Rapid shoreline retreat along the Esmeraldas coast, Ecuador: natural and man-induced processes

Along the coast facing the Pacific Ocean in the province of Esmeraldas (Ecuador) one can observe some stretches where a process of rapid erosion is currently in progress. If it is not prevented, it seriously risks compromising the development of any form of utilization. In this paper, which summarizes the observations carried out in three different periods (1989, 1992 and 1999), we express the opinion that this process is the product of two distinct main causes. Along the Atacames bay, which may be considered as the main seaside resort of Quito, the capital of Ecuador, progressive cliff retreat is not only very dangerous for the existing tourist settlements, but also hinders their further development. The shoreline dynamics that seems to be due only to ‘natural’ causes (sea level rising, or the lastEl Niño event) are so active that defence works are not recommended. At Camarones the erosion of the coast is clearly due to the systematic destruction of mangroves by man. Also as a result of the lastEl Niño event, the situation has become alarming and it could rapidly get worse. By means of the present contribution, the Authors intend to attract the attention of the international scientific community upon the processes, not surveyed so far, affecting the ‘weakest’ stretches of the Ecuadorian coast.     

Active biomonitoring of heavy metal pollution using Rosa rugosa plants

The purpose of this work was to evaluate the quality of a rural area near Faenza (Italy) by using an active biomonitoring approach, i.e., by placing homogeneous individuals of the perennial shrub Rosa rugosa in different sites throughout the area. Further sites, within the city or its environs, were used for comparison. Soil and leaves of R. rugosa were analyzed for their heavy metal content. The total heavy metal pattern of leaves closely paralleled the pattern registered in soil, with the highest content (both in total and assimilable forms) at the site in the urban area, which is exposed to heavy traffic. Pollen quality (abortiveness and viability) was also tested as a potential indicator of pollution. Pollen abortiveness was strictly related to Pb levels in leaves, while viability was inversely related to leaf Cr content. Our results suggest that R. rugosa has the potential to be a good biomonitoring system.     

Integrated Ambient and Microenvironment Model for Estimation of PM10 Exposures of Children in Annual and Episode Settings

Particulate matter air pollution is estimated to cause in the order of 350,000 excess deaths in the European Union calling for policy development and evaluation tools. In the current work, a model for PM₁₀ exposures of children is developed using microenvironment time activities and infiltration of ambient pollution indoors, both evaluated against observations earlier and integrated with city-wide air quality models in the current work. The model is demonstrated using data from two cities in Italy. High-end short-term exposures are characterized by an episode-day situation in Turin, and annual mean exposures in downtown Bologna. The air quality model was unable to capture the highest levels during the episode, and therefore, the exposure model was adjusted using observed–modeled ratio from a monitoring station. Air quality model performance for the annual levels was significantly better. Annual exposure variability within the target population was 1.5-fold in the downtown area Bologna and tenfold during the episode day in Turin.     

Spatial scales of variation in lichens: implications for sampling design in biomonitoring surveys

The variability of biological data is a main constraint affecting the quality and reliability of lichen biomonitoring surveys for estimation of the effects of atmospheric pollution. Although most epiphytic lichen bioindication surveys focus on between-site differences at the landscape level, associated with the large scale effects of atmospheric pollution, current protocols are based on multilevel sampling, thus adding further sources of variation and affecting the error budget. We test the hypothesis that assemblages of lichen communities vary at each spatial scale examined, in order to determine what scales should be included in future monitoring studies. We compared four sites in Italy, along gradients of atmospheric pollution and climate, to test the partitioning of the variance components of lichen diversity across spatial scales (from trunks to landscapes). Despite environmental heterogeneity, we observed comparable spatial variance. However, residuals often overcame between-plot variability, leading to biased estimation of atmospheric pollution effects.     

The assessment of particulate matter emitted from stone-crushing industry by correlating rock textures with particles generated after comminution and dispersed in air environment

The generation and emission of particulate matter from abrasion industry are subjects of the pollution monitoring by multidisciplinary study involving earth sciences and engineering disciplines. This work investigates the correlation between textural properties of in situ rock with class size distribution and morphology of particles generated after rock comminution and particles emitted in the air. A special comminution-dust sampling architecture was realised. The combined use of scanning electron microscopy and particle size analyser was considered in performing digital image analysis on both crushed products and airborne particles collected onto membrane filters. The results show that the size and morphology of crushed particles are linked to the petrographic rock properties. In particular, particles with fibrous morphology are prominent in rocks showing foliated textures where elongated minerals occurred, with implication for asbestos-bearing rocks. For what concerns the airborne particles, the results show that their aerodynamic diameters are independent of the crusher operating conditions. External parameters probably intervene in the distribution of the airborne particles emission, including the dynamic air fluxes, or environmental conditions. By applying mathematical models, the morphology and size range of airborne particles following the comminution processes can be predicted, and results has implication for pollutants contamination due to particulate matters emitted by crush stone industry.     

Acceptable Cancer Risks: Probabilities and Beyond

The acceptability of cancer risk requires consideration of factors that extend beyond mere numerical representations, such as either individual lifetime risk in excess of background and excess incidence. Recently, use of these numbers has been tempered by the addition of qualitative weights-of-evidence that describe the degree of support provided by animal and epidemiologic results. Nevertheless, many other factors, most of which are not quantitative, require incorporation but remain neglected by the analyst eager to use quantitative results.

In this paper we show that simple risk measures are often fraught with problems. Moreover, these measures do not incorporate the very essence of acceptability, which includes notions of responsibility, accountability, equity, and procedural legitimacy, among others. We link the process of risk assessment to those legal and regulatory standards that shape it. These standards are among the principal means to resolve risk-related disputes and to enhance the balancing of competing interests when science and law meet on uncertain and often conjectural ground.

We conclude the paper with a proposal for the portfolio approach to manage cancer risks and to deal with uncertain scientific information. This approach leads to the concept of "provisional acceptability," which reflects the choices available to the decisionmaker, and the trade-offs inherent to such choices.     

Use of a reactive transport model to describe reductive dechlorination (RD) as a remediation design tool: application at a CAH-contaminated site

In this paper, a numerical model is presented that is capable of describing the complex set of biochemical processes that occur in chlorinated aliphatic hydrocarbon (CAH)-contaminated groundwater when an exogenous electron donor is added. The reactive pattern is based on the degradation pathways of both chlorinated ethanes and ethenes, and it includes electron donor production (H₂ and acetate) from the fermentation of an organic substrate as well as rate-limiting processes related to electron acceptor competition. Coupling of the kinetic model to a convection–dispersion module is described. The calibration phase was carried out using data obtained at a real CAH-contaminated site in the north of Italy. Model simulations of different application scenarios are presented to draw general conclusions on the effectiveness of reductive dechlorination (RD) as a possible cleanup strategy. Early outcomes indicate that cleanup targets can only be achieved if source longevity is reduced. Therefore, metabolic RD is expected to produce beneficial effects because it is known to induce bioenhanced degradation and transformation of CAHs.     

Predicting dioxin-like PCBs soil contamination levels using milk of grazing animal as indicator

Dioxin-like PCBs (dl-PCBs) are ubiquitous persistent organic pollutants of recognized negative effects on human health. Assessing highly polluted areas should be an important public health issue. This study proposes to use the milk of grazing animals as a bioindicator of dl-PCB contamination in the environment. The hypothesis is that milk concentration of dl-PCBs are related to soil concentrations of these compounds, and that soils are generally reflective of a larger environmental issue of dl-PCB contamination. In this study, we evaluate the possibility of predicting soil concentrations using milk of sheep, cows and buffalos in a spatial model. For this purpose, samples of soil and milk collected in Campania (Italy) were introduced in a GIS platform to perform geostatistical analysis for building a simple predictive model. The ordinary least squares regressions (OLS) showed a statistically significant correlation (p < 0.05) between soil and milk contamination. However, this relationship was spatially variable. Thus, a geographically weighted regression (GWR) was performed, obtaining R² values of 0.91, 0.77 and 0.66 for sheep’s, buffalo’s and cow’s milk respectively. Assessed the mathematical relationships between the variables, new data was introduced to evaluate the performance of the model. Predictions of soil contamination with dl-PCBs using sheep’s, cow’s and buffalo’s milk showed a mean error of 23%, 25% and 36% respectively. According to these results the sheep’s milk can be considered the best bioindicator of dl-PCBs contamination among the three species. The results of this project evidence the potentialities of the proposed approach to assess bioindicator performance in a spatial predictive model.     

Environmental and lifestyle factors affect benzene uptake biomonitoring of residents near a petrochemical plant

Background

We monitored urinary benzene excretion to examine factors affecting benzene uptake in a sample of the general population living near a petrochemical plant.

Methods

Our study population included 143 subjects: 33 petrochemical plant workers (W) with low level occupational benzene exposure; 30 residents in a small town 2 km from the plant (2kmR); 26 residents in a second small town located 2 to 4 km from the plant (4kmR); and 54 urban residents 25 km from the plant (25kmR). Exposure to benzene was evaluated by personal air sampling during one work-shift for the W group, and from 8.00 to 20:00 for general population subgroups, and by urinary benzene (BEN-U).

Results

Median airborne benzene exposure was 25, 9, 7 and 6 μg/m³ benzene among the W, 2kmR, 4kmR, and 25kmR subgroups, respectively; the highest level was found among the workers, while there was no significant difference among the other groups. Median BEN-U was 2 to 14-fold higher in smokers compared to non-smokers; among non-smokers BEN-U was the highest in W (median 236 ng/L), and lower in the 2kmR (48 ng/L) and 4kmR (63 ng/L) subgroups than in the 25kmR (120 ng/L) subgroup. A multiple linear regression analysis, explaining up to 73% of BEN-U variability, confirmed that active smoking and airborne benzene most strongly affected BEN-U. Among the non-smoking, non-occupationally exposed study subjects, a positive association was found between BEN-U and the distance of residence from the plant. This association was explained by increased exposure to urban traffic emissions in the study group residing at a greater distance from the plant. Environmental tobacco smoke had a marginally positive role.

Conclusion

Among factors affecting benzene uptake in non-occupationally exposed individuals, urban residence contributes to benzene exposure more than residing in close proximity to a petrochemical plant.     

Urinary methyl tert-butyl ether and benzene as biomarkers of exposure to urban traffic

Methyl tert-butyl ether (MTBE) and benzene are added to gasoline to improve the combustion process and are found in the urban environment as a consequence of vehicular traffic. Herein we evaluate urinary MTBE (MTBE-U) and benzene (BEN-U) as biomarkers of exposure to urban traffic. Milan urban policemen (130 total) were investigated in May, July, October, and December for a total of 171 work shifts. Personal exposure to airborne benzene and carbon monoxide (CO), and atmospheric data, were measured during the work shift, while personal characteristics were collected by a questionnaire. A time/activity diary was completed by each subject during the work shift. Spot urine samples were obtained for the determination of MTBE-U and BEN-U. Median personal exposure to CO and airborne benzene were 3.3 mg/m(3) and 9.6 μg/m(3), respectively; median urinary levels in end-of-shift (ES) samples were 147 ng/L (MTBE-U) and 207 ng/L (BEN-U). The time spent on traffic duty at crossing was about 40% of work time. Multiple linear regression models, taking into account within-subject correlations, were applied to investigate the role of urban pollution, atmospheric conditions, job variables and personal characteristics on the level of biomarkers. MTBE-U was influenced by the month of sampling and positively correlated to the time spent in traffic guarding, CO exposure and atmospheric pressure, while negatively correlated to wind speed (R(2) for total model 0.63, P<0.001). BEN-U was influenced by the month and smoking habit, and positively correlated to urinary creatinine; moreover, an interaction between CO and smoking was found (R(2)=0.62, P<0.001). These results suggest that MTBE-U is a reliable marker for assessing urban traffic exposure, while BEN-U is determined mainly by personal characteristics.