Pollutant Diffusion  in Loxahatchee Inlet
                 (Influence of Physical Environment on Pollutant Concentration with GIS)

MingYo Chung


    Until recently, emphasis by environmental engineers and decision makers

had been directed toward the treatment of traditional point source

pollution. Billions of dollars were spent in the United States on the

point source pollutant cleanup mandated by the earlier version of the

Clean Water Act (1972, 1977). As a result of these policies, marked

improvements of water quality of some bodies of water were noticed such

as the River Thames in London, and Potomac River at Washington, D.C.

However, Wolman (1988) focused on the point source abatement has only

maintained more or less a status quo in the majority of water quality

monitoring stations throughout the United States. It has to be pointed

out, that most of the monitoring stations operated by the U.S.

Geological Survey may not be located in places where the most profound

 water quality changes have occurred. Hence the recent experience of

 emphasis on the point source abatement indicates that focusing on one

type of pollution may not be efficient and that an integrated approach

 that would address both point and non point sources is needed.

The elimination or reduction of pollution sources may require excessive

expenses. Furthermore, many diffuse (non point) sources cannot be

regulated and enforcement of control is not feasible. Therefore, the

integrated solutions or management plan should address the magnitude of

the water pollutant sources. This Loxahatchee Inlet data shows both

point and non point source pollution, and this study focused on

visualizing pollutant concentration with surrounding environment

throughout Loxahatchee Inlet.


Three fundamental purposes are involved in this study.

            1). Find spatial relationship between pollutants concentration and

                    main boat path, depth, bottom type
            2). Try to explain the pattern of pollutants concentration in terms of

                    other features of the inlet
            3). Help to developing integrated management modeling and


Data Description

            Loxahatchee Data include:
            Shorelines: determine the study area defined (polygon)
            Depth: shows entire depth (ft) in the Loxahatchee Inlet (polygon)
            Sample station with pollutants concentration: represent concentration of
            each point (ppm) ? (point)
            Bottom type: shows fine different bottom type in the Loxahatchee Inlet
            Main boat path: heavy boat traffic (line)
            Summerhouses location: point source pollution (point)



Quadrat Analysis:

                   Defining spatial randomness of the sample station of entire inlet is

            important to fairness of the study. I create quadrat coverage with

            800 ft, this quadrat shows number of points per 64,000 square ft. Based on

            this quadrat, I could calculate the spatial randomness of the Loxahatchee Inlet

         Arc: create quad1
            Arc: ae
            Arcedit: disp 9999
            Arcedit: ec quad1
            Arcedit: backc pollutant 3
            Arcedit: backc point
            Arcedit: mape point
            Arcedit: draw
            Arcedit: &r/home/ssa10/gridder
            Arcedit: save
            Arcedit: q
            Arc: clean quad1

            - 800 ft is a empirical number.


Linear regression:

                  Using linear regression, I found correlation between pollutant

            concentration and pollutant sources. Acr/Info doesn't recognize shp

            files, but this Loxahatchee data only has shp-file coverage. Therefore,

            I have to be converted into ARC coverages.

         Arc: shapearc pollutants pollutants
            Arc: build pollutants point
            Arc: shapearc summerhouses summerhouses
            Arc: build shouses point
            Arc: shapearc main path main path
            Arc: build main path line
            Arc: addxy pollutants
            Arc: addxy summerhouses

            After this procedure, I calculate correlation between concentration

            levels and pollutant sources. Therefore, I need to find the distance

            between concentration levels and pollutant sources.

         Arc: near pollutants main path line 5000
            Arc: near pollutants summerhouses point 5000

            - This will establish the distance from every point in the pollutants
            coverage to the main path and summerhouses coverage and add that distance
            to the attribute table

X - gobi

                This program is one Arcview's extension pack. This program produce to

            the dynamic changing of symbols or colors in one plot which

            simultaneously change corresponding points in other plots or images in

            Arcview program. Therefore, I will use this for visualizing pollutants

            concentration levels and pollutants sources.

            This study conducted with UNIX based Arcview, Arc/Info, and X-gobi

            programs, and geoprocessing, spatial analyst, X-gobi Arcview's

            extensions are used.


Spatial randomness

            Lamda = 63/70 = 0.875
            P(0) = 0.417 = 30.014
            P(1) = 0.365 = 26.271
            P(2+) = 0.160 = 11.494
Point Per Square
Observed Point
Expected Point


                Based on the calculation the chi -  square is 4.394 with 2 degree of

            freedom. Therefore, I conclude that the sample points are randomly

            distribute throughout the inlet with 90% confidence interval

Correlation between pollutants concentration and main boat path

                I use a regression coefficient between pollutants concentration and main

            path of the boat traffic.
Standard Deviation

            Based on data, I can calculate
            r = {sigma [(concentration - average concentration)*(distance -  average
            distance)] } / [(N * Standard Deviation of X * Standard Deviation of Y)]

            = - 147267.91/63(66.08)(907.421)
            = - 0.38, and r square = 0.14

                It means negative relationships between pollutants concentration and

            main boat path. The r square is only 14%, which means 14% of the Y variation

            is explained by X. Therefore, pollutants concentration and main boat

            path doesnĄ¯t show strong relationship.

Concentration of the pollutants VS Summerhouse outlet
Standard Deviation


            Yhat = a+bXi
            b= -1417797.696/261518832.449 = -0.005
            a = 74.17 - (-0.005*2634.124) = 87.341
            r = 25824918106/132594386709 = 0.20 and r square = 0.04

                This test indicate only 4% variable in pollutant concentration related

            to the distance from the summerhouse outlet. This test also doesnĄ¯t

            show the relationship between pollutant concentration and summerhouse


Concentration and Distance from the Boat Main Path



                These pictures are shows pollutant concentration and main boat path result.

            Using brush function in X-Gobi, red cross represent sample point, and

            green rectangle shows high concentration point. The most of high

            concentration area is left-hand side

Concentration and Bottom types


                 These graphs show relationship pollutant concentration and

            bottom types. Numbers (1 to 5) represent each particle size, and 1 is

            biggest particle size. This result shows very close relationship

            between these two variations.

Concentration and Depth


                    Pollutant concentration is strongly related to the depth, because 4 is

            deepest water in this inlet. The most of higher concentration is

            located in the shallow water, so water depth might be key element for

            the diffusion process.

Pollutant Concentration and Distance from the summerhouse outlet


                    These images doesn't show much about the relationship between these two

            data, but the many of high pollutant concentration is located near by

            summerhouse outlet.  Furthermore, those two biggest pollutant concentration

            sample points are closet location from the summerhouse outlet.


                This Loxahatchee Inlet data shows certain relationship between the

            diffusion of pollutants, but it's hard to say that surrounding

            environment strongly influence to pollutants diffusion processes.

            Bottom types and depth result shows very close relationship to the

            pollutant concentration. In addition, the most of higher concentration

            sample points are located near Loxahatchee river, it's might be the

            bottleneck effects. However, I don't have much additional such as

            water flow, more sample point, exact pollutant material, and biological

            aspect. If I have some more data for this study, I can clearly define

            the process to the Loxahatchee Inlet, or I miss focused this data set.


Wolman, M. G. (1988). Changing national water quality polices, T. WPCF
            60(10): 1774 - 1781

P.E. Rijtema, V. Elias (1996) Regional Approaches to Water Pollution
            in the Environment, NATO ASI Series

Jay Devore (1999) Applied Statistics for Engineer and Scientist,
            Brooks/Cole Publishing Company

Cook, D., Symanzik, J., Majure J. J., and Cressie N. (1997). Dynamic
            Graphics in a GIS: More Examples Using Linked Software. Computer and
            Geosciences: Special issues on Exploratory Cartographic Visualization,
            23(4):371 - 385. Paper, CD, and Http:// www.elsevier.nl/locate/cgvis