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.     

Pasture diversification to combat climate change impacts on grazing dairy production

Among livestock systems, grazing is likely to be most impacted by climate change because of its dependency to feed quality and availability. In order to reduce the impact of climate change on grazing livestock systems, adaptation measures should be implemented. The goal of this study is to identify the best pasture composition for a representative grazing dairy farm in Michigan in order to reduce the impacts of climate change on production. In order to achieve the goal of this study, three objectives were sought: (1) identify the best pasture composition, (2) assess economic and resource use impacts of pasture compositions under future climate scenarios, and (3) evaluate the resiliency of pasture compositions. A representative farm was developed based on a livestock practices survey and incorporated into the Integrated Farm System Model (IFSM). For the pasture compositions, four cool-season grass species and two legumes were evaluated under both current and future climate scenarios. The effectiveness of adaptation measures based on economic and resource use criteria was evaluated. Overall, the pasture composition with 50% perennial ryegrass (Lolium multiflorum) and 50% red clover (Trifolium pratense) was identified as the best. In addition, the increase in precipitation and temperature of the most intensive climate scenario could significantly improve farm net return per cow (Bos taurus) and whole farm profit while no significant impact was observed on resource use criteria. Finally, the overall sensitivity assessment showed that the most resilient pasture composition under future climate scenarios was ryegrass with red clover and the least resilient was orchardgrass (Dactylis glomerata) with white clover (Trifolium repens).     

Comparison of different static methods for assessment of AMD generation potential in mining waste dumps in the Muteh Gold Mines,Iran

Acid mine drainage (AMD) gives rise to several problems in sulfide-bearing mineral deposits whether in an ore body or in the mining wastes and tailings. Hence, several methods and parameters have been proposed to evaluate the acid-producing and acid-neutralizing potential of a material. This research compares common static methods for evaluation of acid-production potential of mining wastes in the Muteh gold mines by using 62 samples taken from six waste dumps around Senjedeh and Chah-Khatoun mines. According to a detailed mineralogical study, the waste materials are composed of mica-schist and quartz veins with a high amount of pyrite and are supposed to be susceptible to acid production, and upon a rainfall, they release acid drainage. All parameters introduced in different methods were calculated and compared in this research in order to predict the acid-generating and neutralization potential, including APP, NNP, MPA, NPR, and NAGpH. Based on the analytical results and calculation of different parameters, all methods are in a general consensus that DWS-02 and DWS-03 waste dumps are acid-forming which is clearly attributed to high content of pyrite in samples. DWS-04 is considered as non-acid forming in all methods except method 8 which is uncertain about its acid-forming potential and method 7 which considers a low potential for it. DWC-01 is acid-forming based on all methods except 8, 9, 10, and 11 which are also uncertain about its potential. The methods used are not reached to a compromise on DWS-01 and DWC-02 waste dumps. It is supposed that method 7 gives the conservationist results in all cases. Method 8 is unable to decide on some cases. It is recommended to use and rely on results provided by methods 1, 2, 3, and 12 for taking decisions for further studies. Therefore, according to the static tests used, the aforementioned criteria in selected methods can be used with much confidence as a rule of thumb estimation.     

Household waste behaviours among a community sample in Iran: An application of the theory of planned behaviour

Understanding the factors influencing recycling behaviour can lead to better and more effective recycling programs in a community. The goal of this study was to examine factors associated with household waste behaviours in the context of the theory of planned behaviour (TPB) among a community sample of Iranians that included data collection at time 1 and at follow-up one year later at time 2. Study participants were sampled from households under the coverage of eight urban health centers in the city of Qazvin. Of 2000 invited households, 1782 agreed to participate in the study. A self-reported questionnaire was used for assessing socio-demographic factors and the TPB constructs (i.e. attitude, subjective norms, perceived behavioural control, and intention). Furthermore, questions regarding moral obligation, self-identity, action planning, and past recycling behaviour were asked, creating an extended TPB. At time 2, participants were asked to complete a follow-up questionnaire on self-reported recycling behaviours. All TPB constructs had positive and significant correlations with each other. Recycling behaviour at time 1 (past behaviour) significantly related to household waste behaviour at time 2. The extended TPB explained 47% of the variance in household waste behaviour at time 2. Attitude, perceived behavioural control, intention, moral obligation, self-identity, action planning, and past recycling behaviour were significant predictors of household waste behaviour at time 2 in all models. The fact that the expanded TPB constructs significantly predicted household waste behaviours holds great promise for developing effective public campaigns and behaviour-changing interventions in a region where overall rates of household waste reduction behaviours are low. Our results indicate that educational materials which target moral obligation and action planning may be particularly effective.     

The level and distribution of selected organochlorine pesticides in sediments from River Chenab,Pakistan

Organochlorine pesticides (OCPs), viz. β-hexachlorocyclohexane (β-HCH), γ-HCH, aldrin, dieldrin, endrin, heptachlor, endosulfan-I, endosulfan-II, heptachlor endoepoxide, heptachlor exoepoxide, mirex, dicofol, o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT), dichlorodiphenyldichloroethane (DDD), and dichlorodiphenyltrichloroethylene (DDE) and 12 other physicochemical parameters were measured in surface sediments from River Chenab during two sampling seasons (summer and winter, 2007) to evaluate spatial and temporal trends of sediment pollution. Hierarchical agglomerative cluster analysis identified three groups of sites based on spatial similarities in physicochemical parameters and OCP residual concentrations. Spatial discriminant function analysis (DFA) segregated 14 parameters, viz. dicofol, endosulfan-I, heptachlor endoepoxide, dieldrin, DDD, DDE, endosulfan-II, o,p′-DDT, p,p′-DDT, pH, electrical conductivity (EC), Cl⁻¹, total P (%), and silt, which explained 96% of total variance between spatial groups. γ-HCH was the most frequently detected (63%) pesticide, followed by DDD (56%). The ratio of DDTs to their metabolites indicated current input and anaerobic biodegradation. Temporal DFA highlighted aldrin, heptachlor endoepoxide, Cl⁻¹, total P, and EC as important variables which caused variations between summer and winter. DDTs were relatively more prevalent as compared to other OCPs in the sediments samples during both seasons. DDT metabolites were detected at greater frequencies and concentrations in winter, whereas DDT isomers were more prevalent in summer sediment samples. Factor analysis identified agricultural and industrial activities as major sources of sediment OCP contamination. Concentrations of γ-HCH, heptachlor endoepoxide, dieldrin, and DDTs (isomers and metabolites) in all sediment samples were well above interim sediment quality guidelines (ISQGs) and probable effect limits (PEL) given by Canadian Sediment Quality Guidelines (CSQGs).     

Design based estimation for ranked set sampling in finite populations

In this paper, we consider design-based estimation using ranked set sampling (RSS) in finite populations. We first derive the first and second-order inclusion probabilities for an RSS design and present two Horvitz–Thompson type estimators using these inclusion probabilities. We also develop an alternate Hansen–Hurwitz type estimator and investigate its properties. In particular, we show that this alternate estimator always outperforms the usual Hansen–Hurwitz type estimator in the simple random sampling with replacement design with comparable sample size. We also develop formulae for ratio estimator for all three developed estimators. The theoretical results are augmented by numerical and simulation studies as well as a case study using a well known data set. These show that RSS design can yield a substantial improvement in efficiency over the usual simple random sampling design in finite populations.     

Determination of nickel, copper, zinc and lead in human scalp hair in Syrian occupationally exposed workers by total reflection X-ray fluorescence

In this study, an attempt has been made to study methane flux and quantification of heavy metals from Municipal Solid Waste (MSW) landfill areas of selected cities in India. During the period of study, the average value of methane flux was estimated from these landfill areas varied from 146–454 mg/m2/h. Methane emission from landfill is of serious environmental global concern as it accounts for approximately 15 percentages of current Greenhouse gas emissions. It has been estimated that methane emission, from landfill areas in the world, in next two decades would be same as that what is emitted from paddy fields presently. Besides, the estimation of methane flux, quantification of some heavy metals was conducted to analyse the suitability of using MSW as compost. The average values for metals were observed to be both within the range of USEPA and Indian standards for MSW disposal in landfill areas and to be used as compost respectively.     

Evaluation of Pb, Cu, Zn, Cd, Ni and Fe levels in Rosmarinus officinalis labaiatae (Rosemary) medicinal plant and soils in selected zones in Jordan

The concentration of heavy metals including Pb, Cu, Zn, Cd, Ni and Fe in different parts of Rosmarinus officinalis medicinal plant grown in Jordan were evaluated. Medicinal plant samples and soil samples were collected from three different zones in Jordan (Irbid, Al-Mafraq and Ma’an). Samples were analyzed by atomic absorption spectrometry (AAS) after chemical treatments using acid digestion procedures. Heavy metal levels in washed and unwashed in each part of R. officinalis were analyzed and compared statistically. Results show that concentrations of investigated heavy metals were varied from plant part to another part of R. officinalis. For example, Pb, Zn, Cu and Cd in most parts of R. officinalis in the three zones were concentrated in the following order: flowers, leaves, stems, whereas Pb, Ni and Fe were concentrated in order as follows: leaves, flowers and stems. Heavy metal concentrations in soil samples was evaluated and correlated with their levels in R. officinalis. Two standard reference materials of plant (SRM 1790a; spinach leaves and CRM 281; rye grass) and one standard reference materials of soil (GBW 07406) were examined to validate the method used. Results show that high recoveries were obtained.     

River water quality assessment using environmentric techniques: case study of Jakara River Basin

Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH₄). Partial correlation analysis (r _p) results showed that there is a strong relationship between salinity and turbidity (r _p?=?0.930, p?=?0.001) and BOD₅ and COD (r _p?=?0.839, p?=?0.001) controlling for the linear effects of conductivity and NH₄, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD₅, COD, SS, NH₄, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin.