Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.     

Distribution of heavy metals in surface sediments from the South China Sea ecosystem, Malaysia

The concentrations of arsenic, cadmium, chromium, copper, mercury, nickel, lead and zinc in surface sediments collected from the east coast of peninsular Malaysia, along the South China Sea, were measured by two methods instrumental neutron activation analysis and inductively coupled plasma mass spectroscopy. The obtained results were use to determine the areal distribution of the metals of in the east coast of peninsular Malaysia and potential sources of these metals to this environment. The geochemical data propose that most of the metals found in the east coast of peninsular Malaysia constitute a redistribution of territorial materials within the ecosystem. Then, the metal concentrations can be considered to be present at natural background levels in surface sediments.     

Parametric study along with selection of optimal solutions in dry wire cut machining of cemented tungsten carbide (WC-Co)

This work deals with parametric study of dry wire EDM (WEDM) process of cemented tungsten carbide. Experiments have been conducted using air as dielectric medium to investigate effects of pulse on time, pulse off time, gap set voltage, discharge current and wire tension on cutting velocity (CV) surface roughness (SR) and oversize (OS). Firstly, a series of exploratory experiments were carried out to identify appropriate gas and its pressure. Afterward, preliminary experiments were conducted to investigate effects of process parameters on dry WEDM characteristics and find appropriate ranges for each factor. Then a central composite rotatable method was employed to design experiments based on response surface methodology (RSM). Empirical models were developed to create relationships between process factors and responses by considering to analysis of variances (ANOVA). To increase the predictability of the process, intelligent models have been developed based on back-propagation neural network (BPNN) and accuracy of these models was compared with mathematical models based on root mean square error (RMSE) and prediction error percent (PEP). In order to select optimal solutions in the cases of single-objective and multi-objectives optimization problems, optimization includes two main approaches. First approach was based on mathematical model and desirability function. Also second approach was designed based on neural network and particle swarm optimization. These approaches were applied in both cases of single-objective and multi-objectives optimization problems and their results were compared with together. Results indicated that selection of air at inlet pressure of 1.5 bar is really appropriate for conducting experiments of next stages. Also, the BPNN creates more accurate prediction rather than mathematical model. Moreover, the BPNN-PSO approach was more efficient in optimization of process rather than mathematical model-desirability function in respect with validation tests.     

Global trends and status in waste foundry sand management research during the years 1971-2020: a systematic analysis

Environmental Science and Pollution Research - Waste foundry sand (WFS) is the by-product of the foundry industry, which is produced about 0.6 tons per 1 ton of foundry industry production. While...     

The association of prenatal exposure to benzophenones with gestational age and offspring size at birth

Environmental Science and Pollution Research - In recent decades, emerging environmental pollutants such as endocrine-disrupting chemicals (EDCs) have become a particular concern. This study...     

Investigation of land use changes in rural areas using MCDM and CA-Markov chain and their effects on water quality and soil fertility in south of Iran

The purpose of the study is to predict drought changes in Dariun, Fars Province, and their impact on water and soil quality. To prepare drought, water, and soil quality zoning maps, Landsat satellite images and the kriging method were used. The fuzzy maps and weights for each parameter were then determined using fuzzy and analytic hierarchy process (AHP) methods. Additionally, cellular automata (CA)-Markov chains were used in order to predict the impact of drought changes on water and soil quality. Using the fuzzy-AHP method, water quality and soil fertility in 2020 were lower compared to previous years, mainly because of land use changes that increased pollution. Based on results of the Markov and CA-Markov chains, approximately 31% of the region will have very poor levels of soil fertility and water quality in 2050. Further, based on remote sensing indicators, it is determined that about 25% of the region will be at high risk of drought in 2050. Thus, if adequate management of the region is not done, the possibility of living in these areas may diminish in the coming years due to drought and deteriorated water and soil quality.

     

Spatial�Ctemporal assessment and redesign of groundwater quality monitoring network: a case study

Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation?Cdistance (T?CD) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy equivalence relations. As a result, the sampling (temporal) frequency determination method also recommends the future sampling frequencies for each location based on certain criteria such as direction, magnitude, correlation with neighboring stations, and uncertainty of the concentration trend derived from representative historical concentration data. The proposed methodology is applied to groundwater resources in the Tehran?CKaradj aquifer, Tehran, Iran.     

Report: future industrial solid waste management in pars Special Economic Energy Zone (PSEEZ), Iran.

The Pars Special Economic Energy Zone (PSEEZ) is located in the south of Iran, on the northern coastline of the Persian Gulf. This area was established in 1998 for the utilization of south Pars field oil and gas resources. This field is one of the largest gas resources in the world and contains about 6% of the total fossil fuels known. Petrochemical industries, gas refineries and downstream industries are being constructed in this area. At present there are three gas refineries in operation and five more gas refineries are under construction. In this study, different types of solid waste including municipal solid waste (MSW) and industrial wastes were investigated separately. The aim of the study was to focus on the management of the industrial wastes in order to minimize the environmental impact. In the first stage, the types and amounts of industrial waste in PSEEZ were evaluated by an inventory. The main types of industrial waste are oil products (fuel oil, light oil, lubricating oil), spent catalysts, adsorbents, resins, coke, wax and packaging materials. The waste management of PSEEZ is quite complex because of the different types of industry and the diversity of industrial residues. In some cases recycling/reuse of waste is the best option, but treatment and disposal are also necessary tools. Recently a design has been prepared for a disposal site in PSEEZ for the industrial waste that cannot be reused or recycled. The total surface area of this disposal site where the industrial waste should be tipped for the next 20 years was estimated to be about 42 000 m2.