Fuzzy logic modeling of bioaccumulation pattern of metals in coastal biota of Ondo State,Nigeria

The accumulation patterns of ten metals in tissues of plant, Eichornia crassipes, and fishes, Hydrocynus forskahlii and Oreochromis mossambicus, were modeled with simple fuzzy classification (SFC) to assess toxic effects of anthropogenic activities on the coastal biota. The plant sample was separated into root, stem, and leaves and the fishes into bones, internal tissues, and muscles. They were analyzed for As, Cd, Cr, Cu, Ni, Pb, V, Fe, Mn, and Zn after wet oxidation of their dried samples. The results were converted into membership functions of five accumulation classes and aggregated with SFC. The classification results showed that there was no metal accumulation in the plant parts while the fishes were classified into low accumulation category. The internal tissues of the fishes had higher metal accumulation than the other parts. Generally, Fe and Mn had highest concentrations in the biota but are natural to the area and may not constitute significant risk. Cr had the highest transfer and accumulation from the coastal water into the aquatic lives and may be indicative of risk prone system being a toxic metal. Metal contaminations in the zone had not significantly accumulated in the biota making them less prone to risk associated with metal accumulation.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

Preliminary air pollution monitoring in San Miguel, Buenos Aires

Passive diffusion samplers were employed in San Miguel(Buenos Aires Metropolitan Area) for a preliminary airpollution monitoring. The highest loads were observedin downtown, compared with an urban background site.Total suspended particulate matter (TSPM) varied from0.257 to 0.033 mg cm^-2 month^-1; dust was examinedfor particle nature and size distribution. A similartrend was observed for nitrogen dioxide (NO₂) andTSPM spatial distribution, suggesting that traffic isthe major pollution source. Sulphur dioxide (SO₂)values were low and rather homogeneous. Levels for theinvestigated pollutants are below EPA's guide linevalues. Geographic (flat area, near to Rio de LaPlata) and climatologic factors (rainfalls andvariable wind directions) contribute to disperse pollutants.     

Comparison of two metal surveys by moss Tortula ruralis in Budapest, Hungary

Moss transplants of Tortula ruralis were used as active biomonitoring organisms as part of a monitoring study to assess the metals (Al, Cd, Cu, Cr, Fe, Ni, Pb, V and Zn) associated with ambient particles on mosses in Budapest, the capital town of Hungary. The moss samples were collected in a nature conservation area from a semi-arid sand grassland (Festucetum vaginatae danubiale), less than 1 month before transplantation. Moss cushions were exposed to pollution in Budapest during October–November 1993 and February–March 1994. In the study area, 16 sites were marked out as measuring sites, in accordance with the structure of the city. A similar stand was established in the Botanical Gardens of the Szent István University in Gödöll? as a control site. ICP-AES analysis of moss for metals showed the ability of Tortula ruralis to accumulate the metals under study. Control site showed lower impact in comparison to the other sites.     

Development and Testing of 2D Finite Difference Model in Open Channels

This study develops a depth-averaged two-dimensional (2D) numerical model using a finite difference method (FDM) on a staggered grid. The governing equations were solved using the Marker and Cell method that was developed at the Los Alamos laboratories by Harlow and Welch in 1965. In the paper, an explicit FDM was used to solve the governing equations. A first-order approximation was used for the temporal derivative. Second-order central difference approximations were used for space discretization. The time step is limited by the Courant–Friedrichs–Lewy (CFL) condition. The time step used in this study depends on the grid spacing and velocity components in the x- and y-directions. The study is divided into two steps: the first step is to develop a depth-averaged 2D numerical model to simulate the flow process. The second constructs a module to calculate the bed load transport and simulate the river morphology in the areas that have steep slopes, torrents, and mountain rivers. Developed model was applied to the artificial channel and a flood event in the Asungjun River section of the mountainous Yangyang Namdae River (South Korea). General simulation results showed that the developed model was in good agreement with the observed data.     

Monitoring of meteorological and hydrological droughts in the Vistula basin (Poland)

The article presents the course of meteorological droughts in Vistula subcatchments in years 1981–2010 and their influence on the occurrence of hydrological droughts. Using the Standardized Precipitation Index (SPI) as an indicator of meteorological drought on the one hand and the Standardized Water-level Index (SWI) and Standardized Runoff Index (SRI) as indicators of hydrological drought on the other, the mutual relationships between precipitation conditions and hydrological conditions were evaluated, as well as the relationships between the two drought types. Studies were conducted for three cumulative periods of these indices, of 12, 24, and 48 months. It was determined that meteorological droughts occurred earliest in the north-western and central part of the basin, and latest in areas lying above 300 m a.s.l. and in the south of Poland. Total duration, depending on the cumulative period, for SPI comprised from 38 to 41% of the analyzed period and for SWI (35–47%) and SRI (24–51%). The strongest relationships were identified in the central part of the Vistula (0.8?<?r?<?0.85), while the weakest relationships were recorded in the foothill region (r?<?0.5). There were also indicated non-climate-related factors influencing those relationships (underground reservoirs, diverse Vistula water resource usage for municipal and industrial intake).     

The effects of socioeconomic parameters on household solid-waste generation and composition in developing countries (a case study: Ahvaz,Iran)

Environment problems associated with the generation of waste are part of societal changes where households play an important role. These societal changes influence the size, structure and characteristic of given households. For the effective planning of solid-waste handling infrastructure, it is essential to know the quantity of waste generation and its composition. This paper presents the findings of a study carried out in an urban municipal area in Iran to determine the household solid-waste generation rate and waste composition based on field surveys and to determine the related socioeconomic parameters. The dependent variables were waste generation and composition, and independent variables were family size, family employment, age, number of room and education. Over 400 sample households were selected for the study using a stratified random sampling methodology and from five different socioeconomic groups. Waste collected from all groups of households were segregated and weighted. Waste generation rate was 5.4 kg/household/day. Household solid waste comprised of ten categories of wastes and with the largest component (76.9%). The generation and composition of household solid waste were correlated with family size, education level and households income. This paper adequately suggests new insights concerning the role of socioeconomic parameters in affecting the generation of household waste.     

Reduction of sludge formed during a coagulation treatment of Ridomil Gold by means of non-thermal quenched plasma pre-treatment

Chemical coagulation and adsorption, despite many drawbacks, are actually the main techniques used for the removal of pollutants from aqueous solution; however, these techniques are becoming ineffective due to the exponential increase in the amount and complexity of discharged pollutants; thus, the sludge treatment process became a more complex challenge. The present study focuses on the way to reduce the quantity of sludge formed during the removal of Ridomil Gold, a widely used pesticide-fungicide in agriculture. Results revealed that pre-treatment of initial waste solution by the gliding arc (Glidarc), a source of non-thermal plasma, leads to a significant reduction of the sludge formed during the coagulation treatment. For a 20-min pre-treated effluent Glidarc followed by chemical coagulation, there was a reduction in the volume of sludge formed in the order of 90 and 80% for alum and ferric sulfate coagulants respectively without reducing the performance of pesticide removal. Therefore, there is a positive synergism between treatment by chemical coagulation and plasma treatment. These results suggest that the Glidarc can be an effective solution for the reduction of sludge obtained during treatment by coagulation.     

Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin

In this study, the water quality of the Coruh River Basin, which is located in the Eastern Black Sea Region of Turkey, was evaluated. The water quality data measurement results obtained by the State Hydraulic Works 26th Regional Directorate from four different sites over a course of 4 years between the years 2011 and 2014 in the Coruh River Basin were used as the data. In this study, the water quality was evaluated by using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI) method and discriminant analysis (DA). The water quality of the Coruh River Basin was calculated as 30.4 and 71.35 by using the CCME WQI and classified as “poor,” “marginal,” and “fair”. These values show that the water of the Coruh River Basin is degraded and under threat and its overall quality is not close to natural or desired levels. The monitoring sites were divided into two groups by the cluster analysis (CA). DA is a multivariate analysis technique used to divide individuals or objects into different groups and assign them into predetermined groups. As a result of DA, calcium (Ca) and sulfate (SO₄) were determined to be significant parameters in the determination of the water quality of the Coruh River Basin. The success of DA depends on the percentage of correct classification. As a result of the analysis, 23% of the parameters in the first measurement point, 69.2% of the parameters in the second and third measurement points, and 76.9% of the parameters in the fourth measurement point were classified correctly. Since the second measurement point is the discharge point of a copper mine, it can be said that the water quality parameters measured may provide accurate results in detecting pollution at this point.