An interregional input-output analysis of the pollution content of trade flows and environmental trade balances between five states in the US Mid-West

In this paper we attempt an empirical application of the multi-region input-output (MRIO) method in order to enumerate the pollution content of interregional trade flows between five Mid-West regions/states in the US –Illinois, Indiana, Iowa, Michigan and Wisconsin – and the rest of the US. This allows us to analyse some very important issues in terms of the nature and significance of interregional environmental spillovers within the US Mid-West and the existence of pollution ‘trade balances’ between states. Our results raise questions in terms of the extent to which authorities at State level can control local emissions where they are limited in the way some emissions can be controlled, particularly with respect to changes in demand elsewhere in the Mid-West and US. This implies a need for policy co-ordination between national and state level authorities in the US to meet emissions reductions targets. The existence of an environmental trade balances between states also raises issues in terms of net losses/gains in terms of pollutants as a result of interregional trade within the US and whether, if certain activities can be carried out using less polluting technology in one region relative to others, it is better for the US as a whole if this type of relationship exists.

Using Effluent Charges in Promoting Investment in Water Pollution Control Technology: A Model of Coordination Failure among Firms

Untreated wastewater being directly discharged into rivers is a very harmful environmental hazard that needs to be tackled urgently in many countries. In order to safeguard the river ecosystem and reduce water pollution, it is important to have an effluent charge policy that promotes the investment of wastewater treatment technology by domestic firms. This paper considers the strategic interaction between the government and the domestic firms regarding the investment in the wastewater treatment technology and the design of optimal e­ffluent charge policy that should be implemented. In this model, the higher is the proportion of non-investing firms, the higher would be the probability of having to incur an e­ffluent charge and the higher would be that charge. On one hand the government needs to impose a sufficiently strict policy to ensure that firms have strong incentive to invest. On the other hand, it cannot be too strict that it drives out firms which cannot afford to invest in such expensive technology. The paper analyses the factors that affect the probability of investment in this technology. It also explains the difficulty of imposing a strict environment policy in countries that have too many small firms which cannot afford to invest unless subsidised.

Molecular biological approaches to the study of vectors in relation to malaria control

To a large extent, control of malaria vectors relies on the elimination of breeding sites and the application of chemical agents. There are increasing problems associated with the use of synthetic insecticides for vector control, including the evolution of resistance, the high cost of developing and registering new insecticides and an awareness of pollution from insecticide residues. These factors have stimulated interest in the application of molecular biology to the study of mosquito vectors of malaria; focussing primarily on two aspects. First, the improvement of existing control measures through the development of simplified DNA probe systems suitable for identification of vectors of malaria. The development of synthetic, non-radioactive DNA probes suitable for identification of species in the Anopheles gambiae complex is described with the aim of defining a simplified methodology wich is suitable for entomologist in the field. The second aspect to be considered is the development of completely novel strategies through the development of completely novel strategies through the genetic manipulation of insect vectors of malaria in order to alter their ability to transmit the disease. The major requirements for producing transgenic mosquitoes are outlined together with the progress wich has been made to date and discussed in relation to the prospects which this type of approach has for the future control of malaria.

The Use of Passive Samplers to Reveal Industrial and Agricultural Pollution Trends in Swiss Rivers

This study shows the efficiency of passive sampling to reveal industrial and agricultural pollution trends. Two practical applications for nonpolar and polar contaminants are presented. Low-density polyethylene (LDPE) samplers were deployed for one year in the Venoge River (VD) to monitor indicator PCBs (iPCBs, IUPAC nos. 28, 52, 101, 138, 153 and 180). The results showed that the impact of PCB emissions into the river is higher in summer than in other seasons due to the low flow rate of the river during this period. P,olar organic chemical integrative samplers (POCIS) were deployed for 4 months in the Sion-Riddes canal (VS) to investigate herbicides (terbuthylazine, diuron and linuron). Desisopropylatrazine-d5 (DIA-d5) was tested as a performance reference compound (PRC) to estimate aqueous concentration. The results showed an increase of water contamination due to the studied agricultural area. The maximal contamination was observed in April and corresponds to the period of herbicide application on the crops.

The problem of the competitiveness of nuclear energy: a biophysical explanation

In this study I try to explain the systemic problem of the low economic competitiveness of nuclear energy for the production of electricity by carrying out a biophysical analysis of its production process. Given the fact that neither econometric approaches nor onedimensional methods of energy analyses are effective, I introduce the concept of biophysical explanation as a quantitative analysis capable of handling the inherent ambiguity associated with the concept of energy. In particular, the quantities of energy, considered as relevant for the assessment, can only be measured and aggregated after having agreed on a pre-analytical definition of a grammar characterizing a given set of finite transformations. Using this grammar it becomes possible to provide a biophysical explanation for the low economic competitiveness of nuclear energy in the production of electricity. When comparing the various unit operations of the process of production of electricity with nuclear energy to the analogous unit operations of the process of production of fossil energy, we see that the various phases of the process are the same. The only difference is related to characteristics of the process associated with the generation of heat which are completely different in the two systems. Since the cost of production of fossil energy provides the base line of economic competitiveness of electricity, the (lack of) economic competitiveness of the production of electricity from nuclear energy can be studied, by comparing the biophysical costs associated with the different unit operations taking place in nuclear and fossil power plants when generating process heat or net electricity. In particular, the analysis focuses on fossil-fuel requirements and labor requirements for those phases that both nuclear plants and fossil energy plants have in common: (i) mining; (ii) refining/enriching; (iii) generating heat/electricity; (iv) handling the pollution/radioactive wastes. By adopting this approach, it becomes possible to explain the systemic low economic competitiveness of nuclear energy in the production of electricity, because of: (i) its dependence on oil, limiting its possible role as a carbon-free alternative; (ii) the choices made in relation to its fuel cycle, especially whether it includes reprocessing operations or not; (iii) the unavoidable uncertainty in the definition of the characteristics of its process; (iv) its large inertia (lack of flexibility) due to issues of time scale; and (v) its low power level.

Non-characteristic half-lives in radioactive decay

Half-lives of radionuclides span more than 50 orders of magnitude. We characterize the probability distribution of this broad-range data set at the same time that explore a method for fitting power-laws and testing goodness-of-fit. It is found that the procedure proposed recently by Clauset et al. [SIAM Rev. 51, 661 (2009)] does not perform well as it rejects the power-law hypothesis even for power-law synthetic data. In contrast, we establish the existence of a power-law exponent with a value around 1.1 for the half-life density, which can be explained by the sharp relationship between decay rate and released energy, for different disintegration types. For the case of alpha emission, this relationship constitutes an original mechanism of power-law generation.

Bioaccumulation of 210Pb and 210Po in fish tissues in a radioactive naturally enhanced area: the Peníscola marsh (Castelló, Spain)

210Pb and 210Po concentration in fish tissues from Peníscola marsh were analyzed, being this area a radioactive naturally enhanced marsh located in the East coast of Spain. Results showed that 210Po accumulation in tissues could reach values ranging from 28±8 Bq kg-1 in muscle of Cyprinus carpio, to 8558±6378 Bq kg-1 in gut content of Chelon labrosus. On the other hand, 210Pb concentrations ranged from 8±4 Bq kg-1 in muscle of Cyprinus carpio, to 475±481 Bq kg-1 in gut content of Chelon labrosus. Bioaccumulation pattern is generally 210Po&210Pb, except in spine, where more 210Pb than 210Po is accumulated. When comparing our samples to those collected as blanks, individuals from Peníscola marsh showed an enrichment in 210Po and 210Pb in their tissues compared to the blanks. Bioaccumulation factors showed that feeding is the major input route of 210Pb and 210Po into the fish body. Highest values of 210Pb and 210Po concentration in tissues were found on Chelon labrosus and Carassius auratus, being Cyprinus carpio the species with the lowest average values of 210Pb and 210Po accumulation.

Biophysical requirements of power-supply systems: nuclear energy and fossil energy

The report presents a grammar capable of analyzing the process of production of electricity in modular elements for different power-supply systems, defined using semantic and formal categories. In this way it becomes possible to individuate similarities and differences in the process of production of electricity, and then measure and compare “apples” with “apples” and “oranges” with “oranges”. For instance, when comparing the various unit operations of the process of production of electricity with nuclear energy to the analogous unit operations of the process of production of fossil energy, we see that the various phases of the process are the same. The only difference is related to characteristics of the process associated with the generation of heat which are completely different in the two systems. As a matter of facts, the performance of the production of electricity from nuclear energy can be studied, by comparing the biophysical costs associated with the different unit operations taking place in nuclear and fossil power plants when generating process heat or net electricity. By adopting this approach, it becomes possible to compare the performance of the two power-supply systems by comparing their relative biophysical requirements for the phases that both nuclear energy power plants and fossil energy power plants have in common: (i) mining; (ii) refining/enriching; (iii) generating heat/electricity; (iv) handling the pollution/radioactive wastes. This report presents the evaluation of the biophysical requirements for the two powersupply systems: nuclear energy and fossil energy. In particular, the report focuses on the following requirements: (i) electricity; (ii) fossil-fuels, (iii) labor; and (iv) materials.

Environmental pollution with soil-transmitted helminths in Sanliurfa, Turkey

Soil transmitted helminth (STH) infection are endemic in developing countries. A study was carried out of sewage farms, streams and vegetables to determine the sources and routes of STH infection in Sanliurfa, Turkey. Stool samples from farmhouse inhabitants as well as soil and vegetable samples from the gardens were collected and examined. In addition, water samples from streams and vegetable samples from the city market were collected and examined. One hundred and eighty-seven (59.5%) of a total of 314 samples, including 88.4% of the stool samples, 60.8% of the water samples, 84.4% of the soil samples and 14% of the vegetable samples, were found to be positive for STH eggs. These results indicate that the water, soil and vegetables are heavily contaminated, and suggest a vicious circle between humans and the environment. Improving environmental sanitation is imperative for the control of soil-transmitted helminthiasis in Sanliurfa.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

PHE-CRCE-010: Estimating Local Mortality Burdens associated with Particulate Air Pollution

The increase in mortality risk associated with long-term exposure to particulate air pollution is one of the most important, and best-characterised, effects of air pollution on health. This report presents estimates of the size of this effect on mortality in local authority areas in the UK, building upon the attributable fractions reported as an indicator in the public health outcomes framework for England. It discusses the concepts and assumptions underlying these calculations and gives information on how such estimates can be made. The estimates are expected to be useful to health and wellbeing boards when assessing local public health priorities, as well as to others working in the field of air quality and public health. The estimates of mortality burden are based on modelled annual average concentrations of fine particulate matter (PM2.5) in each local authority area originating from human activities. Local data on the adult population and adult mortality rates is also used. Central estimates of the fraction of mortality attributable to long-term exposure to current levels of anthropogenic (human-made) particulate air pollution range from around 2.5% in some local authorities in rural areas of Scotland and Northern Ireland and between 3 and 5% in Wales, to over 8% in some London boroughs. Because of uncertainty in the increase in mortality risk associated with ambient PM2.5, the actual burdens associated with these modelled concentrations could range from approximately one-sixth to about double these figures. Thus, current levels of particulate air pollution have a considerable impact on public health. Measures to reduce levels of particulate air pollution, or to reduce exposure of the population to such pollution, are regarded as an important public health initiative.