Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Design and Development of Fiber Optic Sensors for Trace Detection of Certain Environmental Pollutants

In recent years,photonics has emerged as an essential technology related to such diverse fields like laser technology,fiber optics,communication,optical signal processing,computing,entertainment,consumer electronics etc.Availabilities of semiconductor lasers and low loss fibers have also revolutionized the field of sensor technology including telemetry. There exist fiber optic sensors which are sensitive,reliable.light weight and accurate devices which find applications in wide range of areas like biomedicine,aviation,surgery,pollution monitoring etc.,apart from areas in basic sciences.The present thesis deals with the design,fabrication and characterization of a variety of cost effective and sensitive fiber optic sensors for the trace detetction of certain environment pollutants in air and water.The sensor design is carried out using the techniques like evanescent waves,micro bending and long period gratings.

Studies on air pollution meteorology with special reference to Madras city

The main aim of the study is to give a clear picture of various meteorological factors affecting the dispersal of pollutants. One such important developing metropolis, namely Madras, is chosen for the present study. The study throws light into the occurrence of inversions, isothermals and lapse conditions and the vertical and horizontal extent of mixing of pollutants. The thesis also aims to study the wind climatology and atmospheric stability .The study gives a insight to the spatial distribution of sulphudioxide concentration using the Gaussian plume model, which accounts for various industrial sources. The researcher suggests optimum locations for industries and various steps to reduce air pollution.

Studies on the meteriological aspects of air pollution over Cochin

Pollutants that once enter into the earth’s atmosphere become part of the atmosphere and hence their dispersion, dilution, direction of transportation etc. are governed by the meteorological conditions. The thesis deals with the study of the atmospheric dispersion capacity, wind climatology, atmospheric stability, pollutant distribution by means of a model and the suggestions for a comprehensive planning for the industrially developing city, Cochin. The definition, sources, types and effects of air pollution have been dealt with briefly. The influence of various meteorological parameters such as vector wind, temperature and its vertical structure and atmospheric stability in relation to pollutant dispersal have been studied. The importance of inversions, mixing heights, ventilation coefficients were brought out. The spatial variation of mixing heights studies for the first time on a microscale region, serves to delineate the regions of good and poor dispersal capacity. A study of wind direction fluctuation, σθ and its relation to stability and mixing heights were shown to be much useful. It was shown that there is a necessity to look into the method of σθ computation. The development of Gausssian Plume Model along with the application for multiple sources was presented. The pollutant chosen was sulphur dioxide and industrial sources alone were considered. The percentage frequency of occurrence of inversions and isothermals are found to be low in all months during the year. The spatial variation of mixing heights revealed that a single mixing height cannot be taken as a representative for the whole city have low mixing heights and monsoonal months showed lowest mixing heights. The study of ventilation co-efficients showed values less than the required optimum value 6000m2/5. However, the low values may be due to the consideration of surface wind alone instead of the vertically averaged wind. Relatively more calm conditions and light winds during night and strong winds during day time were observed. During the most of the year westerlies during day time and northeasterlies during night time are the dominant winds. Unstable conditions with high values of σθ during day time and stable conditions with lower values of σθ during night time are the prominent features. Monsoonal months showed neutral stability for most of the time. A study σθ of and Pasquill Stability category has revealed the difficulty in giving a unique value of for each stability category. For the first time regression equations have been developed relating mixing heights and σθ. A closer examination of σθ revealed that half of the range of wind direction fluctuations is to be taken, instead of one by sixth, to compute σθ. The spatial distribution of SO2 showed a more or less uniform distribution with a slight intrusion towards south. Winter months showed low concentrations contrary to the expectations. The variations of the concentration is found to be influenced more by the mixing height and the stack height rather than wind speed. In the densely populated areas the concentration is more than the threshold limit value. However, the values reported appear to be high, because no depletion of the material is assumed through dry or wet depositions and also because of the inclusion of calm conditions with a very light wind speed. A reduction of emission during night time with a consequent rise during day time would bring down the levels of pollution. The probable locations for the new industries could be the extreme southeast parts because the concentration towards the north falls off very quickly resulting low concentrations. In such a case pollutant spread would be towards south and west, thus keeping the city interior relatively free from pollution. A more detailed examination of the pollutant spread by means of models that would take the dry and wet depositions may be necessary. Nevertheless, the present model serves to give the trend of the distribution of pollutant concentration with which one can suggest the optimum locations for the new industries

Studis on the climatological aspects of air pollution potential over trivandrum

The deteriorating air quality especially in urban environments is a cause of serious concern. In spite of being an effective sink, the atmosphere also has its own limitations in effectively dispersing the pollutants being dumped into it continuously by various sources, mainly industries. Many a time, it is not the higher emissions that cause alarming level of pollutants but the unfavourable atmospheric conditions under which the atmosphere is not able to disperse them effectively, leading to accumulation of pollutants near the ground. Hence, it is imperative to have an estimate of the atmospheric potential for dispersal of the substances emitted into it. This requires a knowledge of mixing height, ventilation coefficient, wind and stability of the region under study. Mere estimation of such pollution potential is not adequate, unless the probable distribution of concentration of pollutants is known. This can be obtained by means of mathematical models. The pollution potential coupled with the distribution of concentration provides a good basis for initiating steps to mitigate air pollution in any developing urban area. In this thesis, a fast developing industrial city, namely, Trivandrum is chosen for estimating the pollution potential and determining the spatial distribution of sulphur dioxide concentration. Each of the parameters required for pollution potential is discussed in detail separately. The thesis is divided into nine chapters.

Sono, Photo and Sonophoto Catalytic Removal of Chemical and Bacterial Pollutants from Wastewater

The term ‘water pollution’ broadly refers to the contamination of water and water bodies (e.g. lakes, rivers, oceans, groundwater etc). Water pollution occurs when pollutants are discharged directly or indirectly into water bodies without adequate treatment to remove the harmful contaminants. This affects not only the plants and organisms living in these bodies of water but also the entire natural biological communities and the biodiversity.Advanced Oxidation Processes (AOPs) have been tested as environment-friendly techniques for the treatment of contaminated water, in view of their ability to convert pollutants into harmless end products. These techniques refer to a set of treatment procedures designed to remove organic or inorganic contaminants in wastewater by oxidation. The contaminants are oxidized by different reagents such as air, oxygen, ozone, and hydrogen peroxide which are introduced in precise, preprogrammed dosages, sequences and combinations under appropriate conditions. The procedure when combined with light in presence of catalyst is known as photocatalysis. When ultrasound (US) is used as the energy source, the process is referred as sonication. Sonication in presence of catalyst is referred as sonocatalysis. Of late, combination of light and sound as energy sources has been tested for the decontamination of wastewater in the presence of suitable catalyst. In this case, the process is referred as sonophotocatalysis. These AOPs are specially advantageous in pollution control and waste water treatment because unlike many other technologies, they do not just transfer the pollutant from one phase to another but completely degrade them into innocuous substances such as CO2 and H2O.