Environmental Sciences
Year:2016 | Volume:14 | Issue:1 |Papers Count:15

Intelligent model optimization is a key factor in the improvement of water treatment. In the current study, we applied artificial neural networks modelling for the optimization of the coagulation and flocculation processes to achieve sufficient water quality control over the total organic carbon parameter. The ANN network consisted of a multilayer feed-forward structure with a back propagation learning algorithm with the output layer of ferric chloride and cationic polymer dosages. The results were simultaneously compared with the nonlinear multiple regression model. The model validation phase was performed using 94 unknown samples for which the prediction result was in good agreement with the observed values. Analysis of the results showed a determination coefficient of 0.85 for the cationic polymer and 0.97 for the ferric chloride models, respectively. He mean absolute percentage error and root mean square errors were calculated, consequently, as 5.8% and 0.96 for the polymer and 3.1% and 1.97 for the ferric chloride models, respectively. According to the results, artificial neural networks proved to be very promising for the optimization of water treatment processes.

The objectives of this study were to evaluate the energy consumption and greenhouse gas emissions and to determine the input sensitivity for wheat the production system in Kermanshah County, Iran. To achieve these objectives, data were collected from120 irrigated wheat farms selected during 2012 using a random sampling method. The sensitivity of the energy inputs was estimated using the marginal physical productivity (MPP) method and partial regression coefficients on wheat yield. The results indicated that the total energy input was 41, 921.8 MJ ha-1, of which approximately 38% and 13% were from nitrogen fertilizers and diesel fuel, respectively. Approximately 57% of the total energy inputs used in wheat production was direct energy, while the remaining 43% was indirect. Total emissions of CO2, N2O and CH4 in alfalfa farms were 1248.1, 855.6 and 1.6 kg ha-1, respectively: Hence, total GWP was 266525 kg CO2e ha-1 and 68.1 kg of CO2e kg-1 of wheat grain produced. The econometric assessment results revealed that the energy inputs of human labour, machinery, diesel fuel, chemical fertilizers had a significant influence on yield. Sensitivity analysis indicated that the MPP value for energy inputs was between -2.8 and 11.31. Also, the MPP value for human labour was the highest, followed by machinery, water for irrigation and phosphorous fertilizer energy inputs, respectively. However, the MPP for biocide energy was calculated as -1.97, implying that the use of biocide energy is excessive in wheat production, causing a problem of environmental risk in the region. Direct, indirect, renewable, and non-renewable energy forms had positive impacts on the output level.

Optimal management approaches can be adopted in order to increase crop productivity and lower the carbon footprint of grain products. The objective of this study was to estimate the carbon (C) footprint and global warming potential of rice production systems. In this experiment, rice production systems (including SRI, improved and conventional) were studied. All activities, field operations and data in production methods and at different input rates were monitored and recorded during 2012. Results showed that average GWP across production systems was equal to 2803.25 kg CO2-eq ha-1. The highest and least GWP were observed in the SRI and conventional systems, respectively. GWP per unit energy input was the least and most in SRI and conventional systems, respectively. Also, the SRI and conventional systems had the maximum and minimum GWP per unit energy output, respectively. SRI and conventional system had the greatest and least GWP per unit energy output, respectively. Therefore, the optimal management approach found in SRI resulted in a reduction in GHGs, GWP and the carbon footprint.

Quantitative description of soil hydraulic properties is crucial for preventing organic contamination entering into the soil and groundwater. In order to assess the hydraulic behaviour of Perchloroethylene as a toxic chlorinated contaminant in soil, the retention curves for Perchloroethylene and water were determined. The Saturated hydraulic conductivity of both fluids examined was determined by the constant head method. The Perchloroethylene and water hydraulic conductivities obtained were 492.84 and 450.27 cm day-1, respectively. The porous medium retention parameters were obtained based on the van Genuchten, Brooks-Corey and Kosugi retention models. Further, the unsaturated hydraulic conductivity for both fluids was obtained based on the Mualem- Brooks- Corey, Mualem-van Genuchten and Mualem- Kosugi models. The accuracy performance of the models was assessed using some statistics including ME, RMSE, EF, CD and CRM. Results indicated that the van Genuchten model provided better estimations than other models when the fluid studied was Perchloroethylene. The results further indicated that the magnitudes of the pore-size distribution parameters and the bubbling pressure parameters are reduced more in a water-air system compared to a Perchloroethylene-air system. This can be attributed to the high viscosity of water and its considerable resistance against flow. This implies that more suction is needed to drain water out from a porous medium than Perchloroethylene. Consequently, a porous medium provides less retention for Perchloroethylene at a given quantity of fluid than water. Owing to lower Perchloroethylene viscosity, the saturated and unsaturated porous medium hydraulic conductivity of Perchloroethylene was greater than that of water. Since Perchloroethylene has lower retention and larger hydraulic conductivity than water, its infiltration into a porous medium would lead to its faster movement towards groundwater.

An agro- ecosystem could be defined as a special ecosystem with various functions which is usually used for production special crops. In recent years, due to unsuitable management and increasing pressures on agro- ecosystems, their functions and structures have been destroyed and so it is necessary to monitor the health of these ecosystems. In order to evaluate agro- ecosystem health in nine western provinces of Iran (i.e. Ardebil, East Azerbaijan, West Azerbaijan, Zanjan, Kermanshah, Kurdistan, Lorestan, Hamedan and Ilam Provinces) the current study was conducted during 2002-2011. Total agro- ecosystem health and its components (namely, structural health, functional health and organizational health) were determined by use of 13 indices for structural health, 11 indices for functional health and six indices for organizational health. Based on the results, agro- ecosystem health in all of the studied provinces was judged weak. The highest and lowest values of structural health were calculated for Kurdistan and Ilam Provinces, respectively. In the case of functional health, the results were different and the highest and lowest values were observed in Kermanshah and Ilam Provinces. For organizational health, the pattern was totally different with highest value calculated for East Azerbaijan Province whereas the lowest value was observed in Kurdistan Province. Finally, total agro-ecosystem health was calculated using the summation of structural, functional and organizational health values. Based on results, Hamedan Province has the best condition of total agro-ecosystem health and Ilam Province has the worst condition in this regard.

Land use planning is a science that specifies the optimized use of land based on its ecological and socio-economic characteristics. Most assessment methods such as that used by FAO, the Iranian method of land capability survey of the environment and its components and also evaluation calculations without prejudice are all based solely on the inherent territory. However, these methods ignore socio- economic factors and estimate land capability incompletely. In this study, we survey the land capability evaluation using GIS and the EMOLUP (geometric mean and calibration methods) model. Then, comparison was undertaken between the different capability evaluation models, such as makhdoum, its revision and arithmetic method for different uses. The results showed that the proposed model (EMOLUP) has higher accuracy for estimating the real capability in the arid and semi-arid study area.

In order to assess soil pollution formed on the alteration zones of Zakhur District, we used 20 ICP-MS analyses. Argillic, argillic- phyllic, advanced argillic, silicic along with Cu, Fe, Pb, Zn, Co, Ni, Au and Ag are the most important decentralized natural resource contaminating agents that have formed extensive heavy/ toxic metal haloes in this area. Diverse environmental pollution indices (e.g. geo- accumulation- Igeo, modified contamination degree- mCd and potential ecological risk- RI) show that the leve of environmental pollution risk of Pb is considerable and, as in different alteration zones, quaternary sediments are also very high. Soils highly contaminated with sulfur result in the high sulfide mineralization character of the alteration zones in Zakhur District. Calculations of the mass changes in argillic and silisic zones indicate enrichment by Cr, Ni, As, Pb and S and loss of Hg and Cd. Besides the positive correlation of heavy metals with each other, there are significant correlations between them and Mn and Al which may have occurred due to the adsorption processes by manganese, iron oxides and/or clay minerals.

Bottom sludge generated in evaporation ponds is one of the most serious waste products from combined cycle power plants. Since previous studies show that wastewater entering evaporation ponds contains various contaminants, the settled sludge can be regarded as a hazardous waste. Waste characterization showed a high concentration of heavy metals (namely, lead and chromium) as well as of Total Petroleum Hydrocarbons in the generated sludge. Regarding to classification criteria of the Basel Convention and other international instruments (such as EPA), we can see that this waste may be categorized as a hazardous waste. As a consequence, all possible methods for sludge management have been evaluated based on their technical, economic and environmental aspects and land disposal was selected as the preferred method. Finally, various scenarios for this, including landfill and surface impoundment, were considered. To avoid the penetration of contaminants into the environment, the IWEM model was used to design the bottom lining system in which different environmental scenarios and leakage concentrations was evaluated.

It is more expensive to remove pollution groundwater than to prevent it and, so, tools are sought that help managers prevent groundwater pollution. One such tool is aquifer vulnerability mapping which is used to specify the most vulnerable parts of an aquifer. In order to prepare the aquifer vulnerability map for Asadabad plain, which is the water resource for agricultural and industrial activities as well as rural consumption in the region, the DRASTIC, SINTACS and SI models were used for exploration of Asadabad plain groundwater, using the following steps. First, in development the initial layers of the models were prepared and the available nitrate layer of the groundwater was also prepared on the basis of 24 measurements of wells taken during spring 2013. In order to evaluate the performance of the models, the correlation between the initial layers and available nitrates layer was calculated. Based on the calculated coefficient correlation and its significance, DRASTIC and SI models were calibrated and than their parameters were modified. Using the overlap of the correlated aquifer vulnerability maps, a contamination danger map for plain was produced which is called an agricultural DRASTIC map. At last, by comparing the vulnerability potential map, modified SI map, modified DRASTIC model, agricultural DRASTIC model and neuro- fuzzy inference map with the available nitrate layer, the best model was distinguished. The result illustrated that the agricultural DRASTIC method (r=0.79) is identified as the best method to evaluate the vulnerable points of Asadabad plain. According to this map, 26.24, 56.63 and 17.13% of the area are located in the least, medium and high vulnerable points, respectively.

As extreme weather events, dust storms are a recurrent feature of the climate that has contributed to severe damage to farmers. The date palm growing sector in Khuzestan province is one of the dust- prone areas that had been severely affected during recent dust storms in the region. This study aims at investigating the factors contributing to date palm orchardists’ resilience to coping with dust stress. The population for this study comprised 157 date palm orchardists residing in Ahwaz County. This study is based on primary sources of data collected from 100 orchardists, following a structured questionnaire survey design. The questionnaire’s validity was confirmed by a panel of experts. The reliability of different scales was measured by the Alpha Cronbach coefficient which ranged between 0.59-0.84. Results revealed that washing dates, using protecting nets, spraying toxins, cultivating other crops between the palm trees and searching for other sources of income were all known as resilience behaviours among orchardists. Path analysis results showed that date palm growers’ perception of resilience (b=0.43) and social motives (b=0.21) contributed positively and significantly to the date orchardists’ resilience behaviour. There was also a significant positive indirect impact between social dialogue and the resilience of date orchardists towards dusty conditions.

Although economic growth is one of the most important objectives of governments, higher economic growth is mainly associated with an increase in environmental pollution. The experience of developed countries and some developing countries shows that, with increasing economic growth, environmental pollution is first increased and, then, it is reduced due to the attention to the environment at the level of production per capita; this can be shown in the Kuznets environmental curve. The main objective of this study is to determine the level of per capita income which causes reduced emissions of pollution due to considering the environmental issues, as well as studying the impact of technology overflow index on the turning point of the curve. In this regard, using the models of the demand of capital- intermediate goods import, the technology overflow index was calculated and its effect on the Kuznets environmental curve theory during the period of 1966 to 2013 was reviewed. The results showed that the technology overflow variable not only had a positive and significant impact on carbon dioxide emissions, but it also made the Kuznets environmental curve's turning point possible at a higher per capita income.

Contamination of the environment by various pollutants has been one of the most important concerns of environmental scientists over the last decade. Water insoluble hydrophilic polymers with contaminants’ surface absorption potential are considered as new materials for the control and removal of pollutants. Carboxymethyl cellulose (CMC) powder with a purity of 87.7 % and 0.5 degrees of substitution (DS) was utilized in the current research project. The aim was to produce a superabsorbent through an environmentally- friendly approach based on bio- based materials. First, in order to insolubilize CMC powder, a wide range of temperature and time were experimented on among which combinations of temperatures of 165, 175 and 180 °C and time periods of 45, 60 and 90 minutes were selected, respectively. Then, a certain amount of heat- modified samples were weighed and dispersed in water and citric acid as a cross- linking agent was added with 0.1, 0.3, 0.5, 2, 3.5, 5, 10, 15 and 20 addition levels based on polymer weight. The samples were evaluated through the Tea Bag, Ionic Sensitivity, Absorption under load (AUL), Deformability and Swelling Kinetic tests. The results showed that heat treatment reduced the consumption of the cross- linking agent in which the highest absorption capacity was observed in low cross-linker addition levels in all tests.

This research was undertaken with the aim of the valuation of the main soil nutrients, placing an emphasis on the forest soil of Shimbar conservation forest in Khozestan Province. Initially, the EPM method was applied for determining erosion and, then, the amount of soil waste of the three main nutrients, namely nitrogene, phosphorus, and potassium based on the differences in soil nutrients of the control and eroded areas. Then evaluation of forest soil nutrients was conducted based on replacement method. The results of this present research showed that, in study area covering 3116ha, 468.5 tons of NPK had been lost due to erosion and this means a cost of 88,202,945,491 Rials to environment. On the other hand, the results also indicated that the studied forest can prevent eroding NPK equal to 28, 306, 465 Rials according to the high value of the canopy cover and forest.

Analysis of raining days is one of the most significant elements of weather forecasting concerning agricultural section, since rainfall is the most unstable factors and shortage or rainfall during growing season may create heavy damages on agricultural section, particularly on dry farming. Necessity of monitoring and analysis of this phenomenon could be demonstrated when we consider that a great part of agricultural lands depends on rainfall (amount and number of times) directly. Meanwhile, the significant performance of farming products will be related to raining method also in irrigation agriculture section. In the present study, number of raining days in Qazvin synoptic station, to analyze and study pathologically wheat cultivation by dry farming in the province, statistical models were used. Results of statistical analysis of number of raining days demonstrated that number of raining days in wet years in autumn cultivation season with recurrence interval of 5, 10, 25 and 50 year based on 29, 32, 39 and 44 days, respectively. Furthermore, in dry years, number of raining reliable days can be 8, 4, 0 and 1 day. In this regard, to investigate and study pathologically dry farming in the province, a statistical analysis was performed about raining days during growing season for wheat product. Findings of the analysis showed that in dry periods, dry farming is not appropriate and no reliable rainfall will be occurred during growing period.