Biomagnification of anthropogenic and naturally-produced organobrominated compounds in a marine food web from Sydney Harbour, Australia

Polybrominated diphenyl ethers (PBDEs) and naturally-produced organobrominated compounds, such as methoxylated PBDEs (MeO-PBDEs), have been scarcely studied in the Southern Hemisphere. Yet, sources of the latter group of compounds were found in Southern regions, specifically in Australia. The environmental distribution and biomagnification potential of organobrominated compounds were therefore investigated in a representative aquatic food chain (invertebrates and fish) from the Sydney Harbour, Australia. Mean PBDE concentrations ranged from 6.4 ng/g lipid weight (lw) in squid to 115 ng/g lw in flounder. BDE 47 was the dominant congener, followed by BDE 100. Mean levels of MeO-PBDEs (sum of congeners 2’-MeO-BDE 68 and 6-MeO-BDE 47) were as high as 110 ng/g lw in tailor, with a slight dominance of 2’-MeO-BDE 68. Polybrominated hexahydroxanthene derivates (PBHDs), another class of naturally-produced compounds, were found at variable concentrations and ranged from 4.7 ng/g lw in fanbelly and 146 ng/g lw in tailor. The tribrominated PBHD isomer dominated in the samples, except for luderick and squid. The lower levels of PBDEs found in luderick from the harbour compared to those obtained from the upper Parramatta River indicated a terrestrial (anthropogenic) origin of PBDEs, while the higher levels of MeO-PBDEs and PBHDs in the samples from the harbour confirmed the marine (natural) origin of these compounds. The highest trophic magnification factor (TMF) was found for sum PBDEs (3.9), while TMFs for sum MeO-PBDEs and sum PBHDs were 2.9 and 3.4, respectively. This suggests that biomagnification occurs in the studied aquatic food chain for anthropogenic brominated compounds, but also for the naturally-produced organobromines.     

Adapting a geographical information system-based water resource management to the needs of the Romanian water authorities

Background, aim, and scope

The need for global and integrated approaches to water resources management, both from the quantitative and the qualitative point of view, has long been recognized. Water quality management is a major issue for sustainable development and a mandatory task with respect to the implementation of the European Water Framework Directive as well as the Swiss legislation. However, data modelling to develop relational databases and subsequent geographic information system (GIS)-based water management instruments are a rather recent and not that widespread trend. The publication of overall guidelines for data modelling along with the EU Water Framework Directive is an important milestone in this area. Improving overall water quality requires better and more easily accessible data, but also the possibility to link data to simulation models. Models are to be used to derive indicators that will in turn support decision-making processes. For this whole chain to become effective at a river basin scale, all its components have to become part of the current daily practice of the local water administration. Any system, tool, or instrument that is not designed to meet, first of all, the fundamental needs of its primary end-users has almost no chance to be successful in the longer term.

Materials and methods

Although based on a pre-existing water resources management system developed in Switzerland, the methodological approach applied to develop a GIS-based water quality management system adapted to the Romanian context followed a set of well-defined steps: the first and very important step is the assessment of needs (on the basis of a careful analysis of the various activities and missions of the water administration and other relevant stakeholders in water management related issues). On that basis, a conceptual data model (CDM) can be developed, to be later on turned into a physical database. Finally, the specifically requested additional functionalities (i.e. functionalities not provided by classical commercial GIS software), also identified during the assessment of needs, are developed. This methodology was applied, on an experimental basin, in the Ialomita River basin.

Results

The results obtained from this action-research project consist of a set of tangible elements, among which (1) a conceptual data model adapted to the Romanian specificities regarding water resources management (needs, data availability, etc.), (2) a related spatial relational database (objects and attributes in tables, links, etc.), that can be used to store the data collected, among others, by the water administration, and later on exploited with geographical information systems, (3) a toolbar (in the ESRI environment) offering the requested data processing and visualizing functionalities. Lessons learned from this whole process can be considered as additional, although less tangible, results.

Discussion

The applied methodology is fairly classical and did not come up with revolutionary results. Actually, the interesting aspects of this work are, on the one hand, and obviously, the fact that it produced tools matching the needs of the local (if not national) water administration (i.e. with a good chance of being effectively used in the day-to-day practice), and, on the other hand, the adaptations and adjustments that were needed both at the staff level and in technical terms.

Conclusions

This research showed that a GIS-based water management system needs to be backed by some basic data management tools that form the necessary support upon which a GIS can be deployed. The main lesson gained is that technology transfer has to pay much attention to the differences in existing situations and backgrounds in general, and therefore must be able to show much flexibility. The fact that the original objectives could be adapted to meet the real needs of the local end-users is considered as a major aspect in achieving a successful adaptation and development of water resources management tools. Time needed to setup things in real life was probably the most underestimated aspect in this technology transfer process.

Recommendations and perspectives

The whole material produced (conceptual data model, database and GIS tools) was disseminated among all river basin authorities in Romania on the behalf of the national water administration (ANAR). The fact that further developments, for example, to address water quantity issues more precisely, as envisaged by ANAR, can be seen as an indication that this project succeeded in providing an appropriate input to improve water quality in Romania on the long term.

     

Influence of natural events on the concentration and composition of atmospheric particulate matter

A ten-month field study aimed to determine the contribution of natural events (i.e. sea-salt and mineral dust events) to urban PM concentration was carried out at six sampling sites in Central Italy (Lazio region). Four indicators have been used to identify natural events during the period of the study. The first one is constituted by the ratio between number of particles in the coarse to the accumulation mode. It is simple, cheap, and the information are given in quasi-real time, but the nature of the event (sea-salt or mineral dust) is not detectable. The second indicator relies on the chemical analysis of the collected PM by X-ray fluorescence (XRF) and allows a robust identification of sea-salt and crustal components. The third one is based on diagnostic ratios of elemental fractions: Mg_extractable/Ti_residue for sea-salt and Ti_residue/Sb_residue for mineral dust. It requires skilled staff but it is most accurate and sensible. The last indicator, constructed on the basis of natural radioactivity data, is not diagnostic for the nature of the event but it is able to estimate the increase in PM concentration with respect to the expected concentration in the absence of natural events.The relevance of natural events and the variations in PM concentration and composition during the study are discussed. The joined use of the four indicators allowed the identification of about 20 natural PM episodes. In general, sea-salt aerosol events did not cause exceedance of the daily EU limit value for PM₁₀. Saharan dust events, instead, were in most cases responsible for the exceedance of the limit value at all stations.     

Numerical simulation of an array of fences in Saemangeum reclaimed land

This paper discusses about the quantitative effect of windbreak fences on wind velocity in the reclaimed land at Saemangeum in South Korea. Windbreak fences were constructed in the reclaimed land to reduce the wind velocity to prevent the generation and diffusion of dust. However, up to this time, no in-depth studies were conducted to quantitatively measure the effect of the windbreak fences on wind velocity thus an optimum windbreak structure is not yet determined. Using CFD simulations, the effects of fence porosity, fence height, and the distance between the adjacent fences were investigated. A wind tunnel experiment was initially conducted and data gathered were used to develop the CFD models. From the experiments and CFD simulations, the overall percentage difference of the measured velocities was 7.20% which is generally acceptable to establishing the reliability of the CFD models. The reduction effect on wind velocity was measured in between the adjacent fences up to a height of 0.6 m from the ground surface. In terms of porosity ( = 0, 0.2, 0.4, 0.6), 0.2 was found to be the optimum value. Conversely, the effect of fence height (0.6, 0.8 and 1.0 m) showed no significant difference; therefore, 0.6 m height is recommended. In addition, the reduction effect of distance between the adjacent fences (2, 4 and 6 m) on wind velocity having a 0.2 porosity has decreased to about 75% regardless of the distance. In the case of the reclaimed land in Saemangeum, a decrease of 75% can prevent the generation and diffusion of dusts. However, the source of dusts is very large. Therefore, constructing an array of windbreak with 6 m distance between them is deemed necessary.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

A computational study of particulate emissions from an open pit quarry under neutral atmospheric conditions

The extraction of minerals from surface mines and quarries can produce significant fugitive dust emissions as a result of site activities such as blasting, road haulage, loading, crushing and stockpiling. If uncontrolled, these emissions can present serious environmental, health, safety and operational issues impacting both site personnel and the wider community.The dispersion of pollutant emissions within the atmosphere is principally determined by the background wind systems characterized by the atmospheric boundary layer (ABL). This paper presents an overview of the construction and solution of a computational fluid dynamics (CFD) model to replicate the development of the internal ventilation regime within a surface quarry excavation due to the presence of a neutral ABL above this excavation. This model was then used to study the dispersion and deposition of fugitive mineral dust particles generated during rock blasting operations. The paths of the mineral particles were modelled using Lagrangian particle tracking. Particles of four size fractions were released from five blast locations for eight different wind directions.The study concluded that dependent on the location of the bench blast within the quarry and the direction of the wind, a mass fraction of between 0.3 and 0.6 of the emitted mineral particles was retained within the quarry. The retention was largest when the distance from the blast location to the downwind pit boundary was greatest.     

Conceptual issues in designing a policy to phase out metal-based antifouling paints on recreational boats in San Diego Bay

In marine areas throughout the world where recreational boats are densely located, concentrations of copper in the water are being found to be in excess of government standards, due to the hull coatings used on these boats. Copper-based hull coatings are intended to be antifouling in that they retard the growth of algae, barnacles and tubeworms; but alternatives exist that can eliminate the harm that copper contamination does to marine organisms. A variety of policy options are available to mandate or provide economic incentives to switch to these less harmful alternatives. This paper puts forth a conceptual framework for thinking about how to design and evaluate alternative policies to transition to nontoxic boat hulls, drawing from the authors' experience designing a policy for use in San Diego Bay. Many of the issues raised are broadly applicable to environmental problems where the solution involves a large-scale replacement of durable consumer goods.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.