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.     

Application of analytical hierarchy process (AHP) to assess options of energy recovery from municipal solid waste: a case study in Tehran,Iran

Journal of Material Cycles and Waste Management - In the current study, a model was established based on AHP method for assessment of different alternatives for energy recovery from the waste in...     

One-pot hard template synthesis of mesoporous spinel nanoparticles as efficient catalysts for low temperature CO oxidation

Co-Fe, Cu-Cr, and Co-Mn mixed oxide catalysts were prepared using a one-pot hard template synthesis method, and their catalytic performance was investigated before and after the rearrangement of the template. To evaluate the structural properties of the catalysts, various analyses were employed, including the BET, XRD, H₂-TPR, FE-SEM, EDX, and X-ray digital mapping of the elements. The results indicated that the rearrangement of the catalyst structure had a profound effect on the structural and catalytic properties, so that in all three synthesized catalysts, the specific surface and the reducibility increased significantly, and the crystalline structure and morphology of the catalysts changed remarkably. The specific surface area of the CoFe, CuCr, and CoMn catalysts increased from 3.5, 1.1, and 72.9 m²/g to 151.3, 52.8, and 108.0 m²/g, respectively. These structural changes significantly increased the catalytic performance. The results indicated that the 100% conversion temperature of the CoMn catalyst as the optimal sample after rearrangement was reduced from 250 to 125 °C. Also, the stability of the CoMn catalyst in dry and wet conditions was investigated and the results indicated that the presence of water vapor reduced the activity and stability of the catalyst. The activation energy was also calculated on Co-Mn catalyst (59.5 kJ/mol) and the results confirmed that the most probable mechanism for this reaction was the MVK mechanism.

     

Removal of Reactive Blue 19 dye from synthetic wastewater using UV/H2O2 and UV/Cl advanced oxidation processes

The textile and dyeing industries are among the largest water-consuming and polluting industries in the world. The most important feature of the textile dyeing industry wastewater is its color, due to the use of colored materials. Most of these dye compounds are resistant to conventional purification methods and their biodegradation is very low through secondary purification processes, resulting in incomplete removal. Therefore, selecting the optimal method to remove these color compounds is essential. In this study, we studied the removal of an organic dye contaminant (Reactive Blue dye 19 [RB19]) using advanced oxidation processes (AOPs). For this purpose, ultraviolet (UV) mercury lamps with a wavelength of 254 nm and a voltage of W16 inside a reactor were used as an energy source. The experiments were performed in a collimated beam reactor inside a dark chamber. Two oxidizers, sodium hypochlorite (NaOCl) and hydrogen peroxide (H₂O₂), were used to remove RB19 from the artificial sewage stream. Removal of RB19 with a concentration of 20 mg/L with variable pH (5, 7, and 9), oxidant concentrations (5, 10, and 20 mg/L), and time (5, 10, 15, and 30 min) were investigated during the processes of photolysis, chemical oxidation (by H₂O₂ and NaOCl), and UV/NaOCl and UV/H₂O₂ AOPs. The photolysis process did not remove the RB19. The highest removal efficiencies of RB19 by chemical oxidation processes with NaOCl and H₂O₂, UV/NaOCl, and UV/H₂O₂ at optimal conditions (pH = 5, [oxidant] = 20 mg/L, RB19 = 20 mg/L, and radiation intensity of 1005 mJ/cm²) were 64.49%, 0.88%, 99.7%, and 13.31%, respectively. These results indicate that the hydroxyl radical was produced, under optimum conditions, more in the acidic medium; thus, the RB19 removal efficiency was higher in the acidic medium. The combination of UV rays with oxidants resulted in the production of more hydroxyl radicals and increased removal efficiency.     

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.     

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.