Air quality and deposition of trace elements in Didouche Mourad, Algeria

Total suspended particulate matter and deposition fluxes of particles were investigated in the town of Didouche Mourad which is located 13 km north of Constantine. Samples of air particulate matter were collected at one site located in the heart of the town and situated 3 km north of a cement plant. Samples were collected from 2 November 2002 to 28 April 2003 every 3 days using a high volume air sampler. Sampling intervals were 24 h in all cases. During the same period, samples of dust fallout were collected at the same site. Samples were collected at 30-day intervals. Lead, chromium, manganese, nickel, copper, cobalt and cadmium deposition fluxes were measured and both the soluble and insoluble fractions were determined. Furthermore, the information gathered by this study was correlated with the corresponding hourly weather data provided by a weather station installed at the study station. The possible sources for dust and trace metals were analyzed by comparing average contributions of wind aspects to the concentrations and depositions of mass and chemical species with the average frequencies of wind direction. The mean concentration was 300 μg/m³. The average dust deposition rate through the period of study was 221 mg/(m².day). Results indicate that anthropogenic sources contribute greatly to trace elements. An exposure assessment to the heavy metals taking into account the inhalation route and soil dust ingestion was carried out and allowed direct comparison of trace metal intakes via these routes.     

Concentration of heavy metals in Karanja reservoir, Bidar district, Karnataka, India

In this study, some heavy metals concentrations (Zn, Pb, Fe, Mn, Cu, Ni) and other physico-chemical parameters were studied during October 2001 to September 2003 in Karanja reservoir, Bidar district. Water quality parameters were collected monthly basis whereas heavy metals were analyzed by Atomic Adsorption Spectrometer (AAS). Heavy metals have shown within the permissible limits, except Fe and Ni were recorded higher values in southwest monsoon, where as Mn has showed higher concentration in northeast monsoon in and summer. All other physico-chemical parameters are with in the permissible limit. Water is moderately hard and reservoir is productive.     

Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties

In this study, an interval-parameter fuzzy-stochastic two-stage programming (IFSTP) approach is developed for irrigation planning within an agriculture system under multiple uncertainties. A concept of the distribution with fuzzy-interval probability (DFIP) is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets, and probability distributions. IFSTP integrates the interval programming, two-stage stochastic programming, and fuzzy-stochastic programming within a general optimization framework. IFSTP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised amounts are not delivered. IFSTP is applied to an irrigation planning in a water resources management system. Solutions from IFSTP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable solutions are generated for objective function values and decision variables; thus, a number of decision alternatives can be generated under different levels of stream flows.     

Heavy metals partitioning in sediments of the Kabini River in South India

Cu, Cr, Fe, Mn, Ni, Pb, and Zn in the sediments of the Kabini River, Karnataka, India was studied to determine the association of metal with various geochemical phases by sequential extraction. The variations of heavy metal concentration depend on the lithology of the river basin and partly on anthropogenic activities. The Kabini River sediments are dominated by Sargur supracrustals with amphibolites, gneisses, carbonates, and ultrabasic rocks weathering into gneissic and serpentine soils carrying a natural load of cationic heavy metals. The source of heavy metals in the Kabini riverbed sediments is normally envisaged as additional inputs from anthropogenic over and above natural and lithogenic sources. Geochemical study indicates the metals under study were present mostly in the least mobilizable fraction in the overlying water and it is concluded that heavy metals in these sediments are to a great extent derived from multisource anthropogenic inputs besides geochemical background contributions The results show that lead and chromium have higher potential for mobilization from the sediment due to higher concentration at the exchangeable ion and sulfide ion bounded, also Cu and Pb have the greatest percentage of carbonate fraction, it means that the study area received inputs from urban and industrial effluents. Association of the Fe with organic matter fraction can be explained by the high affinity of these elements for the humic substances. Further, Zn and Ni reveal a significant enrichment in sediment and it is due to release of industrial wastewater into the river. These trace metals are possible contaminants to enter into aquatic and food chain.     

Assessment of potential health risk for inhabitants living near a former lead smelter. Part 1: metal concentrations in soils, agricultural crops, and homegrown vegetables

Soil contamination by metals engenders important environmental and health problems in northern France where a smelter (Metaleurop Nord) was in activity for more than a century. This study aims to look at the long-term effects of the smelter after its closedown by combining data on the degree of soil contamination and the quality of the crops grown (agricultural crops and homegrown vegetables) in these soils for a better assessment of the local population’s exposure to Cd, Pb, and Zn. Seven years after the Metaleurop Nord closedown, (1) the agricultural and urban topsoils were strongly contaminated by Cd, Pb, and Zn; (2) the kitchen garden topsoils were even more polluted than the agricultural soils, with great variability in metal concentrations within the gardens studied; (3) a high proportion of the agricultural crops for foodstuffs did not conform with the European legislation; (4) for feedstuffs, most samples did not exceed the Cd and Pb legislation limits, indicating that feedstuffs may be an opportunity for most agricultural produce; and (5) a high proportion of the vegetables produced in the kitchen gardens did not conform with the European foodstuff legislation. The high contamination level of the soils studied continues to be a risk for the environment and the population’s health. A further investigation (part 2) assesses the associated potential health risk for local inhabitants through consumption of homegrown vegetables and ingestion of soil particles by estimating the site-specific human health assessment criteria for Cd and Pb.     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

Arsenic and other trace elements in two catfish species from Paranaguá Estuarine Complex, Paraná, Brazil

Concentrations of arsenic and four additional trace elements (Cu, Cr, Ni, and Zn) were determined by inductively coupled plasma–optical emission spectrometry in the muscular tissue of the yellow catfish (Cathorops spixii) and the urutu catfish (Genidens genidens) from Paranaguá Estuarine Complex, Brazil (PEC). The PEC can be characterized by an environment of high ecological and economic importance in which preserved areas of rainforest and mangroves coexist with urban activities as ports and industries. The average concentrations (in milligram per kilogram dry weight) of elements in the muscle tissue of C. spixii are as follows: Zn (31), As (17), Cu (1.17), Cr (0.62), and Ni (0.28). Similar concentrations could be found in G. genidens with exception of As: Zn (36), As (4.78), Cu (1.14), Cr (0.51), and Ni (0.14). Fish from the geographic northern rural region (Guaraqueçaba–Benito) display higher As concentrations in the muscle tissues than fish found in the south-western (urban) part of the PEC. An international comparison of muscle tissue concentrations of trace elements in fish was made. Except for Ni in C. spixii, a tendency of decrease in element concentration with increasing size (age) of the fish could be observed. According to the National Health Surveillance Agency of Brazil, levels of Cr and As exceeded the permissible limits for seafood. An estimation of the provisional tolerable weekly intake of As was calculated with 109 % for C. spixii and with 29 % for G. genidens.