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Arsenic in the Water

Research . A team of four SSES (Spatial Statistics and Environmental Sciences ) researchers from OSU among them Catherine Calder and Noel Cressie and three researchers from Battelle Memorial Institute was awarded a three-year (2004-2007) contract funded by the American Chemistry Council's (ACC) Long-Range Research Initiative for the research project titled "From Sources to Biomarkers: A Hierarchical Bayesian Approach for Human Exposure Modeling". The objective of this research is to characteri19

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Arsenic in the Water

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    1. Arsenic in the Water by Claude Davila Advisors: Kate Calder Noel Cressie Hong Fei Li

    2. Research A team of four SSES (Spatial Statistics and Environmental Sciences ) researchers from OSU among them Catherine Calder and Noel Cressie and three researchers from Battelle Memorial Institute was awarded a three-year (2004-2007) contract funded by the American Chemistry Council's (ACC) Long-Range Research Initiative for the research project titled "From Sources to Biomarkers: A Hierarchical Bayesian Approach for Human Exposure Modeling". The objective of this research is to characterize multi-pollutant (arsenic, lead, cadmium, and chromium) human exposures by linking sources to biomarkers using a multi-scale hierarchical Bayesian statistical model that describes how multi-media pathways contribute to direct routes of exposure (inhalation, ingestion, dermal). This is under the hypothesis that by incorporating several different sources of data that inform about pollutant pathways, the model will discern patterns in human exposures and allow more informed conclusions to be drawn about current and future distributions of biomarkers. Talk about your experience at Battelle. Kate and Noel invited me to the a meeting at Battelle to see the research team in action. It was quite an experience for an undergraduate to see what the important of teamwork is all about. for research slide Talk about your experience at Battelle. Kate and Noel invited me to the a meeting at Battelle to see the research team in action. It was quite an experience for an undergraduate to see what the important of teamwork is all about. for research slide

    3. Introduction: Arsenic Arsenic occurs naturally in rocks and soil, water, air, and plants and animals. It can be further released into the environment through natural activities such as volcanic action, erosion of rocks and forest fires, or through human actions. Anthropogenic Sources High arsenic levels can also come from certain fertilizers and animal feeding operations. Industry practices such as copper smelting, mining and coal burning also contribute to arsenic in our environment. First I shall provide you with a background of arsenic before I explain what my REU project is about.First I shall provide you with a background of arsenic before I explain what my REU project is about.

    4. Arsenic Large number of arsenic-containing chemical compounds are present in the terrestrial environment: they include the inorganic species arsenate, or As (V), and arsenite, or As (III), in addition to organic derivatives. The inorganic species are the more toxic ones. The arsenic species present in groundwater and surface water are largely arsenate and arsenite.

    5. Groundwater and Surface water Surface water is the water in the oceans, streams, lakes and rivers. Groundwater is the underground water that gets tapped when a well gets dug for drinking water. When it rains or if water is poured on the ground it will travel downward because of gravity. It gets filtered by the soil but at the same time it collects certain minerals or metals such as arsenic. It may be released as a spring, drain into a lake or river, travel to the ocean underground or get pumped up from a well into somebody’s kitchen sink.

    6. How does Arsenic get into the ground water, surface water and drinking water? Drinking water can come from either ground water sources (via wells) or surface water sources (such as rivers, lakes, and streams). Nationally, most water systems use a ground water source (80%), but most people (66%) are served by a water system that uses surface water. Ground water that is in contact with the rocks with high concentration in arsenic can have high levels of arsenic.

    7. Chemistry behind Arsenic getting into the Water Arsenic needs to be in a soluble form to end up in drinking water. If there is a reduction of As (V) to As (III), As (III) will be more mobile hence it will end up in water. If a certain form of arsenic is present in rock (perhaps as waste rock from a mining site) it can get attached to Oxygen and turn into the mobile form As (III) and end up in the water.

    8. Health Effects Short term exposure (high concentration in short amount of time) Vomiting Throat and stomach pain Bloody diarrhea Long term exposure (low concentration over long period of time) Circulatory problems (trouble with blood vessels and circulation) High blood pressure Cancer

    9. Details of this study The object of this REU project is to use geostatistics to analyze data from public water systems in Arizona. The data was obtained from Water Quality Division, Arizona Department of Environmental Quality. It originally included the information of the PWS, the arsenic concentration of each PWS and the counties served. Since exact locations of each PWS has not been provided the location of each PWS from the county that it serves has been randomly generated. Data that was provided -Id: Id number of the public water system -Sys.source: source of the drinking water -x: longitude -y: latitude -arsenic: log concentration of arsenic Slide 9: Mention that you used the log concentration of arsenic in order to make the data look more normal. X and y give location of a public water system in Arizona. Slide 9: Mention that you used the log concentration of arsenic in order to make the data look more normal. X and y give location of a public water system in Arizona.

    10. Histogram Histograms summarize the distribution of data Horizontal axis is the log concentration of arsenic in drinking water Vertical axis is for the frequency of counts in each bin Here you can see that there is a higher frequency of -5 arsenic in drinking water. Here you can see that there is a higher frequency of -5 arsenic in drinking water.

    11. Exploratory Analysis: Map of Arizona This is a map of the data locations. There are circles of different sizes indicating different levels of arsenic concentration. The different colors of the circles indicate four different source types: GW-groundwater GWP-groundwater primary SW-surface water SWP-surface water primary This is a slide that shows how the data has been fitting into a map of the state of Arizona. Difference between ground water and groundwater primary is that groundwater is a mixture of surface water and ground water but primary there is more groundwater. The difference between surface water and surface water primary is that there is also a mixture of surface water and ground water but there is more surface water present. This is a slide that shows how the data has been fitting into a map of the state of Arizona. Difference between ground water and groundwater primary is that groundwater is a mixture of surface water and ground water but primary there is more groundwater. The difference between surface water and surface water primary is that there is also a mixture of surface water and ground water but there is more surface water present.

    12. Plot of Sys.Source v Arsenic Here is a picture of a box plot. It compares the different levels of arsenic in the 4 sources of drinking water (GW, GWP, SW, SWP).U is for unknown. In GW the concentration levels of arsenic vary anywhere from -7to -1. The width of the box is arbitrary for this box plot. The median (the bold vertical line in the middle of the box) is value of the point which has half the data smaller than that point and half the data larger than that point. The box is around the median and it represents the middle 50 percent of the data. The line below the box is 25 percent of the data (lower quartile) , the line above the box is 75 percent of the data (upper quartile).Here is a picture of a box plot. It compares the different levels of arsenic in the 4 sources of drinking water (GW, GWP, SW, SWP).U is for unknown. In GW the concentration levels of arsenic vary anywhere from -7to -1. The width of the box is arbitrary for this box plot. The median (the bold vertical line in the middle of the box) is value of the point which has half the data smaller than that point and half the data larger than that point. The box is around the median and it represents the middle 50 percent of the data. The line below the box is 25 percent of the data (lower quartile) , the line above the box is 75 percent of the data (upper quartile).

    13. Exploratory Analysis: Contour Plot Arsenic is plotted against longitude (x) and latitude(y). You can see how arsenic levels change according to the location. On the right I have a closeup of an area of the graph on the left. Here you can see the distribution of arsenic levels along the x and y axis. Arsenic is plotted against longitude (x) and latitude(y). You can see how arsenic levels change according to the location. On the right I have a closeup of an area of the graph on the left. Here you can see the distribution of arsenic levels along the x and y axis.

    14. Background: Geostatistics A collection of statistical methods which are used in the geosciences Used for estimating/predicting the value of continuous spatial process at unobserved locations given observations at known locations Kriging is a method used to perform spatial prediction (to be explained later on). In order to analyze the Public water system data I used statistical method known as kriging that comes from a branch of statistics known as geostatistics.In order to analyze the Public water system data I used statistical method known as kriging that comes from a branch of statistics known as geostatistics.

    15. Variogram Analysis Consists of an experimental variogram (eg. Empirical variogram) calculated from the data and variogram model fitted to the data. Spatial dependence - measurements at points close together are more similar than those further apart. Variogram tells you whether data exhibit spatial dependence. Nugget effect is when a variogram, as distance goes to 0, does not approach zero variance. The amount by which the variance differs from zero is known as the nugget effect. Before I tell you what a variogram is it First of all it is important to understand the meaning of spatial dependence The discontinuity of the variogram at the origin is the nugget effect. Before I tell you what a variogram is it First of all it is important to understand the meaning of spatial dependence The discontinuity of the variogram at the origin is the nugget effect.

    16. Variogram Analysis: Variogram The variogram is defined by: The difference between specific locations is known equal to h. y thing is a gamma. The difference between specific locations is known equal to h. y thing is a gamma.

    17. Variogram Analysis: Semi-Variogram The function that is used in kriging is the semi-variogram which is the variogram equation divided by 2. Apparently semi-variogram is also know as variogram. Later on you will see what kriging is all about.Apparently semi-variogram is also know as variogram. Later on you will see what kriging is all about.

    18. Variogram Analysis: Exploratory Plots Empirical Variograms- nonparametric estimators of the variogram of a spatial process When performing a variogram analysis one uses certain exploratory plots. I have used a robust empirical variogram. After one has the exploratory plot done one then has to model the variogram. An outlier is a data point that comes from a distribution different (in location, scale, or distributional form) from the bulk of the data or faulty observations. When performing a variogram analysis one uses certain exploratory plots. I have used a robust empirical variogram. After one has the exploratory plot done one then has to model the variogram. An outlier is a data point that comes from a distribution different (in location, scale, or distributional form) from the bulk of the data or faulty observations.

    19. Variogram Analysis: Variogram Exponential Model Exponential Variogram Model: when combined with nugget effect it is used for an experimental variogram that levels out but has curve all the way up. Here there is a a discontinuity at the origin. The length of the discontinuity is the nugget effect so from origin to the part where the c(0) starts. Here there is a a discontinuity at the origin. The length of the discontinuity is the nugget effect so from origin to the part where the c(0) starts.

    20. Variogram Analysis: Empirical Variogram-Robust This is the plot of the variogram (robust empirical variogram). The mean squared difference is plotted against the magnitude/length of h. The dots are the robust empirical variogram which are fitted to an exponential model estimated from the observed data and now this information can be used for kriging. This semi-variogram is the one that will be used for kriging. This is the plot of the variogram (robust empirical variogram). The mean squared difference is plotted against the magnitude/length of h. The dots are the robust empirical variogram which are fitted to an exponential model estimated from the observed data and now this information can be used for kriging. This semi-variogram is the one that will be used for kriging.

    21. Spatial Prediction: Kriging Kriging : uses the information from a variogram to find an optimal set of weights that are used in estimating a surface at unsampled locations. Kriging is named after D.G. Krige, a South African mining engineer and a pioneer in the application of statistical techniques to mining investigations.

    22. Grid of Data and Prediction Locations

    23. The black dots are location of the water systems. The areas around the dots are the predicted values of arsenic. The darker the color the higher the concentration level. The plot of the kriging standard errors shows the levels of uncertainty from the predictions made. The black dots are location of the water systems. The areas around the dots are the predicted values of arsenic. The darker the color the higher the concentration level. The plot of the kriging standard errors shows the levels of uncertainty from the predictions made.

    24. Conclusion Groundwater seems to be a common water source because most of the data collected is from groundwater because there is not much surface water in Arizona. Higher levels of arsenic concentration are in the groundwater. According to the kriging estimates, log arsenic levels of approx.-5 are quite abundant throughout Arizona. EPA Guideline is 0.010 ppm (this includes both organic and inorganic arsenic) Arizona itself is lots of desert so that is why groundwater is a common water source.Arizona itself is lots of desert so that is why groundwater is a common water source.

    25. Sources Calder A., Catherine and Cressie, Noel (2006) Kriging and Variogram Models. Ohio: Ohio State University Websites http://www.ento.vt.edu/~sharov/PopEcol/lec2/geostat.html http://www.itl.nist.gov/div898/handbook/glossary.htm#K http://www.bioss.sari.ac.uk/smart/unix/mvariog/slides/frames.htm http://www.goldensoftware.com/variogramTutorial.pdf#search=%22variogram%22 http://www.u.arizona.edu/~donaldm/homepage/glossary.html http://www.statios.com/Resources/04-variogram.pdf#search=%22variogram%20nugget%22 http://www.umeciv.maine.edu/MacRae/Arsenic%20Main.htm

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