Engineering Decisions for Life Quality

To improve the overall quality of life for all in society is a desirable high-level goal, but our capacity to do so is limited by available resources. Work creates wealth, but it also adds to, and creates, risk to life, health, and the environment. We take a good portion of that wealth and use it to reduce those risks. How big should that portion be, and how should it be distributed over the hundreds of risk-reducing options? We can answer this question by means of the quantified societal capacity to commit resources to risk reduction, which we derive from the economics of human welfare. The underlying principles and the methods are discussed in the first three chapters and the appendices. The remainder of the book illustrates application of the principles in risk management practice.

Assessment and quantified analysis of risk are necessary to support and improve the quality of risk management decisions. We propose the use of social indicators for managing risk. There are several compound social indicators that quantify some aspects of human welfare, reflecting how well a society empowers people to lead the life they desire. The indicators also allow a comparison amongst nations and monitoring of the performance of a nation over time. The Life Quality Index (LQI), developed in this book, is the basis for the life quality method, primarily meant as a tool for managing risk. The LQI provides practical guidance for justification of expenditures on life safety and allows decision-makers a defendable basis for allocation of resources amongst competing claims.

The life quality method can be an effective and versatile tool to support social and economic cost–benefit analysis of projects that have consequential impacts on individual welfare and the quality of life. The approach transcends traditional cost–benefit analysis by drawing into account demographics, economic productivity, and life safety impacts. Here we illustrate the computational procedures required to develop the guidance in practical contexts.

The adverse impacts of air pollution and ground-level ozone on public health and the environment have motivated the development of Canada-Wide Standards (CWS) on air quality. Valuation of reduction in mortality is a critical step in assessing the benefits and costs of regulatory option as it accounts for the largest proportion (> 80%) of the benefits. The overestimation of benefits is a concern since it has the potential of diverting resources from other social needs that also contribute to enhanced life quality. Here we show how the Life Quality Index (LQI) can be used to quantify the level of expenditure beyond which it is no longer justifiable to spend societal resources.

The safe operation of nuclear reactors places a premium on reducing the risk of radiation exposure to workers and members of the public with the potential for adverse health effects and loss of life. To ensure safety, large financial investments are generally incurred at the design stage of the power plants. By the life quality method, the efficacy of the expenditures can be judged against the safety benefit to be gained. The approach provides a defendable basis for making such judgment through its link to the societal capacity to commit resources. Here we illustrate how to quantify the justifiable expenditures for safety measures enacted to reduce the risk of exposures to radiation through engineering safety programs and safety regulations.

In this chapter we illustrate the application of the LQI method to select a structure that is optimal. Dams, dikes, and levees have traditionally been designed to a fuzzy quantity called the PMF (“probable” maximum flood). Proper probabilistic design is preferable, but it requires that hydrological data be translated into a local flood probability distribution. It is inadequate merely to do a conventional estimation of the distribution, since the application is to a unique location (a single sample realization of a time series) rather than a statistical population; the application is monoscopic in the sense of Matheron (1989). Estimation is a process that always introduces additional information, going beyond the facts. A tool to minimize this contaminating information, the method of relative entropy with fractile (or quantile) constraints (REF) has a practical and simple approximation described and illustrated here. The societal capacity to commit resources (SCCR), is used as the design criterion. Details of financing have an important influence on the design of civil engineering facilities by socio-economic optimization, including flood control projects. Since future life risk must be discounted like finances, the interest rate and the amortization period influence designs decisively. These aspects are all brought out in the example of a city protected by a levee.

In this book we place the management of public risks into the broader context of social policy in the service of the public good. We present a unified foundation for strategic management of risk in the form of four principles. Together these principles reflect some necessary general attributes of the quality of life in a modern state: public accountability, maximum net benefit for all, compensation for those who lose when there is change, and long life in good health with maximum personal choice. These principles form the basis of the life quality method of risk management, which we develop to operational level and illustrate by several examples drawn from engineering and public health practice. We have advanced the concept of the societal capacity to commit resources as a constraint in the decisionmaking process, recognizing that our desire to enhance life quality is limited by our capacity to create the wealth.