Automatic Decision-Oriented Mapping of Pollution Data

The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

Bioreporters and biosensors for arsenic detection. Biotechnological solutions for a world-wide pollution problem.

A wide variety of whole cell bioreporter and biosensor assays for arsenic detection has been developed over the past decade. The assays permit flexible detection instrumentation while maintaining excellent method of detection limits in the environmentally relevant range of 10-50 μg arsenite per L and below. New emerging trends focus on genetic rewiring of reporter cells and/or integration into microdevices for more optimal detection. A number of case studies have shown realistic field applicability of bioreporter assays.

A Monte Carlo approach to the inverse problem of diffuse pollution risk in agricultural catchments

The hydrological and biogeochemical processes that operate in catchments influence the ecological quality of freshwater systems through delivery of fine sediment, nutrients and organic matter. Most models that seek to characterise the delivery of diffuse pollutants from land to water are reductionist. The multitude of processes that are parameterised in such models to ensure generic applicability make them complex and difficult to test on available data. Here, we outline an alternative - data-driven - inverse approach. We apply SCIMAP, a parsimonious risk based model that has an explicit treatment of hydrological connectivity. we take a Bayesian approach to the inverse problem of determining the risk that must be assigned to different land uses in a catchment in order to explain the spatial patterns of measured in-stream nutrient concentrations. We apply the model to identify the key sources of nitrogen (N) and phosphorus (P) diffuse pollution risk in eleven UK catchments covering a range of landscapes. The model results show that: 1) some land use generates a consistently high or low risk of diffuse nutrient pollution; but 2) the risks associated with different land uses vary both between catchments and between nutrients; and 3) that the dominant sources of P and N risk in the catchment are often a function of the spatial configuration of land uses. Taken on a case-by-case basis, this type of inverse approach may be used to help prioritise the focus of interventions to reduce diffuse pollution risk for freshwater ecosystems. (C) 2012 Elsevier B.V. All rights reserved.

Effects of the 80 km/h and variable speed limits on air pollution in the metropolitan area of Barcelona

In 2008 the regional government of Catalonia (Spain) reduced the maximum speed limit on several stretches of congested urban motorway in the Barcelona metropolitan area to 80 km/h, while in 2009 it introduced a variable speed system on other stretches of its metropolitan motorways. We use the differences-in-differences method, which enables a policy impact to be measured under specific conditions, to assess the impact of these policies on emissions of NOx and PM10. Empirical estimation indicate that reducing the speed limit to 80 km h-1 causes a 1.7 to 3.2% increase in NOx and 5.3 to 5.9% in PM10. By contrast, the variable speed policy reduced NOx and PM10 pollution by 7.7 to 17.1% and 14.5 to 17.3%. As such, a variable speed policy appears to be a more effective environmental policy than reducing the speed limit to a maximum of 80 km/h.

The Andean Biotic Index (ABI): revised tolerance to pollution values for macroinvertebrate families and index performance evaluation.

Score-based biotic indices are widely used to evaluate the water quality of streams and rivers. Few adaptations of these indices have been done for South America because there is a lack of knowledge on mac-roinvertebrate taxonomy, distribution and tolerance to pollution in the region. Several areas in the Andes are densely populated and there is need for methods to assess the impact of increasing human pressures on aquatic ecosystems. Considering the unique ecological and geographical features of the Andes, macroinvertebrate indices used in other regions must be adapted with caution. Here we present a review of the literature on mac-roinvertebrate distribution and tolerance to pollution in Andean areas above 2 000masl. Using these data, we propose an Andean Biotic Index (ABI), which is based on the BMWP index. In general, ABI includes fewer macroinvertebrate families than in other regions of the world where the BMWP index has been applied because altitude restricts the distribution of several families. Our review shows that in the high Andes, the tolerance of several macroinvertebrate families to pollution differs from those reported in other areas. We tested the ABI index in two basins in Ecuador and Peru, and compared it to other BMWP adaptations using the reference condi-tion approach. The ABI index is extremely useful for detecting the general impairment of rivers but class quality boundaries should be defined independently for each basin because reference conditions may be different. The ABI is widely used in Ecuador and Peru, with high correlations with land-use pressures in several studies. The ABI index is an integral part of the new multimetric index designed for high Andean streams (IMEERA). Rev. Biol. Trop. 62 (Suppl. 2): 249-273. Epub 2014 April 01.

Case-Crossover Analysis of Air Pollution Health Effects: A Systematic Review of Methodology and Application

Case-crossover is one of the most used designs for analyzing the health-related effects of air pollution. Nevertheless, no one has reviewed its application and methodology in this context. Objective: We conducted a systematic review of case-crossover (CCO) designs used to study the relationship between air pollution and morbidity and mortality, from the standpoint of methodology and application.Data sources and extraction: A search was made of the MEDLINE and EMBASE databases.Reports were classified as methodologic or applied. From the latter, the following information was extracted: author, study location, year, type of population (general or patients), dependent variable(s), independent variable(s), type of CCO design, and whether effect modification was analyzed for variables at the individual level. Data synthesis: The review covered 105 reports that fulfilled the inclusion criteria. Of these, 24 addressed methodological aspects, and the remainder involved the design’s application. In the methodological reports, the designs that yielded the best results in simulation were symmetric bidirectional CCO and time-stratified CCO. Furthermore, we observed an increase across time in the use of certain CCO designs, mainly symmetric bidirectional and time-stratified CCO. The dependent variables most frequently analyzed were those relating to hospital morbidity; the pollutants most often studied were those linked to particulate matter. Among the CCO-application reports, 13.6% studied effect modification for variables at the individual level.Conclusions: The use of CCO designs has undergone considerable growth; the most widely used designs were those that yielded better results in simulation studies: symmetric bidirectional and time-stratified CCO. However, the advantages of CCO as a method of analysis of variables at the individual level are put to little use

Association between Long-Term Exposure to Traffic-Related Air Pollution and Subclinical Atherosclerosis: The REGICOR Study

Background: Epidemiological evidence of the effects of long-term exposure to air pollu tion on the chronic processes of athero genesis is limited. Objective: We investigated the association of long-term exposure to traffic-related air pollu tion with subclinical atherosclerosis, measured by carotid intima media thickness (IMT) and ankle–brachial index (ABI). Methods: We performed a cross-sectional analysis using data collected during the reexamination (2007–2010) of 2,780 participants in the REGICOR (Registre Gironí del Cor: the Gerona Heart Register) study, a population-based prospective cohort in Girona, Spain. Long-term exposure across residences was calculated as the last 10 years’ time-weighted average of residential nitrogen dioxide (NO2) estimates (based on a local-scale land-use regression model), traffic intensity in the nearest street, and traffic intensity in a 100 m buffer. Associations with IMT and ABI were estimated using linear regression and multinomial logistic regression, respectively, controlling for sex, age, smoking status, education, marital status, and several other potential confounders or intermediates. Results: Exposure contrasts between the 5th and 95th percentiles for NO2 (25 μg/m), traffic intensity in the nearest street (15,000 vehicles/day), and traffic load within 100 m (7,200,000 vehicle-m/day) were associated with differences of 0.56% (95% CI: –1.5, 2.6%), 2.32% (95% CI: 0.48, 4.17%), and 1.91% (95% CI: –0.24, 4.06) percent difference in IMT, respectively. Exposures were positively associated with an ABI of > 1.3, but not an ABI of < 0.9. Stronger associations were observed among those with a high level of education and in men ≥ 60 years of age. Conclusions: Long-term traffic-related exposures were associated with subclinical markers of atherosclerosis. Prospective studies are needed to confirm associations and further examine differences among population subgroups.key words: ankle–brachial index, average daily traffic, cardiovascular disease, exposure assessment, exposure to tailpipe emissions, intima media thickness, land use regression model, Mediterranean diet, nitrogen dioxide

Effects of the sewage pollution in the structure and dynamics of the community of Cystoseira mediterranea (Fucales, Phaeophyceae)

We performed a study on the specific composition, structure, and dynamics of two Cystoseira mediterranea communities from the north-western Mediterranean submitted to different degrees of pollution. The structural complexity (species richness, specific distribution, and species and pattern diversity) and biomass production were lower in the polluted site. In this station, opportunistic algae (mainly Ulva rigida) loomed, and Mesophyllum lichenoides and some encrusting brown algae increased their cover. Other species (Jania rubens, and some Ceramiales) decreased their abundance when compared with the polluted site

Air pollution and emergency admissions for cardiorespiratory diseases in Lisbon (Portugal)

Daily records of hospital admissions due to cardiorespiratory diseases and levels of PM10, SO2, CO, NO, NO2, and O3 were collected from 1999-2004 to evaluate the relationship between air pollution and morbidity in Lisbon. Generalised additive Poisson regression models were adopted, controlling for temperature, humidity, and both short and long-term seasonality. Significant positive associations, lagged by 1 or 2 days, were found between markers of traffic-related pollution (CO and NO2) and cardiocirculatory diseases in all age groups. Increased childhood emergency admissions for respiratory illness were significantly correlated with the 1-day lagged SO2 levels coming from industrial activities.

Pollution trends using bark of morus alba in the cities of buenos aires and mendoza (Argentina)

A comparative study of elements deposited on tree bark was carried out for urban and periurban areas of two of the most important cities in Argentina. The content of Fe, Mg, Al, Mn, Zn, Pb, Ba, Cr, Hg, Cu, Ni, Cd and Sb was determined by inductively coupled plasma atomic emission spectrometry (ICP-OES) in Morus alba tree bark collected in the cities of Buenos Aires and Mendoza. The main air pollutants detected in the Buenos Aires urban area were Ba, Cr, Cu and Ni and indicate significative difference from the Mendoza urban and periurban areas. Significantly, higher concentrations of Zn, Ba, Cr and Cu were recorded in the periurban area of the city of Buenos Aires than in Mendoza. Bark samples were strongly influenced by dust and show Al, Fe, Mg and other element accumulations that indicate that soil particles were carried out by wind. Elements like Ba and Zn, commonly linked to traffic emissions, showed the highest concentrations in the Buenos Aires metropolitan area, possibly due to more intensive vehicular traffic. Our results indicated that intensity of vehicular traffic and not city structure is responsible for air pollution.