The intent in this book is to carefully describe the methodologies, typical mathematical notation, and assumptions typically used in risk assessment calculations. Subsequently, the book’s chapters describe various statistical analysis procedures that are used for estimating the parameters used in risk assessment methodologies. Numerous examples and descriptions of the bases of the methodologies are provided.

Unlike much of the professional literature in statistics, this text makes concerted efforts to describe statistical techniques in terms comprehensible to the nonstatistician. This is accomplished by downplaying mathematical notation, comprehensively explaining the development of equations, and emphasizing example applications. Thus, as example problems of interpretations of environmental monitoring results are described, the text demonstrates through use of simple examples, how the procedures are utilized. References are provided, with particular emphasis on works describing applications reported in the technical literature. Problems included at the end of the chapters stress fundamentals and increase the usefulness of this book as a classroom text, intended for senior undergraduate and graduate students in environmental engineering and environmental sciences.

The collection and laboratory analyses of samples needed to characterize environmental quality are expensive. Further, as society expresses increasing concern for environmental protection and as instrumentation technology evolves to allow detection of contaminants at ever‐lower concentrations, expenditures for monitoring environmental quality will continue to increase with time. As a direct consequence of the substantial costs of environmental monitoring, it is essential to use available environmental quality data as effectively as possible. Effective utilization involves answering questions such as, “Is the environmental quality acceptable?,” “Is the environmental quality improving or deteriorating?,” and “Is the risk acceptable and/or need to be managed?” Responding to these types of questions requires interpretation of data, and this stage of assessment is beset with difficulties. Some difficulties with interpreting environmental‐monitoring results include:

1. Since environmental data are frequently expensive to accumulate, the data sets being interpreted are typically modest in size.
2. The data may involve a vector of chemical and biological constituent measurements because consideration must typically be given to a range of constituents. Correlation between the constituents may help the infilling of missing data or the identification of outlier data.
3. Early detection of any deterioration in environmental quality is highly desirable because early detection may provide the opportunity for controlling the problem, at a lower cost, before the problem magnifies. Any procedure for identifying early warning signals must not, however, falsely identify a problem of apparent environmental deterioration when one does not actually exist, a so‐called false positive, nor should it fail to identify a problem when one does exist, a so‐called false negative.
4. The vagaries of nature typically introduce significant noise, and sources of variability such as seasonal effects, make the identification of trends more difficult.
5. The derivation of quantitative risk assessments is, in many ways, data dependent. However, a key question is whether the information returned by risk estimates warrant additional data collection efforts?

The net result of difficulties such as the five examples mentioned above is that making sense of the data relevant to risk assessment methodologies necessarily involves statistical interpretation. Statistical interpretation procedures must be sensitive to small changes in environmental quality and yet recognize the potentially substantial costs of any additional data collection requirement.

The need for the statistical interpretation of data is widespread. The range of concerns for each environmental media – air quality, surface water quality, groundwater quality, and soil contamination – is similar in many respects. And yet, there is no single statistical analysis procedure universally applicable to the variety of problems associated with environmental quality data. Instead, the practitioner needs to have an array of statistical procedures available. A multitude of statistical analysis tests are available, but each of the tests possesses assumptions that may, or may not, be appropriate for specific circumstances and hence, having a number of techniques is frequently required. Computer programs now becoming widely available facilitate the use of various procedures (e.g. ProUCL, EPA, 2013). The difficulty remains for the student and practitioner to learn which conditions dictate a particular procedure and which conditions render it highly inappropriate.

Following the introduction (Chapter 1), the book is organized into three parts as follows:

• Part I – Chapters 2 through 4 develop the fundamental calculation procedures and methodologies for risk characterization.
• Part II – Chapters 5 through 7 describe the characteristics of common distributions as utilized to describe data.
• Part III – Chapters 8 through 12 describe the bases used in hypothesis testing to determine when there are differences in environmental quality at various locations. Problems of censored data are considered as they influence the utilization of alternative tests. Chapter 12 focuses on nonparametric procedures, an alternative to the parametric procedures utilized in previous chapters.

Edward A. McBean (B.A.Sc. from the University of British Columbia and S.M., C.E., and Ph.D. from the Massachusetts Institute of Technology) is a Professor of Water Resources, Canada Research Chair (CRC) in Water Supply Security in the School of Engineering and now a University Research Leadership Chair, at the University of Guelph. Dr. McBean has also been the Assistant Dean of the College of Physical and Engineering Science at the University of Guelph for an 8‐year period. Dr. McBean started his career in risk assessment as a faculty member for two decades at the University of Waterloo and the University of California, followed by a decade as a Vice‐President of Conestoga‐Rovers and Associates (CRA) and President of CRA Engineering Inc., both environmental engineering firms. For the most recent decade, Dr. McBean has been a Canada Research Chair of Water Supply Security at the University of Guelph. He is an author of 2 previous books, editor of 17 books, and author of more than 350 papers in the refereed technical literature. Dr. McBean has been the recipient of many awards including Fellow of the Canadian Academy of Engineering, Fellow of the Canadian Society of Civil Engineering, Fellow of Engineering Institute of Canada, the K.Y. Lo Award for his work in international engineering, the Research and Development Award of the Professional Engineers of Ontario, and the Camille Dagenais Award for outstanding contributions to engineering.

The work reported in this book is the assembly of work completed by many. A much earlier version of this book was published under the title of Statistical Procedures for Analyses of Environmental Monitoring Data and Risk Assessment by Prentice‐Hall in 1998, but this book is no longer in print. The copyright for this early book was requested, and received, from the publisher. Extensive rewriting and examples have been introduced into this book. Most importantly, the emphasis of this current book is on risk assessment and the information provided on statistical data in support of risk assessment methodologies.

In addition to the literature, the experience and efforts of many individuals has been important in developing this book, and for this assistance I am truly grateful. In particular, the talent and expertise of Frank Rovers, a co‐author of the previous book, is gratefully acknowledged. Frank has been an inspiration as well as a colleague and friend throughout my professional career.

As well, I gratefully acknowledge the work and effort of many colleagues and students, who have been very important to the learning expressed in this book. These individuals are too many to name, but specific important examples include:

• The employees of CRA (now GHD) who so generously provided examples. The advice and assistance of many is acknowledged, with special mention of Wes Dyck, John Donald, and Klaus Schmidtke.
• All the people who examined drafts of the book and whose comments for improvement were valuable. In particular, the comments from many students are gratefully acknowledged.
• The efforts of Melissa McBean and Munir Bhatti who prepared many of the figures in this book are also gratefully acknowledged.

To all of the above, I owe sincere thanks for their assistance.

In an undertaking of the magnitude of this text, it is not possible to avoid errors, and for this I apologize; but this book is supplied in good faith. While I have taken reasonable care to avoid errors, I accept no liability for any damage, consequential or otherwise, that may be caused by the use of this book. Any suggestions for corrections, criticisms, or suggestions for improvements will be greatly appreciated and I will work towards improvements in any future versions of this book. As well, many of the coefficients continue to be updated, and hence, the reader must refer to the Internet and other sources of the information for these updates; the emphasis in this book must necessarily be on the methodological processes and explanations thereof. I would also welcome any additional information and data that would make future editions of the book more complete.

This book is accompanied by a companion website:

www.wiley.com/go/McBean/RiskAssessProcedure_1e

Scan this QR code to visit the companion website

The BCS is a compilation of answers to various questions in the book itself. The intent in providing these is to expand the opportunity for the students to “learn through using the information provided in the book.” Many of the questions are from old examination questions generated over the years while using the book in “draft” form.