Methodology in the epidemiological research of respiratory diseases and environmental pollution

There are complex and diverse methodological problems involved in the clinical and epidemiological study of respiratory diseases and their etiological factors. The association of urban growth, industrialization and environmental deterioration with respiratory diseases makes it necessary to pay more attention to this research area with a multidisciplinary approach. Appropriate study designs and statistical techniques to analyze and improve our understanding of the pathological events and their causes must be implemented to reduce the growing morbidity and mortality through better preventive actions and health programs. The objective of the article is to review the most common methodological problems in this research area and to present the most available statistical tools used.

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.

Environmental pollution promotes selection of microbial degradation pathways

Astonishing as it may seem, one organism's waste is often ideal food for another. Many waste products generated by human activities are routinely degraded by microorganisms under controlled conditions during waste-water treatment. Toxic pollutants resulting from inadvertent releases, such as oil spills, are also consumed by bacteria, the simplest organisms on Earth. Biodegradation of toxic or particularly persistent compounds, however, remains problematic. What has escaped the attention of many is that bacteria exposed to pollutants can adapt to them by mutating or acquiring degradative genes. These bacteria can proliferate in the environment as a result of the selection pressures created by pollutants. The positive outcome of selection pressure is that harmful compounds may eventually be broken down completely through biodegradation. The downside is that biodegradation may require extremely long periods of time. Although the adaptation process has been shown to be reproducible, it remains very difficult to predict.

Environomics - A Financial Estimate of Environmental Pollution Control and Abatement Schemes in Eloor-Edayar Industrial Belt

The present study consists of nine chapters including the introductory chapter. Chapter II makes a brief review of environmental literature and examines various measures adopted at the global level to protect the environment. The environmental problems often transgress national sovereignity and geographical boundaries. Therefore, attempts must be made at the national and international levels to protect the environment, the resources of which are the common property of mankind. The protection of the national environment from the ancient till the present forms the content of Chapter III. These chapters together provide a background to understand the issues analysed in the subsequent chapters. Carefully worked out theoretical framework is a pre-requisite for the successful study of a complex subject. Some of the theoretical issues of ‘environomics’ are examined in Chapter IV. The theoretical issues involved in estimating the costs and benefits of environmental protection constitute the theme of Chapter V. The state of environment in Eloor-Edayar Industrial belt andthe impact analysis of pollution of the area are discussed in Chapter VI and VII respectively. Chapter VIII makes the financial estimate of environmental protection of the project And finally, Chapter IX presents the findings of the study

Paper industry in Kerala: An evaluation of labour absorption,capacity utilisation, and environmental pollution

Paper industry is one of the oldest and largest industries in Kerala. Despite the developments in the industry in terms of growth in output , value added and employment generation, many of the units face grave problems. Irrespective of the size of the plant, the problems of the industry are general in nature. The problems are galore in the supply, not the demand side. Amomg the problems, the important ones are: raw material scarcity, energy deficiency and obsolete technology. Further, the industry is subject to many controls by the Government — price control, product control and raw materials control — which result in the dwindling of profits and investments. Equally important are the reservations against the industry for polluting the environment byeffluent disposal on the one hand and affecting ecological balance by depleting the existing forest on the other. Apart from the large, medium and small pulp and paper mills, there are about 30 hand made paper units in Kerala which can be categorised as village and cottage industry. Almost all of these units began at the initiative and support of Khadi and Village Industries Commission. The primary purpose of these units is employment generation, and not profit making. Currently many of these units are in the red and many others are on the verge of closure. Therefore, a separate analysis of the growth performance, and problems and prospects of the hand made paper industry has also been attempted. It is analysed separately because of the very small size of the hand made paper units

An Institutional Analysis of Environmental Pollution Disputes in Taiwan: Cases of 'Self-Relief'

During the late 1980s and early 1990s in Taiwan, people's protests against environmental pollution often took the form of "self-relief," meaning that they attempted to fight polluters using their own resources, without relying on legal or administrative procedures. Why did such an extreme form of disputes become so widespread? What institutional changes did these movements bring about? These questions are analyzed using the analytical framework of "law and economics." Our research shows that "self-relief" functioned to a certain extent as a means of realizing quick compensation for victims, and for reflecting the opinions of local people concerning development projects; in addition, it served to promote the formulation of law and administrative systems. However, as it was based on direct negotiations between the parties concerned, the outcome of each dispute only reflected the transient balance of forces, and the experience gained in negotiations was not accumulated as a social norm.

Management for a Variety of Environmental Pollution and North-South Trade

A simple static model incorporating a variety of environmental pollution is developed. An autarky model shows that a developing country regulates fewer types of pollution by income-induced environmental policy. As income grows, the types of regulated pollution increase and also introduced regulations become tougher.Then the model incorporates international trade between a developed country and a developing country. The model gives a new interpretation for the pollution haven hypothesis. Some types of pollution abated with inefficient technology are emitted more in a developing country but other types necessarily increase in a developed country in order to meet the trade balance.

ANN and Fuzzy c-Means applied to environmental pollution prediction

Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.

Environmental pollution control alternatives : drinking water treatment for small communities.

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