Characterization of microbial communities from coastal waters using microarrays

Molecular methods, including DNA probes, were used to identify and enumerate pathogenic Vibrio species in the Chesapeake Bay; our data indicated that Vibrio vulnificus exhibits seasonal fluctuations in number. Our work included a characterization of total microbial communities from the Bay; development of microarrays that identify and quantify the diversity of those communities; and observation of temporal changes in those communities. To identify members of the microbial community, we amplified the 16S rDNA gene from community DNA isolated from a biofilm sample collected from the Chesapeake Bay in February, 2000. The resultant 75 sequences were 95% or more similar to 7 species including two recently described Shewanella species, baltica and frigidimarina, that have not been previously isolated from the Chesapeake. When the genera of bacteria from biofilm after culturing are compared to those detected by subcloning amplified 16S fragments from community DNA, the cultured sample exhibited a strong bias. In oysters collected in February, the most common bacteria were previously unknown. Based on our 16S findings, we are developing microarrays to detect these and other microbial species in these estuarine communities. The microarrays will detect each species using four distinct loci, with the multiple loci serving as an internal control. The accuracy of the microarray will be measured using sentinel species such as Aeromonas species, Escherichia coli, and Vibrio vulnificus. Using microarrays, it should be possible to determine the annual fluctuations of bacterial species (culturable and non-culturable, pathogenic and non-pathogenic). The data may be applied to understanding patterns of environmental change; assessing the health of the Bay; and evaluating the risk of human illness associated with exposure to and ingestion of water and shellfish.     

Incorporating natural capital into economy-wide impact analysis: a case study from Alberta

Traditionally, decision-makers have relied on economic impactestimates derived from conventional economy-wide models. Conventional models lack the environmental linkages necessary for examining environmental stewardship and economic sustainability, and in particular the ability to assess the impact of policies on natural capital. This study investigatesenvironmentally extended economic impact estimation on a regionalscale using a case study region in the province of Alberta knownas the Foothills Model Forest (FMF). Conventional economic impactmodels are environmentally extended in pursuit of enhancingpolicy analysis and local decision-making. It is found that theflexibility of the computable general equilibrium (CGE) modelingapproach offers potential for environmental extension, with a solid grounding in economic theory. The CGE approach may be the tool of the future for more complete integrated environment andeconomic impact assessment.     

Fractionation of heavy metals and assessment of contamination of the sediments of Lake Titicaca

Chemical weathering is one of the major geochemical processes that control the mobilization of heavy metals. The present study provides the first report on heavy metal fractionation in sediments (8–156 m) of Lake Titicaca (3,820 m a.s.l.), which is shared by the Republic of Peru and the Plurinational State of Bolivia. Both contents of total Cu, Fe, Ni, Co, Mn, Cd, Pb, and Zn and also the fractionation of these heavy metals associated with four different fractions have been determined following the BCR scheme. The principal component analysis suggests that Co, Ni, and Cd can be attributed to natural sources related to the mineralized geological formations. Moreover, the sources of Cu, Fe, and Mn are effluents and wastes generated from mining activities, while Pb and Zn also suggest that their common source is associated to mining activities. According to the Risk Assessment Code, there is a moderate to high risk related to Zn, Pb, Cd, Mn, Co, and Ni mobilization and/or remobilization from the bottom sediment to the water column. Furthermore, the Geoaccumulation Index and the Enrichment Factor reveal that Zn, Pb, and Cd are enriched in the sediments. The results suggest that the effluents from various traditional mining waste sites in both countries are the main source of heavy metal contamination in the sediments of Lake Titicaca.     

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0–15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015?±?3,373, 236?±?286, 103?±?192, 29.8?±?6.04, and 141?±?270 mg kg^?1, respectively. Free metal ion activity, viz., pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺, as estimated by the Baker soil test was 9.37?±?1.89, 13.1?±?1.96, 12.8?±?1.89, 11.9?±?2.00, and 11.6?±?1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley–Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺ to the extent of 59, 56, 46, 52, and 51 %, respectively. Predictability of the solubility model based on pH, KMnO₄-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl₂-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.     

Biodegradation or simple adsorption to the support material? Development of a simple, fast and low-cost technique

Biofilms are present in several areas and are studied in microbiology, medical sciences, biology and, of course, sanitary engineering. Biofilms are used for the treatment of municipal wastewater, and their application was even before the invention of the activated sludge process. The main objective of this work was to develop a simple, fast and low-cost technique to evaluate the nature of the first decay in the concentration of an organic compound in the presence of a solid material. Though simple, the technique developed has allowed the clarification of whether the initial concentration decay is due to adsorption to the support material or a result of biodegradation. The results show that, with two different support materials, adsorption does not take place, and the biodegradation processes are responsible for the first decay in the organic concentration. The technique used offers a fast and low-cost way of studying the existence of adsorption. Two feed concentration solutions and two different support materials were used.     

Changes in water quality in agricultural catchments after deployment of wastewater treatment plant

Insufficient wastewater remediation in small communities and nonpoint source pollution are the key factors in determining the water quality of small streams in an agricultural landscape. Despite the current extensive construction of municipal wastewater treatment facilities in small communities, the level of organic substances and nutrients in the recipient catchments has not decreased in many areas. This paper analyzes the changes in the water quality of the small streams after the deployment of wastewater treatment plants that were designed to address sources of pollution from small municipalities. The analysis is based on the results from a water quality monitoring network in the small watersheds in the Czech Republic. Five rural catchments with one dominant municipal pollution source, where a wastewater treatment plant was deployed during the monitoring period, were selected according to a predefined set of criteria, from a series of 317 profiles. Basic water quality indicators were selected for the assessment: O₂, BOD-5, COD, TOC, conductivity, NH₄-N, NO₂-N, NO₃-N, PT, and PO₄-P. Results of the analysis showed that the simple deployment of the water treatment facilities at these streams often did not lead to a reduction of contamination in the streams. The expected post-deployment changes, namely, a significant and permanent reduction of stream contamination, occurred only in one catchment, whereas in the remainder of the catchments, only marginal changes or even increased concentrations of the contaminants were detected. As the critical factors that determined the efficiency of wastewater treatment were studied, the need for the consideration of the local conditions during the design of the facility, particularly regarding the size of the catchments, initial level of contamination, proper system of operation, and process optimization of the treatment facility, emerged as the important factor.     

Metals in water, sediments, and biota of an offshore oil exploration area in the Potiguar Basin, Northeastern Brazil

Metal concentrations were evaluated in water, bottom sediments, and biota in four field campaigns from 2002 to 2004 in the Potiguar Basin, northeastern Brazil, where offshore oil exploration occurs. Analyses were performed by inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry. Total metal concentrations in water (dissolved?+?particulate) and sediments were in the range expected for coastal and oceanic areas. Abnormally high concentrations in waters were only found for Ba (80 μg?l^?1) and Mn (12 μg?l^?1) at the releasing point of one of the outfalls, and for the other metals, concentrations in water were found in stations closer to shore, suggesting continental inputs. In bottom sediments, only Fe and Mn showed abnormal concentrations closer to the effluent releasing point. Metal spatial distribution in shelf sediments showed the influence of the silt–clay fraction distribution, with deeper stations at the edge of the continental shelf, which are much richer in silt–clay fraction showing higher concentrations than shallower sediments typically dominated by carbonates. Metal concentrations in estuarine (mollusks and crustaceans) and marine (fish) organisms showed highest concentrations in oysters (Crassostrea rhizophorae). Fish tissues metal concentrations were similar between the continental shelf influenced by the oil exploration area and a control site. The results were within the range of concentrations reported for pristine environments without metals contamination. The global results suggest small, if any, alteration in metal concentrations due to the oil exploration activity in the Potiguar Basin. For monitoring purposes, the continental inputs and the distribution of the clay–silt fraction need to be taken into consideration for interpreting environmental monitoring results.     

Some Dependence Models for the Time Between Ozone Exceedances in Mexico City

In this paper, we consider several modelling approaches for the mean time between exceedances of a given environmental threshold. The interest here resides in the time between ozone exceedances (also called ozone inter-exceedances times). The proposed models assume two basic density functions for the time between surpassings: the Weibull and the generalised exponential functions. Considering those distributions, a random effect with autoregressive structure is taken into account to determine unexpected changes in the mean of the inter-exceedances density functions. Those unexpected changes could be captured either by their scale parameter or by both their scale and shape parameters. The models are applied to ozone data from the monitoring network of Mexico City. Selection of the model that best explains the data is performed using the deviance information criterion and also the sum of the absolute values of the differences between the estimated and observed means of the inter-exceedances times. An analysis to detect the possible presence of change-points is also presented.     

Main results of strategic noise maps and action plans in Navarre (Spain)

According to Directive 2002/49, strategic noise maps and their correspondent action plans were carried out in the Autonomous Community of Navarre, Spain. Six strategic noise maps were produced for 120 km of major roads as well as a strategic noise map for the Agglomeration of the Region of Pamplona (ARP) with a population of 280,199 inhabitants. In the ARP, a total of 36,400 people (13.0 %) are exposed to Ln levels over 55 dBA and 42,300 people (15.1 %) are exposed to Lden levels over 65 dBA. With regard to major roads, a total of 3,900 people are exposed to Ln levels over 55 dBA and 2,400 people are exposed to Lden levels over 65 dBA. When designing action plans, different prioritisation criteria concerning rank-based effectiveness measures (mainly the amount of people benefitting from them) were taken into account.     

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.