and analyzed by Fourier transform infrared spectroscopy instrument. The water content of soil was kept 25 % (w/w). Results were shown that PCE removal efficiency achieved was 74 and 89 % for 10,000 and 30,000 mg/kg PCE, respectively, for 16 days. Therefore, in this study, the integration of electrokinetic with non-ionic surfactant as a hybrid method was most effective for the remediation of PCE-contaminated soils.     

Phytoremediation potential of native plants grown in the vicinity of Ahangaran lead–zinc mine (Hamedan,Iran)

This study aims to assess the extent of metal accumulation by plants found in a mining area in Hamedan Province in the central west part of Iran. It also investigates to find suitable plants for phytoextraction and phytostabilization as two phytoremediation strategies. Plants with a high bioconcentration factor (BCF) and low translocation factor (TF) have the potential for phytostabilization while plants with both BCFs and TFs greater than one have the potential to be used for phytoextraction. In this study, shoots and roots of the 12 plant species and the associated soil samples were collected. The collected samples were then analyzed by measurement of total concentrations of trace elements (Pb, Zn, Mn and Fe) using atomic absorption spectrophotometer. Simultaneously, BCF and TF parameters were calculated for each element. Results showed that although samples suitable for phytoextraction of Pb, Zn, Mn and Fe and phytostabilization of Fe were not detected, Scrophularia scoparia was the most suitable for phytostabilization of Pb, Centaurea virgata, Echinophora platyloba and Scariola orientalis had the potential for phytostabilization of Zn and Centaurea virgata and Cirsium congestum were the most efficient in phytostabilization of Mn. Present study showed that native plant species growing on contaminated sites may have the potential for phytoremediation.     

Assessing the Performance of Independent Component Analysis in Remote Sensing Data Processing

Independent component analysis (ICA) is a novel method to be considered as a powerful type of analysis in the process of source signal separation. Based on the capabilities of this particular analysis, there will be a hypothesis of applying ICA in the image processing of remote sensing data. This paper aims to introduce the ability of ICA in contrasting and highlighting some area with potential of mineralization. Considering and applying ICA transformation on the ETM⁺ image of southern Masule, Iran has resulted in finding some favorable points for further investigation. Moreover, sampling program on the indicated area has led to identify some huge, unexpected lithology and dikes. ICA analysis is a robust method even in remote sensing data processing with the high speed and capabilities in separating source signals from noise.     

Accumulation of heavy metals in soil and uptake by plant species with phytoremediation potential

Contamination of heavy metals represents one of the most pressing threats to water and soil resources, as well as human health. Phytoremediation can be potentially used to remediate metal contaminated sites. In this study, concentrations of copper, zinc, iron, and magnesium accumulated by native plant species were determined in field conditions of Hame Kasi iron and copper mine in the central part of Iran in Hamadan province. The results showed that metal accumulation by plants differed among species and tissue bodies. Species grown in substrata with elevated metals contained significantly higher metals in plants. Metals accumulated by plants were mostly distributed in root tissues, suggesting that an exclusion strategy for metal tolerance exists widely amongst them. The mentioned species could accumulate relatively higher metal concentrations far above the toxic concentration in the plant shoots. With high translocation factor, metal concentration ratio of plant shoots to roots indicates internal detoxification metal tolerance mechanism; thus, they have potential for phytoextraction. The factors affecting metal accumulation by plant species including metal concentrations, pH, electrical conductivity, and nutrient status in substrata were measured. Mostly, concentrations of zinc and copper in both aboveground and underground tissues of the plants were significantly, positively related to their total in substrata, while iron, zinc, and copper were negatively correlated to soil phosphorus.     

Spatial modelling of hazardous elements at waste dumps using geostatistical approach: a case study Sarcheshmeh copper mine,Iran

Mining activities and resulting wastes can be considered as one of the most important sources of hazardous elements in the environment. Knowledge of the spatial distribution of toxic elements in waste dump systems is necessary to assess environmental hazard and strategy. To achieve this goal, this paper investigates spatial distribution of toxic elements using statistical and geostatistical analysis. A total of 58 soil samples were collected, and the amount of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb and Zn was then determined at “Sarcheshmeh” copper mine waste dumps. In order to evaluate the presence of multivariate outliers, Mahalanobis distance technique (D ²) was applied and the multivariate outlier samples were removed. This resulted in an increase in correlation coefficient. To reduce dimension of data set, principal component analysis was applied and four principal components were determined which indicate 83.463% of the total variance of data set. Estimated PCs together with the toxic elements maps based on the ordinary kriging display aggregation of toxic elements in some parts, and validity of predictions was evaluated using the leave-one-out cross-validation method. The regression coefficients of estimated and observed values presented the reliability of the kriging estimates. Sequential Gaussian simulation method was applied for principal components due to similar results of estimated principal components and toxic elements. The results of simulation maps are almost identical to estimated outcomes.