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9780471964353

Statistics for the Environment, Pollution Assessment and Control

by ;
  • ISBN13:

    9780471964353

  • ISBN10:

    0471964352

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 1997-07-07
  • Publisher: Wiley
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Summary

Pollution is an environmental issue that concerns us all and is of major importance in terms of its impact on peoples health and their living and working environments. This most recent volume of the Statistics for the Environment titles comprises the latest research and case-study material on topics in this area, with discussions on the various ways in which statistical models and methods can be used to advance knowledge and understanding of the different aspects of the pollution problem. Containing contributions from leading world experts in the use of statistics in the environmental sciences, it is the only work of its kind at this level. As with the previous two books, the editors have produced a cohesive and comprehensive overview of recent statistical advances in the area of pollution. Topics include: Policy and Management Issues Water Quality Sampling and Monitoring Radiation Air Quality Health and Ecology An essential addition to the already successful Statistics for the Environment series, this book will be a valuable resource for statisticians and scientists interested in the quantitative and qualitative aspects of pollution control, water contamination and environmental protection and conservation and many other pollution related themes.

Author Biography

Vic Barnett is the editor of Statistics for the Environment, Volume 3, Pollution Assessment and Control, published by Wiley. K. Feridun Turkman is the editor of Statistics for the Environment, Volume 3, Pollution Assessment and Control, published by Wiley.

Table of Contents

Preface xi
PART I INTRODUCTION 1(44)
1 Statistical Analyses of Pollution Problems
3(42)
V. Barnett
1.1 Introduction
3(4)
1.2 Towards a classification system
7(5)
1.3 Statistical analysis of pollution--general features
12(1)
1.4 Statistical methods used for pollution studies
13(12)
1.5 Classified analysis of publications on standard studies of pollution (1993-1995)
25(15)
1.6 Conclusions
40(5)
PART II SAMPLING AND MONITORING OF POLLUTION 45(42)
2 Sampling and Efficient Data Use for Characterizing Polluted Areas
45(26)
A. Stein
2.1 Introduction
45(1)
2.2 Theory
46(5)
2.2.1 The best linear predictor and the best linear unbiased predictor
46(2)
2.2.2 Modelling the spatial structure
48(2)
2.2.3 Cross-validation
50(1)
2.3 Interactive sampling
51(3)
2.4 Organoleptic observations
54(7)
2.5 Extrapolation
61(7)
2.6 Conclusions
68(1)
Acknowledgements
69(2)
3 Statistical Models for the Semi-Arid Land-Surface-Atmosphere Program: An Integrated Monitoring Experiment
71(16)
F. Avila
3.1 Introduction
71(2)
3.2 The SALSA program
73(3)
3.2.1 The San Pedro basin
73(1)
3.2.2 The Semi-Arid Land-Surface-Atmosphere program
73(2)
3.2.3 Statistical modeling for the SALSA program
75(1)
3.3 Model space
76(1)
3.3.1 The functional model
76(1)
3.3.2 The model space
77(1)
3.4 Data space
77(4)
3.4.1 Measurement process
77(2)
3.4.2 Data
79(1)
3.4.3 Randomness in the data model
80(1)
3.5 Prediction/estimation space
81(1)
3.6 Predictor space
81(1)
3.7 Statistical examples
82(3)
3.7.1 Random function model: geostatistics
83(1)
3.7.2 Random function model with random sampling
84(4)
3.7.3 Deterministic function model
88
3.8 Conclusions
85(1)
Acknowledgements
85(2)
PART III RADIATION 87(42)
4 Geostatistical Analysis of Residual Contamination from Nuclear Weapons Testing
89(20)
P. J. Diggle
L. Harper
S. L. Simon
4.1 Introduction
89(2)
4.2 Survey design
91(3)
4.2.1 Location of gamma-counting sites on Rongelap Island
91(1)
4.2.2 Gamma spectrometry
92(2)
4.3 Conventional geostatistical analysis
94(7)
4.3.1 Linear prediction for stationary Gaussian spatial processes
94(2)
4.3.2 Geostatistics in practice: transformations and the variogram
96(3)
4.3.3 Log-Gaussian analysis of the Rongelap Island data
99(2)
4.4 An approach to non-Gaussian geostatistics
101(5)
4.4.1 An extended class of spatial process models
101(2)
4.4.2 A Poisson log-linear model
103(2)
4.4.3 Poisson log-linear analysis of the Rongelap Island data
105(1)
4.5 Conclusions
106(1)
Acknowledgement
107(2)
5 Bayesian Uncertainty Analysis and Radiological Protection
109(20)
R. Haylock
A. O'Hagan
5.1 Introduction
109(2)
5.2 The underlying theory of Bayesian uncertainty analysis
111(8)
5.2.1 The Bayesian model
111(1)
5.2.2 Estimating model outputs
112(2)
5.2.3 Estimating the mean of the uncertainty distribution
114(1)
5.2.4 Estimating the variance of the uncertainty distribution
115(3)
5.2.5 Selection of optimum design points
118(1)
5.3 The PU239 internal dosimetry model
119(9)
5.3.1 A classical analysis of the Pu model
122(1)
5.3.2 Bayesian uncertainty analysis of the Pu model
123(2)
5.3.3 Results
125(1)
5.3.4 Discussion
126(2)
Acknowledgements
128(1)
PART IV AIR QUALITY 129(70)
6 Constructing Spatial Designs for Monitoring Air Pollution using Subset Regression
131(24)
D. Nychka
Q. Yang
J. A. Royle
6.1 Introduction
131(2)
6.2 Random surfaces and subset selection
133(2)
6.2.1 Random field model
133(1)
6.2.2 Properties of the motivating example
134(1)
6.2.3 A pseudo regression problem for a given covariance
134(1)
6.3 Variable selection for linear regression models
135(2)
6.4 Space-filling designs
137(1)
6.5 Comparing designs on regular grids
138(12)
6.5.1 Performance measures
142(3)
6.5.2 Results
145(4)
6.5.3 Random designs
149(1)
6.6 Chicago area ozone monitoring network
150(4)
6.6.1 Subset designs
150(1)
6.6.2 Design performance
150(4)
6.7 Discussion
154(1)
7 Local Polynomial Regression and Its Applications in Environmental Statistics
155(20)
D. Ruppert
7.1 Introduction
155(4)
7.2 Local regression
159(3)
7.3 Bandwidth selection
162(3)
7.4 Estimation of conditional variance
165(1)
7.5 Examples
166(6)
7.5.1 Biomonitoring of mercury
166(4)
7.5.2 LIDAR
170(1)
7.5.3 Soil elevation and gradient
170(2)
7.6 Discussion
172(1)
Acknowledgements
173(2)
8 Statistical Analysis of Trend in Urban Ozone
175(10)
H. Vaquera-Huerta
J. A. Villasenor
J. Hughes
8.1 Introduction
175(1)
8.2 Parametric models for the intensity function of an NHPP
176(1)
8.3 Proposed model for the intensity function
176(2)
8.4 A likelihood ratio test for trend
178(1)
8.5 Computations of the maximum likelihood parameter estimates
178(1)
8.6 Non-parametric estimation of the intensity function
179(4)
8.7 Discussion
183(1)
Appendix
183(2)
9 Forecasting Air Pollution with Casual Probabilistic Networks
185(14)
L. E. Sucar
J. C. Ruiz-Suarez
9.1 Introduction
185(2)
9.2 Probabilistic networks
187(3)
9.3 Structure learning in casual probabilistic networks
190(4)
9.4 Experimental results
194(2)
9.5 Conclusions and future work
196(3)
PART V WATER QUALITY 199(50)
10 Non-Point-Source Pollution of Surface Waters over a Watershed
201(24)
N. Cressie
J. J. Majure
10.1 Introduction
201(2)
10.2 The GIS's role in the computing environment
203(15)
10.2.1 The GIS
204(2)
10.2.2 The original database
206(2)
10.2.3 The derived database
208(9)
10.2.4 Distances between sampling sites
217(1)
10.3 Modelling the large-scale variation
218(3)
10.4 Spatio-temporal analysis of statistical dependence
221(3)
10.5 Conclusions
224(1)
Acknowledgements
224(1)
11 Geostatistics Applied to Hydrology Problems and Tools
225(16)
D. Myers
11.1 Introduction
225(2)
11.1.1 Heterogeneity
226(1)
11.1.2 Stochastic modelling
227(1)
11.2 The tools
227(4)
11.2.1 Univariate
227(3)
11.2.2 Multivariate
230(1)
11.3 Simulation
231(3)
11.3.1 Turning Bands Algorithm
231(1)
11.3.2 L-U or Cholesky decomposition
232(1)
11.3.3 Sequential Gaussian simulation
232(1)
11.3.4 Simulated annealing
233(1)
11.4 Parameters
234(1)
11.5 Contaminant concentrations
235(1)
11.6 Sampling design
236(1)
11.7 Model-based vs. design-based analyses
237(1)
11.8 Lingering statistical problems
237(4)
12 Optimal Screening Methods in Detection of Water Contamination
241(8)
M. A. Amaral Turkman
K. F. Turkman
12.1 Introduction
241(1)
12.2 Optimal screening of water contamination with fixed number of variables
242(4)
12.2.1 Optimal specification region for the probit model
244(2)
12.3 Sequential screening for water quality
246(2)
Acknowledgements
248(1)
PART VI HEALTH 249(52)
13 Interpolating Air Pollution for Health Impact Assessment
251(18)
J. V. Zidek
13.1 Introduction
251(2)
13.2 The errors-in-variables problem
253(2)
13.3 Assessment methods and models
255(3)
13.4 A spatial prediction method
258(6)
13.5 Selected findings from an application
264(3)
13.6 Concluding remarks
267(1)
Acknowledgements
268(1)
14 Latencies, Exposures to Environmental Hazards, and Cancer Rates
269(18)
Y. Mao
I. B. MacNeill
14.1 Introduction
269(4)
14.2 Population mobility
273(1)
14.3 Confounding variables
273(1)
14.4 Brief description of the enhanced cancer surveillance system
273(1)
14.5 Definition of latency
274(1)
14.6 Data requirements for latency estimation
275(4)
14.7 Distribution of ages of addiction to tobacco
279(1)
14.8 Addiction-age-group/death-age-group
280(2)
14.9 Latency distribution
282(3)
14.10 Continuous time models
285(2)
15 An Investigation of the Effect of Road Traffic Pollution on Asthma, Using Geographical Information Systems
287(14)
M. McCready
S. Patel
K. Rennolls
15.1 Introduction
287(3)
15.1.1 Environmental epidemiology
287(1)
15.1.2 Asthma
288(2)
15.2 Data and methods
290(4)
15.2.1 National Child Development Study
290(1)
15.2.2 GIS and Bartholomew's Digital Map of Great Britain
290(1)
15.2.3 Data linkage
291(1)
15.2.4 A measure of road traffic related pollution
291(3)
15.3 Epidemiological analysis
294(2)
15.4 Results
296(2)
15.5 Discussion
298(1)
Acknowledgements
299(2)
PART VII POLICY AND MANAGEMENT 301(16)
16 Statistical Issues in Environmental Monitoring and Assessment of Anthropogenic Pollution
303(14)
L. H. Cox
N. P. Ross
16.1 Introduction
303(1)
16.2 Statistical issues in environmental monitoring and measurements: the collection of primary environmental data
304(2)
16.2.1 Monitoring
304(1)
16.2.2 Spatial and temporal variability
304(2)
16.3 Environmental indicators
306(1)
16.4 Statistical issues in environmental sampling
306(1)
16.5 Use of environmental models
307(1)
16.6 Use of encountered data
308(4)
16.7 Issues for environmental statistics in decision making and public policy
312(4)
16.7.1 Environmental risk assessment
312(1)
16.7.2 Reporting on the state of the environment
313(1)
16.7.3 Public assess
314(2)
16.8 Summary
316(1)
Acknowledgements
316(1)
References 317(36)
Index 353

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