Predictors of poor outcomes among patients of acute methanol intoxication with particular reference to Sequential Organ Failure Assessment (SOFA) score

Environmental Science and Pollution Research - Methanol intoxication is a global problem with serious morbidities and mortalities. Apart from the lifelong disabilities experienced by methanol...     

Correction to: Effect of organic and inorganic phosphorus fertilizers on phosphorus availability and its leaching over incubation time

Environmental Science and Pollution Research - The correct presentation of the equations in Table 6 footnote is presented in this paper     

Quantification of human adenovirus in irrigation water-soil-crop continuum: are consumers of wastewater-irrigated vegetables at risk?

Environmental Science and Pollution Research - Because of health concerns regarding the presence of enteric viruses in wastewater effluents, this study was designed to investigate the occurrence of...     

Development of GP and GEP models to estimate an environmental issue induced by blasting operation

Air overpressure (AOp) is one of the most adverse effects induced by blasting in the surface mines and civil projects. So, proper evaluation and estimation of the AOp is important for minimizing the environmental problems resulting from blasting. The main aim of this study is to estimate AOp produced by blasting operation in Miduk copper mine, Iran, developing two artificial intelligence models, i.e., genetic programming (GP) and gene expression programming (GEP). Then, the accuracy of the GP and GEP models has been compared to multiple linear regression (MLR) and three empirical models. For this purpose, 92 blasting events were investigated, and subsequently, the AOp values were carefully measured. Moreover, in each operation, the values of maximum charge per delay and distance from blast points, as two effective parameters on the AOp, were measured. After predicting by the predictive models, their performance prediction was checked in terms of variance account for (VAF), coefficient of determination (CoD), and root mean square error (RMSE). Finally, it was found that the GEP with VAF of 94.12%, CoD of 0.941, and RMSE of 0.06 is a more precise model than other predictive models for the AOp prediction in the Miduk copper mine, and it can be introduced as a new powerful tool for estimating the AOp resulting from blasting.     

Engineered silica nanoparticles alleviate the detrimental effects of Na+ stress on germination and growth of common bean (Phaseolus vulgaris)

Environmental Science and Pollution Research - During the past 10 years, exploiting engineered nanoparticles in agricultural sector has been rapidly increased. Nanoparticles are used to...     

Thermo-chemical pretreatment of the organic fraction of municipal solid waste for improved anaerobic digestion

Journal of Material Cycles and Waste Management - The hydrolysis of organic waste in anaerobic digestion is slow and time-consuming. Pretreatment of the waste can potentially improve hydrolysis and...     

Livelihood change and livelihood sustainability in the uplands of Lembang subwatershed, West Sumatra, Indonesia, in a changing natural resource management context

This paper analyzes livelihood change and livelihood sustainability of households in the upland part of the Lembang subwatershed, West Sumatra, in response to changes in the natural resource management context during the last decade. Using the sustainable livelihood framework (SLF), we measured livelihood changes at two separate points in time, 1996 and 2006, and assessed their environmental, economic, social, and institutional sustainability. We found that people with a low income had less access to capital assets than people from middle- and high-income groups. Our analysis revealed, however, that access to capital assets increased over time, and that poor households experienced economic improvement, indicating an overall increase in economic sustainability. Environmental sustainability, however, is threatened by intensive agricultural practices such as high agrochemical input and intensive soil tillage on steep slopes, leading to pollution and soil erosion. Social sustainability is also a matter of concern: while social exclusion has been reduced, income inequity has increased. Institutional sustainability is likely to remain uncertain, as local institutions for natural resource management are still weak, despite the fact that decentralization has been implemented during the last 8 years. External facilitation is needed to improve the livelihood of upland people while, at the same time, enhancing the sustainability of watershed management. Strengthening local institutions, conserving natural resources, and promoting environmentally sound agricultural practices are the three most important policies to be promoted within the watershed.     

Predicting Particulate Matter (PM2.5) Concentrations in the Air of Shahr‐e Ray City,Iran, by Using an Artificial Neural Network

Particulate matter (PM), along with other air pollutants, pose serious hazards to human health. The Artificial Neural Network (ANN) is a branch of artificial intelligence that has an ability to make accurate predictions. In this article, the authors describe such methods and how historical data on air quality, moisture, wind velocity, and temperature in Shahr‐e Ray City, located at the southern tip of Tehran, was used to train an ANN to provide accurate predictions of PM concentrations. The availability of such predictions can offer significant assistance to those who are working to reduce air pollution.     

Application of ultrasound irradiation in landfill leachate treatment

Environmental Science and Pollution Research - Landfilling is known to be the most widely used method in municipal solid waste management in many countries. Landfill leachate containing different...