Human health impacts of exposure to metals through extreme consumption of fish from the Colombian Caribbean Sea

The health risks of metal exposure due to the high consumption of fish were assessed for a riverine population living on the Caribbean coast of Colombia. The concentrations of metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) in the edible tissues of fish were determined and used for risk assessment. The daily fish consumption of residents (n = 95) was as high as 283, 366 and 469 g/day in children (CH), women of childbearing age (WCHA) and the remaining population groups (RP), respectively. The estimation of the potential risk (HQ) indicated that there was no health risk from most of the metals, because they did not exceed their related reference doses, with values of HQ < 1. Although the concentrations of Pb and Hg were not particularly high in fish (<0.2 µg/g), their possible health effects for vulnerable groups are of great concern due to the extremely high fish intake. The Pb intake for all groups was higher than the lower confidence limit of the benchmark dose for nephrotoxicity and neurodevelopmental effects in children. The weekly intake of methylmercury was also elevated, with values approximately 3, 2 and 1.5 times the provisional tolerable weekly intake for CH, WCHA and RP, respectively. Moreover, higher Hg levels were found in top predators, whereas maximum levels for other metals were found in bottom-feeding fish. This study highlights that an accurate data of daily intake, a continuous monitoring of metals in fish and their related fish consumption advisories to protect subsistence fishing communities are recommended in a local and worldwide context.     

Evaluation of geomorphic changes and retreat rates of a coastal pyroclastic cliff in the Campi Flegrei volcanic district,southern Italy

Geomorphic evolution of sea cliffs has significant impact on coastal settlements worldwide, so that evaluation of cliff instability processes, failure factors, and retreat rates involves a growing number of scientists for coastal risk and management purposes. Aerial photogrammetry and lidar are among the most used techniques for topographic characterization and geomorphic monitoring of coastal environments. A crucial role in the combined use of such techniques is the evaluation of different spatial accuracy and co-registration between derived terrain models, so that a robust error analysis is required. In this study, we present a change detection analysis of the Torrefumo coastal cliff, in the Campi Flegrei volcanic area (Southern Italy). Aerial images taken in 1956 and 1974, processed through digital photogrammetry, and an airborne lidar point cloud acquired in 2008 were used to produce Digital Elevation Models of the cliff. The analysis was based on the multi-temporal comparison of these models and included the calculation of volumetric changes and average retreat rates of the cliff face with reference to the 1956–1974 and 1974–2008 time intervals. The spatially variable elevation uncertainty of each Digital Elevation Model was evaluated with a probabilistic approach based on the fuzzy set theory. The results of this study showed significant eroded volumes during the period 1956–1974 and relatively smaller volumes in the 1974–2008 time span, with mean annual retreat rates of 1.2 m/year and 0.17 m/year, respectively. We infer that the significant decrease of erosion characterizing the second period was induced by the sheltering effect at the base of the cliff produced by the construction of a seawall in the early 80’s.     

Multiple source spatial cluster detection via multi-criteria analysis

Multiple data sources are essential to provide reliable information regarding the emergence of potential health threats, compared to single source methods. Spatial Scan Statistics have been adapted to analyze multivariate data sources, but only ad hoc procedures have been devised to address the problem of selecting the most likely cluster and computing its significance. In this work, information from multiple data sources of disease surveillance is incorporated to achieve more coherent spatial cluster detection using tools from multi-criteria analysis. The best cluster solutions are found by maximizing two objective functions simultaneously, based on the concept of dominance. To evaluate the statistical significance of solutions, a statistical approach based on the concept of attainment function is used. The multi-criteria approach has several advantages: the representation of the evaluation function for each data source is clear, and does not suffer from an artificial, and possibly confusing mixture with the other data source evaluations; it is possible to attribute, in a rigorous way, the statistical significance of each candidate cluster; and it is possible to analyze and pick-up the best cluster solutions, as given naturally by the non-dominated set. The methodology is illustrated with real datasets.     

The effect of environmental regulation on firms' competitive performance: the case of the building & construction sector in some EU regions

There is a considerable debate on the effects of environmental regulation on competitive performance. Based on survey data, this paper analyzesthe two main research questions, derived from literature, on the links between environmental regulation and competitiveness, by focusing on firms operating in the building and construction sector, i.e.: 1) whether environmental policy stringency affects the competitive performance of firms in the building and construction sector 2) and how a specific form of environmental regulation (direct regulation, economic instruments and soft instruments) affects this performance? By applying a regression analysis, we find that a more stringent environmental regulation, measured by inspection frequency, provides a positive impulse for increasing investments in advanced technological equipment and innovative products and on business performance. Moreover, a well-designed “direct regulation” appears to be the most effective policy instrument for prompting the positive impact of environmental policies on innovation and intangible performance while economic instruments do negatively affect business performance.     

Occupational accidents model based on risk–injury affinity groups

This article sets outs a generalized utility model for the diagnosis and prediction of accidents among the Spanish workforce. Based on observational data classified into a risk–injury contingency table (19 × 19), we have summarized the accident rate of all Spanish companies over an 11-year period (75,19,732 accidents). By using correspondence analysis a structure composed of three axes can be obtained, the combination of which identifies three separate risk and injury groups, which we use as a general Spanish pattern. The relationships of greater affinity or likelihood amongst the risks and injuries identified in the pattern facilitate decision-making at the risk-assessment stage in Spanish companies. Each risk–injury group has its own characteristics, interpretable within the phenomenological framework of the accident.The main advantage of this model is its potential application to any other country and the feasibility of contrasting results from different countries. One limiting factor, however, is that the model currently lacks a common classification frame for risks and injuries which would enhance this contrast. The aim of this model is to automatically manage work-related accidents at a national level.     

Hydrochemical,isotopic and microbiota characterization of telese mineral waters (Southern Italy)

Environmental Geochemistry and Health - The study deals with the analyses of springs and wells at the base of Montepugliano Hill that represents the SE edge of the wide carbonate Matese massif...     

Iron oxide nanoparticles embedded in organic microparticles from Yerba Mate useful for remediation of textile wastewater through a photo-Fenton treatment: Ilex paraguariensis as a platform of environmental interest – Part 1

Environmental Science and Pollution Research - Seven composites of iron oxide nanoparticles embedded in organic microparticles mediated by Cu(II) were synthesized using yerba mate (Ilex...     

A retrospective study on dioxins and dioxin-like polychlorinated biphenyls in milk and dairy products from the Latium region (Italy) over a 7-year study period (2011–2017)

Environmental Science and Pollution Research - This study reports the data of polychlorinated dibenzo-p-dioxins (PCDDs), -furans (PCDFs), and polychlorinated biphenyls dioxin-like (dl PCBs)...     

Optimal Environmental Policy for a Polluting Monopoly with Abatement Costs: Taxes Versus Standards

In this paper, we characterize the optimal environmental policy for a polluting monopoly that devotes resources to abatement activities when damages are caused by a stock pollutant. With this aim, we calculate the stagewise feedback Stackelberg equilibrium of a (differential) policy game where the regulator is the leader and the monopolist is the follower. Our analysis shows that the first-best policy consists of applying a Pigouvian tax and a subsidy on production equal to the difference between the price and the marginal revenue. However, for a stock pollutant, the Pigouvian tax is not equal to the marginal damages but is given by the difference between the social and private valuation of the pollution stock. On the other hand, if a second-best emission tax is used, the tax is lower than the Pigouvian tax and the difference decreases with the price elasticity of the demand. Finally, we find that taxes and standards are equivalent in a second-best setting. In the second part of the paper, we solve a linear-quadratic differential game and we obtain that the first-best tax increases with the pollution stock whereas the subsidy decreases. Moreover, the tax is negative for low values of the pollution stock, i.e., for low values of the pollution stock, we obtain that the social valuation of the stock is lower than the private valuation. Furthermore, when a second-best policy is applied, the steady-state pollution stock is lower than the steady-state pollution stock associated with the efficient outcome.