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.     

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...     

Production of biofuels from microalgae

The production of biofuels from microalgae, especially biodiesel, has become a topic of great interest in recent years. However, many of the published papers do not consider the question of scale up and the feasibility of the various processes to be operated at the very large scale required if algal biofuels are to make a meaningful contribution to renewable fuels. All the steps in the process must also be very low cost. This paper discusses the unit processes required for algal biofuels production (i.e., growing the algae, harvesting, dewatering, extraction and conversion to biofuel) and their scalability. In many cases, especially in the lipid extraction step, little is known as yet as to the scalability and economic feasibility of the various processes proposed. We also highlight the key engineering and biological issues which must be resolved for the production of biofuels from microalgae to become an economic reality.     

Artificial intelligence,fetal echocardiography,and congenital heart disease

There has been a recent explosion in the use of artificial intelligence (AI), which is now part of our everyday lives. Uptake in medicine has been more limited, although in several fields there have been encouraging results showing excellent performance when AI is used to assist in a well-defined medical task. Most of this work has been performed using retrospective data, and there have been few clinical trials published using prospective data. This review focuses on the potential uses of AI in the field of fetal cardiology. Ultrasound of the fetal heart is highly specific and sensitive in experienced hands, but despite this there is significant room for improvement in the rates of prenatal diagnosis of congenital heart disease in most countries. AI may be one way of improving this. Other potential applications in fetal cardiology include the provision of more accurate prognoses for individuals, and automatic quantification of various metrics including cardiac function. However, there are also ethical and governance concerns. These will need to be overcome before AI can be widely accepted in mainstream use. It is likely that a familiarity of the uses, and pitfalls, of AI will soon be mandatory for many healthcare professionals working in fetal cardiology.