Groundwater Vulnerability Assessment Using Fuzzy Logic: A Case Study in the Zayandehrood Aquifers, Iran

Groundwater is an important source of water, especially in arid and semi-arid regions where surface water is scarce. Groundwater pollution in these regions is consequently a major concern, especially as pollution control and removal in these resources are not only expensive but at times impossible. It is, therefore, essential to prevent their contamination in the first place by properly identifying vulnerable zones. One method most commonly used for evaluating groundwater pollution is the DRASTIC method, in which the Boolean logic is used to rank and classify the parameters involved. Problems arise, however, in the application of the Boolean logic. In this paper, the fuzzy logic has been used to avoid the problems. For this purpose, three critical cases of minimum, maximum, and mean values have been considered for the net recharge parameter. The process has been performed on the Zayandehrood river basin aquifers. The fuzzy-DRASTIC vulnerability map thus obtained indicates that the western areas of the basin generally have the maximum pollution potential followed by the areas located in the east. The central parts of the study area are found to have a low pollution potential. Finally, two sensitivity analyses are performed to show the significance of each value of the net recharge parameter in the calculation of vulnerability index.     

An integrative framework for sustainable supply chain management practices in the oil and gas industry

This paper proposes a framework for understanding the contextual factors of sustainable supply chain management (SSCM) practices in the O&G industry. It is based on a literature review of studies related to SSCM of O&G topics. The review reveals that there is a lack of SSCM research specific to the industry. Present studies focus on individual stages of its supply chain and do not consider all dimensions of sustainable development, namely economic, environmental and social factors. In addition, existing frameworks lack important contextual aspects of the industry's business and organizational environment. To address these gaps, our research develops an overarching framework operationalizing the internal and external contextual factors of the O&G industry environment that can influence the outcome of its SSCM practices. The proposed framework is useful as a tool in the formulation and implementation of SSCM strategy that enables alignment of a company's internal capabilities with its external environment.     

Performance evaluation of a continuous flow photocatalytic reactor for wastewater treatment

A novel photocatalytic reactor for wastewater treatment was designed and constructed. The main part of the reactor was an aluminum tube in which 12 stainless steel circular baffles and four quartz tube were placed inside of the reactor like shell and tube heat exchangers. Four UV–C lamps were housed within the space of the quartz tubes. Surface of the baffles was coated with TiO₂. A simple method was employed for TiO₂ immobilization, while the characterization of the supported photocatalyst was based on the results obtained through performing some common analytical methods such as X-ray diffraction (XRD), scanning electron microscope (SEM), and BET. Phenol was selected as a model pollutant. A solution of a known initial concentration (20, 60, and 100 ppmv) was introduced to the reactor. The reactor also has a recycle flow to make turbulent flow inside of the reactor. The selected recycle flow rate was 7?×?10^?5 m³.s^?1, while the flow rate of feed was 2.53?×?10^?7, 7.56?×?10^?7, and 1.26?×?10^?6 m³.s^?1, respectively. To evaluate performance of the reactor, response surface methodology was employed. A four-factor three-level Box–Behnken design was developed to evaluate the reactor performance for degradation of phenol. Effects of phenol inlet concentration (20–100 ppmv), pH (3–9), liquid flow rate (2.53?×?10^?7?1.26?×?10^?6 m³.s^?1), and TiO₂ loading (8.8–17.6 g.m^?2) were analyzed with this method. The adjusted R ² value (0.9936) was in close agreement with that of corresponding R ² value (0.9961). The maximum predicted degradation of phenol was 75.50 % at the optimum processing conditions (initial phenol concentration of 20 ppmv, pH?～?6.41, and flow rate of 2.53?×?10^?7 m³.s^?1 and catalyst loading of 17.6 g.m^?2). Experimental degradation of phenol determined at the optimum conditions was 73.7 %. XRD patterns and SEM images at the optimum conditions revealed that crystal size is approximately 25 nm and TiO₂ nanoparticles with visible agglomerates distribute densely and uniformly over the surface of stainless steel substrate. BET specific surface area of immobilized TiO₂ was 47.2 and 45.8 m² g^?1 before and after the experiments, respectively. Reduction in TOC content, after steady state condition, showed that maximum phenol decomposition occurred at neutral condition (pH?～?6). Figure

The schematic view of the experimental set-up     

Cross‐sectoral and participatory approaches to combating desertification: The Iranian experience

Anti‐desertification planning in Iran operates at the national level through the Five Year Development Plans, the National Plan to Combat Desertification — a long‐running scheme for which the Forest, Rangeland and Watershed Management Organisation (FRWO) is responsible — and the recently developed National Action Programme to Combat Desertification (the NAP). The Iranian NAP was formulated following the country's ratification of the United Nations Convention to Combat Desertification and drew heavily on the experience, expertise and collaboration of personnel in FRWO. Development and implementation of the NAP has had major policy impacts in Iran in the two main areas of generating cross‐sectoral cooperation between government instruments at the national planning level and by community participation in local projects to combat desertification. Documenting the evolution of cross‐sectoral and participatory approaches to desertification in Iran shows that the NAP provided impetus towards a transformation of previous procedures, a policy impact that is continuing to generate change.     

Assessments on emergy and greenhouse gas emissions of internal combustion engine automobiles and electric automobiles in the USA

Increasing energy consumption in the transportation sector results in challenging greenhouse gas (GHG) emissions and environmental problems. This paper involved integrated assessments on GHG emissions and emergy of the life cycle for the internal combustion engine (ICE) and electric automobiles in the USA over the entire assumed fifteen-year lifetime. The hotspots of GHG emissions as well as emergy indices for the major processes of automobile life cycle within the defined system boundaries have been investigated. The potential strategies for reducing GHG emissions and emergy in the life cycle of both ICE and electric automobiles were further proposed. Based on the current results, the total GHG emissions from the life cycle of ICE automobiles are 4.48E + 07 kg CO₂-e which is 320 times higher than that of the electric automobiles. The hotspot area of the GHG emissions from ICE and electric automobiles are operation phase and manufacturing process, respectively. Interesting results were observed that comparable total emergy of the ICE automobiles and electric automobiles have been calculated which were 1.54E + 17 and 2.20E + 17 sej, respectively. Analysis on emergy index evidenced a better environmental sustainability of electric automobiles than ICE automobiles over the life cycle due to its higher ESI. To the authors’ knowledge, it is the first time to integrate the analysis of GHG emissions together with emergy in industrial area of automobile engineering. It is expected that the integration of emergy and GHG emissions analysis may provide a comprehensive perspective on eco-industrial sustainability of automobile engineering.     

Benzene degradation in waste gas by photolysis and photolysis-ozonation: experiments and modeling

A photochemical model of benzene degradation compares well with experimental data obtained in the Lab. 62 reactions were needed to fully describe benzene degradation. A feasibility study shows that the photolysis of benzene is a cost-effective process. Experimental data and modeling results show that the degradation efficiency will increase when the combination of UV light and ozone is used. The degradation of benzene, a carcinogenic air pollutant, was studied in a gas-phase photochemical reactor with an amalgam lamp emitting ultraviolet light at 185 and 254 nm. Efficient benzene degradation (>70%) was possible for benzene mass flow rates of up to 1.5 mg·min⁻¹. Adding ozone allowed benzene mass flow rates of up to 5 mg·min⁻¹ to be treated with the same efficiency. In terms of energy consumption, ozone doubles the efficiency of the process. A comprehensive mechanistic simulation model was developed incorporating a chemical kinetics model (62 reactions involving 47 chemical species), a material balance model incorporating diffusion and flow, a flow velocity model, and a light field model. The model successfully predicted the efficiency of the reactor, generally within 20%, which indicates that the model is sound, and can be used for feasibility studies. The prediction of the reactor efficiency in the presence of ozone was less successful, with systematically overestimated efficiency. Condensation of reaction products in the reactor is thought to be the main cause of model inaccuracy. Both experimental data and model predictions show that there is a synergistic effect between ozonation and ultraviolet degradation.     

Mitigation of climate change impacts on maize productivity in northeast of Iran: a simulation study

Development and evaluation of mitigation strategies are fundamental to manage climate change risks. This study was built on (1) quantifying the response of maize (Zea mays L.) grain yield to potential impacts of climate change and (2) investigating the effectiveness of changing sowing date of maize as a mitigation option for Khorasan Province which is located in northeast of Iran. Two types of General Circulation Models (GCM: (United Kingdom Met Office Hadley Center :HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1) at four locations (Mashhad, Birjand, Bojnourd and Sabzevar) employed in this study. Long Ashton Research Station-Weather Generator (LARS-WG) was employed for generating the future climate. The Cropping System Model (CSM)-CERES-Maize was used for crop growth simulation under projected climate conditions. The results showed the simulated grain yields of maize gradually would decrease (from −1% to −39%) during future 100 years compared to baseline under different scenarios and two GCM at all study locations. The simulation results suggested that delayed sowing date from May to June at all study locations, except Sabzevar location is the most effective mitigation option for avoiding thermal stress at end of growth period. In addition, shifting in sowing date to March or April will be beneficial in terms of obtaining higher yields in Sabzevar. Grain yield did not show special trend from north to south of Khorasan Province in the future climate. In general, change of sowing date may be quite beneficial to mitigate climate change impacts on grain yield of maize in northeast of Iran.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

RANDAP: An integrated framework for reliability analysis of detailed action plans of combined automatic-operator emergency response taking into account control room operator errors

Automatic process control and control room operators supervision/intervention in an emergency are of critical importance in major hazard industries. These combined operator and automatic actions are defined in Detailed Action Plans (DAP). A framework has been proposed for analyzing the reliability, and hence the likelihood of success, of DAPs. The Reliability Block Diagram technique is utilized for modeling the reliability of integrated automatic-operator emergency actions. The focus is on incorporating operator's operational and cognitive errors in the process/equipment reliability analysis. For this purpose, the human reliability analysis method SPAR-H is utilized. The proposed framework was used for analyzing emergency response DAPs of a real process plant in order to check and improve its applicability. It is argued that the presented framework facilitates the DAP assessment process by performing Task Analysis, modeling the detailed tasks as well as reliability analysis, thereby uncovering the shortcomings of the designed DAPs. Besides, it provides a very effective, transparent tool with insight into improvement areas and directions for improving the reliability of DAPs.