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.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Test of a Modelling System for Estimating Nitrogen Leaching – A Pilot Study in a Small Agricultural Catchment

Nitrogen leaching is a world-wide concern for the quality of ground- and surfacewater. Measures to abate this is still limited by a lack of understanding mechanisms behind all factors describing the leaching process, time lags between countermeasures and improvement in waterquality and spatial distribution of nitrogen leaching. The purpose of this study was to do an initial test of the SOILNDB model system which is built on the existing mechanistic SOIL and SOILN models and an automatic parameterization procedure for use of simplified input data. The test was done by simulating nitrogen leaching from each of the 150 fields in a small catchment during a three-year study period. The simulated mean root-zone nitrogen leaching rate from all the fields in the catchment was compared to measurements of nitrogen flow in the stream draining the catchment and showed good agreement in between-year dynamics.     

Transportation and fate of cationic surfactant in river water

The degradation, sorption, transportation and material balance of cationic surfactants discharged from domestic waste into river water was studied. Ion-pair solid-phase extraction behavior showed that the sorption of cationic surfactants as an ion-pair with anionic surfactant onto river sediment was so strong that little cationic surfactant was found in the bulk water. Cationic surfactant was found in river sediment at more than 500 times higher concentration than that in the bulk water. The degradation of the cationic surfactant was very slow in river water and much slower in the sediment. A material balance of cationic surfactant was estimated for a river running through Toyama City by measuring the flow rate and the concentration of cationic surfactant in the water at several points. It was found that more than 30% of cationic surfactant introduced to the river was lost during the river running through ca. 3 km in 3 h. This reduction probably comes from a quick transfer of the cationic surfactant from river water to sediment and water weed by means of adsorption or precipitation with suspending solids.     

Multiplex-PCR and PCR-RFLP assays to monitor water quality against pathogenic bacteria

In this work we developed and optimized two molecular-based approaches to monitor rapidly, sensitively and specifically bacterial pathogens from three different genera, Escherichia coli, Pseudomonas aeruginosa, and Salmonella spp., directly in waters. To achieve this aim, firstly a multiplex-PCR assay (M-PCR) was optimized using a primer pair specific for each pathogen. Secondly, as a molecular confirmatory test after isolation of the pathogens by classical microbiological methods, PCR-RFLP of their amplified 16S rDNA genes was performed. It was observed from the results that the developed M-PCR assay has significant impact on the ability to detect sensitively, rapidly and specifically the three pathogens directly in water within a short time (5 h from sampling to obtain final results), therefore it represents a considerable advancement over other known more time-consuming and less-sensitive methods for identification and characterization of these kinds of pathogens.