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.     

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).     

Emergy-based fuzzy optimization approach for water reuse in an eco-industrial park

The establishment of an eco-industrial park (EIP) provides opportunity for individual plants to cooperate with each other in order to utilize resources efficiently and thus reduce waste. The goal of an EIP is to “close the loop” through recycling and reuse of material and energy streams. Studies show with current freshwater consumption trends there would be water stress aggravated by global warming in the near future. This paper presents a model to design an EIP water reuse network that considers overall system sustainability as measured with emergy, as well as cost saving desired by individual plants. Case studies from literature are then solved to illustrate the advantage of this method in decision making. The illustrative examples show how the model achieves a compromise among the potentially conflicting fuzzy goals of the various EIP stakeholders.     

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.     

Emission factor estimation for oil and gas facilities

Fugitive emission rate quantification in an oil and gas facility is an important step of risk management. There are several studies conducted by the United States Environmental Protection Agency (USEPA) and American Petroleum Institute (API) proposing methods of estimating emission rates and factors. Four major approaches of estimating these emissions, in the order of their accuracy, are: average emission factor approach, screening ranges emission factor approach, USEPA correlation equation approach, and unit-specific correlation equation approach. The focus of this study is to optimize the USEPA correlation equations to estimate the emission rate of different units in an oil and gas facility. In the developed methodology, the data available from USEPA (1995) is used to develop new sets of equations. A comparison between USEPA correlation equations and the proposed equations is performed to define the optimum sets of equations. It is observed that for pumps, flanges, open-ended lines, and others, the proposed developed equations provide a better estimation of emission rate, whereas for other sources, USEPA equations supply the better estimate of emission rate.     

The efficiency of Amberlite XAD-4 resin loaded with 1-(2-pyridylazo)-2-naphthol in preconcentration and separation of some toxic metal ions by flame atomic absorption spectrometry

A selective method has been developed for the determination of trace amount of metal ions after preconcentration on 1-(2-pyridylazo)-2-naphthol loaded Amberlite XAD-4 resin. The chelating resin was characterized on the basis of infra red spectra, thermal and chemical stability, and hydrogen ion capacity. High preconcentration factor of 160?C400 up to a low preconcentration limit of 10 ??g L^???1 has been achieved for almost all the metals. The chelating resin was highly selective even in the presence of large concentrations of alkali and alkaline earth metals and various matrix components. Chromatographic separation of metal ions in binary mixtures has been accomplished. The analytical utility of the resin for metal ions was explored by analyzing natural water and standard reference materials.     

Organochlorine residual concentrations in cattle egret from the Punjab Province, Pakistan

In this study, residual concentration of organochlorine pesticides (OCPs) in the sediments, prey, and eggs of Bubulcus ibis were measured from three breeding heronries from the Punjab province of Pakistan. Pattern of contamination in eggs followed the order: DDTs > HCHs > heptachlor > aldrin. Overall, pesticide residual concentrations were greater in eggs of cattle egrets collected from heronry on the River Ravi. Among HCHs, ??-HCH was more prevalent in eggs, whereas DDTs followed the order: DDD > DDE > p,p ^??-DDT > o,p ^??-DDT. Eggshell thinning was detected which showed negative relationship with residual concentration of DDE. In prey samples, residual concentration of POPs followed the order: DDTs > HCHs > dicofol > heptachlor; however, contamination pattern in sediments followed a slightly different order: DDTs > heptachlor > dicofol > HCHs > dieldrin > aldrin. Concentration of ??-HCH was more prevalent in sediments and comparatively greater concentrations of POPs were measured in sediments collected from the River Ravi. Dicofol was found for the very first time in the biological samples from Pakistan, and its concentration was measured as relatively high in eggs from heronry from the River Chenab. Residual concentrations measured in eggs were below the levels that could affect egret populations. Biomagnification of the total OCPs through the food chain was evident in three breeding heronries. The concentration of DDE measured in eggs of the cattle egret suggests the need for monitoring this contaminant in other bird species at different trophic levels.     

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

Corpus Christi Bay (TX, USA) is a shallow wind-driven bay and thereby, can be characterized as a highly pulsed system. It cycles through various episodic events such as hypoxia, water column stratification, sediment resuspension, flooding, etc. Understanding of the processes that control these events requires an efficient observation system that can measure various hydrodynamic and water quality parameters at the multitude of spatial and temporal scales of interest. As part of our effort to implement an efficient observation system for Corpus Christi Bay, a mobile monitoring system was developed that can acquire and visualize data measured by various submersible sensors on an undulating tow-body deployed behind a research vessel. Along with this system, we have installed a downward-looking Acoustic Doppler Current Profiler to measure the vertical profile of water currents. Real-time display of each measured parameter intensity (measured value relative to a pre-set peak value) guides in selecting the transect route to capture the event of interest. In addition, large synchronized datasets measured by this system provide an opportunity to understand the processes that control various episodic events in the bay. To illustrate the capability of this system, datasets from two research cruises are presented in this paper that help to clarify processes inducing an inverse estuary condition at the mouth of the ship channel and hypoxia at the bottom of the bay. These measured datasets can also be used to drive numerical models to understand various environmental phenomena that control the water quality of the bay.     

Selection and performance estimation of Green Lean Six Sigma Projects: a hybrid approach of technology readiness level,data envelopment analysis,and ANFIS

Environmental Science and Pollution Research - Nowadays budget and schedule constraints have forced organizations to select six sigma projects based on pre-defined success criteria. Also,...