Modelling changes in forest soil chemistry at 16 Swedish coniferous forest sites following deposition reduction

The dynamic forest ecosystem model ForSAFE was applied at 16 coniferous forest sites in Sweden to investigate past and future changes in soil chemistry following changes in atmospheric deposition. The simulation shows a considerable historical soil acidification. Acidification in the southwest, where deposition has been greatest, was more expressed in the deepest soil layers, while it was more evenly distributed through the soil profile in central Sweden, and was greater in the upper soil layers in the north. The simulation also shows that a slight recovery took place after the reduction in emissions, but was counteracted by the effect of harvesting. The simulation predicts an increase in the number of acidified sites in the future. The results also suggest that future acidification will be mainly due to the enhanced tree growth resulting from the chronic high deposition of nitrogen and the removal of soil base cations through harvesting.     

Production of valued materials from squid viscera by subcritical water hydrolysis

Subcritical water hydrolysis was carried out to produce valued materials from squid viscera, the waste product of fish processing industries. The reaction temperatures for hydrolysis of rawand deoiled squid viscera were maintained from 180 to 280 degrees C for5 min. The ratio of material to water forhydrolysis was 1:50. Most of the proteins from deoiled squid viscera were recovered at high temperature. The protein yield in raw squid viscera hydrolyzate decreased with the rise of temperature. The reducing sugar yield was higher at high temperature in subcritical water hydrolysis of both raw and deoiled squid viscera. The highest yield of amino acids in raw and deoiled squid viscera hydrolyzates were 233.25 +/- 3.25 and 533.78 +/- 4.13 mg g(-1) at 180 and 280 degrees C, respectively. Most amino acids attained highest yield at the reaction temperature range of 180-220 degrees C and 260-280 degrees C for raw and deoiled samples, respectively. The recovery of amino acids from deoiled squid viscera was about 1.5 times higher than that of raw squid viscera.     

Effectiveness in the use of natural gas for the reduction of atmospheric emissions: case study--industrial sector in the metropolitan region of Santiago,Chile

The purpose of this investigation was to quantify the potential of natural gas to reduce emissions from stationary combustion sources by analyzing the case study of the metropolitan region of Santiago, Chile. For such purposes, referential base scenarios have been defined that represent with and without natural gas settings. The method to be applied is an emission estimate based on emission factors. The results for this case study reveal that stationary combustion sources that replaced their fuel reduced particulate matter (PM) emissions by 61%, sulfur oxides (SOx) by 91%, nitrogen oxides (NOx) by 40%, and volatile organic compounds (VOC) by 10%. Carbon monoxide (CO) emissions were reduced by 1%. As a result of this emission reduction, in addition to reductions caused by other factors, such as a shift to cleaner fuels other than natural gas, technological improvements, and sources which are not operative, emission reduction goals set forth by the environmental authorities were broadly exceeded.     

ANFIS-based modelling for coagulant dosage in drinking water treatment plant: a case study

Coagulation is the most important stage in drinking water treatment processes for the maintenance of acceptable treated water quality and economic plant operation, which involves many complex physical and chemical phenomena. Moreover, coagulant dosing rate is non-linearly correlated to raw water characteristics such as turbidity, conductivity, pH, temperature, etc. As such, coagulation reaction is hard or even impossible to control satisfactorily by conventional methods. Traditionally, jar tests are used to determine the optimum coagulant dosage. However, this is expensive and time-consuming and does not enable responses to changes in raw water quality in real time. Modelling can be used to overcome these limitations. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modelling of coagulant dosage in drinking water treatment plant of Boudouaou, Algeria. Six on-line variables of raw water quality including turbidity, conductivity, temperature, dissolved oxygen, ultraviolet absorbance, and the pH of water, and alum dosage were used to build the coagulant dosage model. Two ANFIS-based Neuro-fuzzy systems are presented. The two Neuro-fuzzy systems are: (1) grid partition-based fuzzy inference system (FIS), named ANFIS-GRID, and (2) subtractive clustering based (FIS), named ANFIS-SUB. The low root mean square error and high correlation coefficient values were obtained with ANFIS-SUB method of a first-order Sugeno type inference. This study demonstrates that ANFIS-SUB outperforms ANFIS-GRID due to its simplicity in parameter selection and its fitness in the target problem.     

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy,USA

Environmental Science and Pollution Research - This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In...     

Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study

This article presents a comparison of two adaptive neuro-fuzzy inference systems (ANFIS)-based neuro-fuzzy models applied for modeling dissolved oxygen (DO) concentration. The two models are developed using experimental data collected from the bottom (USGS station no: 420615121533601) and top (USGS station no: 420615121533600) stations at Klamath River at site KRS12a nr Rock Quarry, Oregon, USA. The input variables used for the ANFIS models are water pH, temperature, specific conductance, and sensor depth. Two ANFIS-based neuro-fuzzy systems are presented. The two neuro-fuzzy systems are: (1) grid partition-based fuzzy inference system, named ANFIS_GRID, and (2) subtractive-clustering-based fuzzy inference system, named ANFIS_SUB. In both models, 60 % of the data set was randomly assigned to the training set, 20 % to the validation set, and 20 % to the test set. The ANFIS results are compared with multiple linear regression models. The system proposed in this paper shows a novelty approach with regard to the usage of ANFIS models for DO concentration modeling.     

A risk-based approach to design warning system for processing facilities

Alarm flooding is a major safety issue in today's processing facilities. Important recommendations are available for alarm management; however, they are often violated in practice, especially in the alarm systems implemented through the distributed control system. An effective process alarm prioritization and management system is desired for a safe and effective operation of a process facility.In present work, authors address two main issues related to an alarm system – the reliability and the prioritization of the alarms. The main objective is to deal with the alarm-flooding problem in process facilities. A multi alert voting system based on sensor redundancy approach is proposed to improve the reliability. A quantitative risk-based alarm management approach is proposed to address the flooding issue. In the risk-based approach, an integrated model consisting of the probability (P), the impact (I) of the potential hazards, and the process safety time is proposed to prioritize these raised alarms.The proposed approach is further explained by a reactor system with pressure and temperature variable monitoring and controls, where the hazards associated with two alerts caused by over high pressure and over high temperature are analyzed and integrated with response time for alarms generation and prioritization.     

坦桑尼亚水质和污染研究回顾

坦桑尼亚的海岸带(图1)有多种生物栖息地,其中包括珊瑚礁、红树林、海草床、沙坝、湿地和沙滩.除了承担海岸带所有功能中的基本连接作用外,这些海岸带栖息地还提供了生物和非生物资源.     

Assessing the risk of N leaching from forest soils across a steep N deposition gradient in Sweden

Nitrogen leaching from boreal and temporal forests, where normally most of the nitrogen is retained, has the potential to increase acidification of soil and water and eutrophication of the Baltic Sea. In parts of Sweden, where the nitrogen deposition has been intermediate to high during recent decades, there are indications that the soils are close to nitrogen saturation. In this study, four different approaches were used to assess the risk of nitrogen leaching from forest soils in different parts of Sweden. Nitrate concentrations in soil water and C:N ratios in the humus layer where interpreted, together with model results from mass balance calculations and detailed dynamic modelling. All four approaches pointed at a risk of nitrogen leaching from forest soils in southern Sweden. However, there was a substantial variation on a local scale. Basing the assessment on four different approaches makes the assessment robust.     

Effects of Deltamethrin on striatum and hippocampus mitochondrial integrity and the protective role of Quercetin in rats

Environmental Science and Pollution Research - The present work is to evaluate the neurotoxicity induced by pyrethroid insecticide “Deltamethrin” at 0.32 mg/kg/day in two main...