Effect of humic substances on the precipitation of calcium phosphate

For phosphorus （P） recovery from wastewater, the effect of humic substances （HS） on the precipitation of calcium phosphate was studied. Batch experiments of calcium phosphate precipitation were undertaken with synthetic water that contained 20 mg/L phosphate （as P） and 20 mg/L HS （as dissolved organic carbon, DOC） at a constant pH value in the range of 8.0-10.0. The concentration variations of phosphate, calcium （Ca） and HS were measured in the precipitation process; the crystalline state and compositions of the precipitates were analysed by powder X-ray diffraction （XRD） and chemical methods, respectively. It showed that at solution pH 8.0, the precipitation rate and removal efficiency of phosphate were greatly reduced by HS, but at solution pH ≥9.0, the effect of HS was very small. The Ca consumption for the precipitation of phosphate increased when HS was added; HS was also removed from solution with the precipitation of calcium phosphate. At solution pH 8.0 and HS concentrations ≤3.5 mg/L, and at pH ≥ 9.0 and HS concentrations ≤ 10 mg/L, the final precipitates were proved to be hydroxyapatite （HAP） by XRD. The increases of solution pH value and initial Ca/P ratio helped reduce the influence of HS on the precipitation of phosphate.     

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.     

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.     

A Three-Dimensional Water Quality Model of Chicago Area Waterway System (CAWS)

As outfalls from various water reclamation plants, pumping stations, and combined sewer overflow outfalls discharge into the Chicago Area Waterway System (CAWS), an enhanced understanding of the final fate of crucial water quality state variables is of utmost importance. This paper reports the development and application of a 3D water quality model for a modified CAWS combined with the hydrodynamic kernel of Environmental Fluid Dynamics Code (EFDC). The modified CAWS is used to demonstrate the usefulness of the model while eliminating complications beyond the scope of this initial effort. The water quality model developed and presented in this research is a simplistic dissolved oxygen (DO)—biochemical oxygen demand model with the facility to account for the interaction between the water column and the bed. The aforementioned model is applied for the month of May 2009. The results from the hydrodynamic (EFDC) and water quality model is validated with the help of the observed data obtained from United States Geological Survey gaging stations and Metropolitan Water Reclamation District of Greater Chicago monitoring stations present inside the modeled domain. The 3D modeling captured the hydrodynamic and water-quality processes in CAWS in a satisfactory manner. Furthermore, modeling results showed and proved the interdependence of water quality characteristics in Bubbly Creek and CAWS with the effluent concentration from Racine Avenue Pumping Station situated at the head of Bubbly Creek, South Fork of South Branch of Chicago River.     

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.     

Statistical apportionment and risk assessment of selected metals in sediments from Rawal Lake (Pakistan)

The present study was carried out in order to evaluate the statistical apportionment and risk assessment of selected metals (Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Pb, Sr, and Zn) in freshly deposited sediments in Rawal Lake, Pakistan. Composite sediment samples were collected, oven-dried, grounded, homogenized, and processed to assess the water-soluble and acid extractable concentrations of the metals in the water extract and acid extract of the sediments using flame atomic absorption spectrophotometer. Statistical methods were used to identify the possible sources of the metals. Sediment quality guidelines and potential acute toxicity were used to evaluate the ecotoxicological sense of selected metals. Non-carcinogenic health risk assessment was also carried out to determine the potential adverse health risks to the inhabitants. Relatively higher concentration was noted for Ca, Fe, Mg, Na, K, Mn, and Sr in the sediment samples. Principal component analysis and cluster analysis revealed anthropogenic contributions of Cd, Pb, Cr, Mn, Fe, and Li in the sediments. Enrichment factors of the metals in sediments showed severe to moderate enrichment of Cd, Pb, Ca, Fe, Li, Mn, and Sr. Geoaccumulation indices and contamination factors evidenced significant contamination by Cd and Pb, although, on the whole, low degree of contamination was noted. The levels of some metals exceeded the sediment quality guidelines, which revealed frequently adverse biological effects to the dwelling biota in the aquatic ecosystem. The sediments were found to be significantly contaminated by Cd, Pb, Cr, Mn, Fe, and Li.     

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.     

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.     

Soil properties and crop productivity as influenced by flyash incorporation in soil

Field experiments were carried out during 1996–97at Gulawathi, Muthiani and Salarpur Villages, IARI Farm, NewDelhi and NCPP Campus, Dadri to evaluate changes in soilcharacteristics and growth of wheat (Triticum aestivum L.),mustard (Brassica juncea L.), lentil (Lence esculentaMoench.), rice (Oryza sativa L.) and maize (Zea mays L.) byvarying amounts of flyash addition (up to 50t ha^-1) in soils atsowing/transplanting time of crops. Flyash addition in areasadjoining NCPP Thermal Power Plant, Dadri, Ghaziabad, U.P.ranged from 5–12 t ha^-1 yr^-1 in 1995–96. Shoot and root growthand yield of test crops at different locations after flyashincorporation resulted in beneficial effects of flyashaddition in most cases. The silt dominant texture of flyashimproved loamy sand to sandy loam textures of the surfacesoils at the farmers' fields. The increased growth in yield ofcrops with flyash incorporation was possibly due tomodifications in soil moisture retention and transmissioncharacteristics, bulk density, physico-chemical characterssuch as pH and EC and organic carbon content. The response offlyash addition in the soil on soil health and cropproductivity needs to be evaluated on long-term sustainableaspects.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.