Climate Adaptation Engineering: Risks and Economics for Infrastructure Decision-Making

By Emilio Bastidas-Arteaga and Mark G. Stewart

Climate Adaptation Engineering defines the measures taken to reduce vulnerability and increase the resiliency of built infrastructure. This includes enhancement of design standards, structural strengthening, utilisation of new materials, and changes to inspection and maintenance regimes, etc. The book examines the known effects and relationships of climate change variables on infrastructure and risk-management policies. Rich with case studies, this resource will enable engineers to develop a long-term, self-sustained assessment capacity and more effective risk-management strategies. The book's authors also take a long-term view, dealing with several aspects of climate change. The text has been written in a style accessible to technical and non-technical readers with a focus on practical decision outcomes.

• Provides climate scenarios and their likelihoods, hazard modelling (wind, flood, heatwaves, etc.), infrastructure vulnerability, resilience or exposure (likelihood and extent of damage)
• Introduces the key concepts needed to assess the risks, costs and benefits of future proofing infrastructures in a changing climate
• Includes case studies authored by experts from around the world

• Language: English
• Publisher: Elsevier Science
• Release date: Mar 16, 2019
• ISBN: 9780128168400

Emilio Bastidas-Arteaga

Emilio Bastidas-Arteaga is Associate Professor of Civil and Mechanical Engineering at the University of Nantes in France. Since 2009, he has been working on the assessment of consequences and adaptation of infrastructure and buildings subjected to climate change within the framework of national and international collaborations and research projects. He has been and is also participating in several technical committees related to climate change and civil engineering: French Association for Normalisation (AFNOR, France), American Concrete Institute (ACI, USA), Joint Research Centre (JRC, Europe), and the International Association for Bridge and Structural Engineering (IABSE, International).

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Newcastle.

Part I

Introduction

Chapter One

Introduction to Climate Adaptation Engineering

Mark G. Stewart*; Emilio Bastidas-Arteaga†    * Centre for Infrastructure Performance and Reliability, School of Engineering, The University of Newcastle, Callaghan, NSW, Australia

† Research Institute in Civil and Mechanical Engineering, UMR CNRS 6183, Université de Nantes, Nantes Cedex, France

Abstract

Climate change predictions announced significant changes in the current weather patterns that could increase infrastructure vulnerability. Since infrastructure assets are of primary importance for protecting human lives and for providing fundamental societal and economical services, the adaptation of these infrastructure to new demands induced by climate changes becomes paramount for future sustainable development. Within this framework this chapter poses the basis of a concept called ‘Climate Adaptation Engineering’ that aim to improve the response of built infrastructure to future potential climate change effects based on a rational risk-based decision support. The chapter starts by introducing and reviewing basic concepts about climate change impacts and scenarios. This literature review justifies the introduction of a risk-based decision support that integrates climate and hazard, engineering, and fragility models, as well as economical decision tools to perform a comprehensive assessment of the cost-effectiveness of adaptation measures. This risk-based decision support will be illustrated with various study cases in the following chapters of this book.

Keywords

Risk; Climate change; Cost–benefit analysis; Infrastructure; Climate adaptation

Acknowledgements

The authors gratefully acknowledge the support of the Université de Nantes, and the Pays de la Loire Regional Council for supporting the project RI-ADAPTCLIM.

1.1 Introduction

Climate change arouses much fear and anxiety in society; and for good reasons, if climate projections are correct, a changing climate will cause sea-level rise, more flooding, and more intense storms and hurricanes, droughts, and other climate extremes. This will affect every nation, and populations in developing countries will be hit hardest. This can, in the worst case, lead to energy and food scarcity, increase the spread of disease, mass migration of ‘climate refugees’, and weaken fragile governments. Urban communities are particularly vulnerable to a changing climate, and Rapid urbanization and the growth of megacities, especially in developing countries, have led to the emergence of highly vulnerable urban communities, particularly through informal settlements and inadequate land management (IPCC, 2012).

The focus of this chapter (and this book) is on technological innovation and adaptive behaviours—that is, the future proofing of infrastructure to climate change for future generations, economies, and environments. The impact of climate change on infrastructure performance is a temporal and spatial process, but most existing models of infrastructure performance are based on a stationary climate. For example, the World Bank states that Despite the ability to quantify future risk (albeit with uncertainty), risk assessments typically fail to account for changing climate, population, urbanization, and environmental conditions (World Bank, 2016). Hence, there is a need to quantify the costs and benefits of adaptation strategies. Climate adaptation engineering involves estimating the risks, costs and benefits of climate adaptation strategies, and assessing at what point in time climate adaptation becomes economically viable. Climate adaptation measures aim to reduce the vulnerability or increase the resiliency of built infrastructure to a changing climate, this may include, for example, enhancement of design standards, retrofitting or strengthening of existing structures, utilisation of new materials, and changes to inspection and maintenance regimes. Engineers have a unique capability to model infrastructure vulnerability, and these skills will be essential to modelling future climate impacts, and measures to ameliorate these losses.

The climate change literature places more emphasis on impact modelling than on climate adaptation engineering modelling. This is to be expected when the current political and social environment is focused on mitigating (reducing) CO2 emissions. The impacts on people and infrastructure may be considerable if there is no climate adaptation engineering to the existing and new infrastructure. Some posit that climate change may even be a threat to national security, but Stewart (2014) suggests that climate change threats to US national security are modest and manageable. On the other hand, higher temperatures in higher latitude regions such as Russia and Canada can be beneficial through higher agricultural yields, lower winter mortality, lower heating requirements, and a potential boost to tourism (Stern, 2007).

There is seldom mention of probabilities, quantitative measures of vulnerability, or the likelihood or extent of losses in ‘risk’ and ‘risk management’ reports on climate change and infrastructure. While useful for initial risk screening, intuitive and judgement-based risk assessments are of limited utility to complex decision-making since there are often a number of climate scenarios, adaptation options, limited funds, and doubts about the cost-effectiveness of adaptation options. In this case, the decision maker may still be uncertain about the best course of action, and so a detailed risk analysis is required (e.g., AS 5334-2013). For this reason, there is a need for sound system and probabilistic modelling that integrates the engineering performance of infrastructure with the latest developments in stochastic modelling, structural reliability, and decision theory. Such an approach is a logical extension of disaster risk management. The emphasis of the book is built infrastructure. This accords with the World Bank (2016) for the need for the construction of buildings, infrastructure, and urban developments should consider how design, construction practices, and construction materials will affect disaster risk in both current and future climates.

The cost to mitigate CO2 emissions is considerable. Stern (2007) estimated that to stabilise CO2 levels at 550 ppm (by reducing total emissions to three quarters of today’s levels by 2050), it would cost 1.0%–3.5% of gross domestic product (GDP), with a central estimate of approximately 1%. The mean estimate would result in an annual mitigation cost of approximately $720 billion. This is a stupendous sum, and so a pivotal question becomes: is this the best option, or are there others? This is the question that Bjorn Lomborg posed to a group of experts—they found that climate change action ranked very low when compared with other hazard and risk-reducing measures, in this case the benefit-to-cost ratio (BCR) for CO2 mitigation was only 0.9 (not cost-effective), but increased to 2.9 for a mix of mitigation and adaptation strategies (Lomborg, 2009). Yohe et al. (2009) found that a global investment of $18 billion per year in ‘R&D (research and development) and mitigation’ can halve ‘business as usual’ CO2 emissions by 2100. Such actions would reduce the impact of climate change by at least 60%. The key here is R&D where innovation can be an important driver to reducing CO2 emissions.

Some of the more dire predictions of food and energy insecurity, and mass migration can be ameliorated by funding climate adaptation measures in the developing world. Adaptation measures to reduce vulnerability of infrastructure, coastal zones, agriculture, forestry, fisheries, and human health to climate change hazards would include: flood control dikes and levees, dams, cyclone shelters, storm and flood-resistant housing, improved communication infrastructure, resettlement of populations to lower risk zones, and improved health care. The World Bank (2010) estimated that the cost to the developing world of adapting to an approximately 2°C warmer world by 2050 is approximately $75 billion per year. This represents about one-tenth of 1% of world GDP. Clearly, investing in targeted adaptation measures has the potential to dramatically reduce the impact of climate change.

As we have seen, CO2 mitigation costs can be high, and the benefits of reduced CO2 levels will take decades to accrue. Modest and sustained investments in R&D, CO2 mitigation, and adaptation will lessen the worst impacts of climate change. Hence, a mix of mitigation and adaptation is desirable to cope with a changing climate. There are uncertainties, risks, upsides, and downsides that need to be factored into any decision. And we are talking about decisions that will involve many hundreds of billions of dollars of expenditures, so there is a need to explore the full range of options to effectively compare costs and benefits. There is no certainty about the future which makes decision-making for climate change incredibly challenging. There is clearly a need for action, the question is what should we be doing now? What decisions can be deferred? and to when? And perhaps most importantly—what information do we need to be able to make better decisions?

There are strongly held beliefs about climate change, vested interests, wasteful expenditures, and poor thinking at times. There is a need to bring a scientific, analytic, and objective risk-based approach to this serious issue. Poor infrastructure decisions made today can lead to long-term adverse impacts over many decades to come.

The chapter will describe how risk-based decision support is well suited to optimising climate adaptation strategies related to the design, construction, operation, and maintenance of built infrastructure. Fig. 1.1 describes the overall concept outlined in this book. An important aspect is assessing when climate adaptation becomes economically viable, if adaptation can be deferred, and decision preferences for future costs and benefits (many of them intergenerational). Stochastic methods are used to model infrastructure vulnerability, effectiveness of adaptation strategies, exposure, and costs. Case studies to follow in other chapters will detail how state-of-the-art risk-based approaches will help ‘future proof’ built infrastructure to a changing climate.

Fig. 1.1 Flowchart of risk-based decision support.

1.2 Climate Change Impact

The 2014 Intergovernmental Panel for Climate Change (IPCC) Fifth Assessment Report (AR5) concluded that the Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased (IPCC, 2014). What is less certain is the impact that rising temperatures will have on rainfall, wind patterns, sea-level rise, and other phenomena.

There is considerable literature on the impact of climate change. We start with the latest IPCC AR5 report released in 2013. For the sake of brevity, the main changes to climate by 2100 relevant to this book are (IPCC, 2013) as follows:

•Temperatures to increase from 1995 levels, anywhere from 0.3°C to 4.8°C.

•Sea-level rise of 26–82 cm.

•More intense tropical cyclones and other severe wind events.

•Precipitation may increase in high latitudes, but will decrease in Central America, Southern Africa, and Southern Europe.

•Enhanced monsoon precipitation.

•More frequent hot and fewer cold temperature extremes over most land areas.

The IPCC (2014) then suggests with a high or very high confidence level that these changes to climate will increase drought affected areas, hundreds of millions of people will be affected by coastal flooding, increases in risks of fire, pests, and disease outbreak, will have significant consequences on food and forestry production, food insecurity, and so on. When these impacts are projected to monetary units the damages are staggering. In the United States, one study estimates that $238 billion to $507 billion worth of property will be below sea level by 2100, and that average annual losses from hurricanes and other coastal storms along the Eastern Seaboard and the Gulf of Mexico will grow by more than $42 billion due to sea-level rise alone (Risky Business, 2014). The 2006 review by economist Nicholas Stern (2007) predicts that if no action is taken against climate change, the mean loss of GDP would be 2.9% and 13.8% each year (‘now and forever’) by 2100 and 2200, respectively. This is equivalent to worldwide losses of up to $10 trillion each year by 2200. Not surprisingly, some consider it to be highly pessimistic in its assumptions (Lomborg, 2006; Mendelsohn, 2006). However, the Australian Garnaut Review predicted that unmitigated climate change would reduce Australian GDP by approximately 8% by 2100 (Garnaut, 2008), and a more recent study projects that unmitigated warming is ‘expected to reshape the global economy’ and reduce global incomes by 23% by 2100 (Burke et al., 2015). A 2014 White House report states that a delay of implementing mitigation policies that results in warming of 3°C above preindustrial levels, instead of 2°, could increase economic damages by approximately 0.9% of global output. To put this percentage in perspective, 0.9% of estimated 2014 US GDP is approximately $150 billion. Moreover, these costs are not one-time, but are rather incurred year after year because of the permanent damage caused by increased climate change resulting from the delay (White House, 2014).

A reality check is often needed, as these are often worst-case losses, and the losses described above are all predicated on ‘business as usual’. According to the Risky Business Report, this assumes no new national policy or global action to mitigate climate change and an absence of investments aimed at improving our resilience to future climate impacts. Taking these policy and adaptive actions could significantly reduce the risks we face. It is difficult to fathom that the world will continue on its current path to the next millennium with no changes in the way we emit CO2 emissions, how we live, how we work, how we travel, how we value the environment, and so on. The history of human kind is one of constant change and innovation—it has never been static not even for a generation.

These staggering losses also do not reflect wealth creation, human capital, and new improved technologies. Goklany (2008) states that these often reduce the extent of the human health and environmental ‘bads’ associated with climate change more than temperature increases exacerbate them. Weather and climate-related fatality rates and economic losses are also 3–10 times higher in developing countries (IPCC, 2012). Clearly then, if people are wealthier in the future, their well-being will be higher, and the argument that we should shift resources from dealing with the real and urgent problems confronting present generations to solving potential problems of tomorrow’s wealthier and better positioned generations is unpersuasive at best and verging on immoral at worst (Goklany, 2008). This is not to say that we should place our trust in market forces alone, but to recognise that economic development, CO2 mitigation and adaptation are interlinked, and that Vulnerability too changes with urban and socioeconomic development. Some people become less vulnerable because of improved construction and a more prosperous economic situation. But in many areas, structural vulnerability continues to increase because of unregulated building practices and unplanned development (World Bank, 2016).

The observed increase in weather-related losses in the United States, Australia, and elsewhere is more a function of increased exposure with more people moving to vulnerable coastal locations than climate-change increases in wind speed or flood levels (Crompton and McAneney, 2008; IPCC, 2012). The apparent lack of a climate change signal in disaster losses is backed by the IPCC: "Economic losses due to extreme weather events have increased globally, mostly due to increase in wealth and exposure, with a possible influence of climate change (low confidence in attribution to climate change)" (IPCC, 2014).

Moreover, climate impacts will not be sudden, but gradual in their appearance. For instance, hurricane wind speeds are predicted to increase at worst by 10% in 50 years due to climate change, or a miniscule 0.2% per year (Bjarnadottir et al., 2011). This is in contrast with the population growth rate in Florida and other southern states which is double that of the United States at large, and is running at above 2% per year. This suggests that there will be time to adapt to a changing climate.

There is significant regional variability in climate change-induced hazards. A CSIRO study based on AR5 climate projections found that wind speeds are projected to fall by on average 1.8% in the southern city of Adelaide by 2090, but expected to increase by 2.2% in the Far North Queensland city of Cairns. Similarly, the number of days over 40°C is expected to increase by only 0.7 days per year for Cairns, but 83 days per year for the Central Australian city of Alice Springs (Webb and Hennessy, 2015). Large fluctuations in climate hazard in time and space necessitate tailoring engineering adaptation measures for local conditions. A ‘one-size’ fits all approach will not be optimal.

1.3 Climate Adaptation Engineering

The design and construction of infrastructure has evolved over many millennia so today we are able to predict with relative ease the likelihood and size of natural hazards, and take steps to design houses, buildings, bridges, power stations, dams, and other infrastructure to withstand these anticipated hazards. Earthquakes, tropical cyclones or hurricanes, storm surge, floods, and blizzards are often the low-probability high-consequence hazards of interest. Over the past century building standards have been developed and continually improved—with the prevention of building collapse and catastrophic loss (ultimate limit state) being the main driver for change. Moreover, while uncertainties and knowledge gaps still exist, disaster risks in the developed world are, in general, at an acceptable level. This is particularly the case for life-safety risks where, for example, the annual fatality rate from earthquakes in New Zealand is close to the generally acceptable risk of 1 × 10− 6 or one in a million (e.g., Taig, 2012, Stewart and Melchers, 1997). However, the seismic fatality rate in China in the decade 2001–10 is 50 times higher at 5 × 10− 5 (data sourced from Li et al., 2015).

Often the huge loss of life in the developing world is due to the poor quality of construction. In Bangladesh, the quality of concrete is poor (Koehn and Ahmmed, 2001). In Turkey, higher than expected earthquake damage is attributed to project errors, poor quality of construction, unlicensed modifications to buildings, and so on (Irtem et al., 2007). A magnitude 7.0 earthquake in Haiti in 2010 killed more than 230,000 people, mainly because of poor building construction, whereas a larger earthquake in densely populated Kobe, Japan, in 1995 killed around 6000, and a magnitude 6.9 earthquake in 1989 in the San Francisco Bay area killed some 63 people. Surveying the damage caused by an earthquake in China in 2008, in which many schools collapsed, killing hundreds of children, a field team of Australian and Hong Kong earthquake experts observed that many buildings had inadequate construction quality including insufficient reinforcement, poor detailing and poor quality concrete (Wibowo et al., 2008). In addition, building codes have been bypassed with the complicity of corrupted officials and construction site staff. As Penny Green noted for Turkey, ‘Violations were part of a well-entrenched political process,’ and she quotes an adviser to the mayor in one of the worst hit earthquake areas of Turkey, who admits, The project managers, they take bribes, we do it ourselves. There is no project inspection (Green, 2005).

On the other hand, large economic losses often arise from natural disasters in the developed world. For example, in 2012 Hurricane Sandy (also known as ‘Superstorm Sandy’) damaged over 750,000 residences in New Jersey and New York, and caused more than $50 billion in losses (Huffington Post, 2013). Loss of life numbered around 100, mostly from drownings. The 2010–11 earthquakes in Christchurch killed 185 people, most of them were victims of the collapse of two multistorey buildings, and caused over $30 billion in damages—or 20% of the New Zealand GDP. The widespread damage across the central business district and suburbs led to over 750,000 insurance claims being lodged, 64% of businesses were forced to close temporarily, and 11% were forced to close permanently (Potter et al., 2015). With the exception of two buildings that collapsed, other buildings performed as expected and did not collapse—so life safety was ensured. However, the widespread damage to building reduced their functionality and this loss was the main contributor to the huge economic losses suffered by the New Zealand Economy, and to the massive social dislocation of residents.

A key emphasis of this book, thus, is on how climate adaptation engineering can reduce damage to infrastructure that in turn can ameliorate the social and economic disruption of climate change hazards to the built environment. It aims to provide practical and climate-conscious engineering knowledge and solutions to reduce the impact of potential climate change on the performance of buildings and infrastructure, including safety, serviceability, and durability. Examples of climate adaptation engineering to be presented in this book are as follows:

•using probabilistic models for the assessment of climate change effects for infrastructure and buildings subjected to hurricanes under a changing climate (Chapter 2);

•installing underground storage tanks to enhance urban drainage and reduce flooding (Chapter 3);

•specifying higher durability recommendations to reduce climate change increases in corrosion (Chapter 4);

•changing inspection and replacement practices for timber power poles to reduce losses from climate-induced increases in wind speeds and rates of timber decay (Chapter 5);

•increasing bridge foundation depths to reduce the risk of scouring from floods (Chapter 6);

•integrating the interdependency between several infrastructure systems to increase its resilience in the case of extreme events (Chapter 7);

•combining housing and protection structure adaptations to reduce flooding vulnerability, (Chapter 8);

•enhancing design standards for new houses and retrofitting existing houses to reduce damage from extreme wind events (Chapter 9);

•upgrading construction quality and practices to increase housing resilience in the developing world (Chapter 10);

•upgrading building energy efficiency ratings for houses using insulation, sealing, and phase change materials to reduce heat stress during heatwaves (Chapter 11); and so on.

The above case studies are cognizant of the overriding principles for effective adaptation that include (IPCC, 2014) the following:

1.Adaptation is place- and context-specific, with no single approach for reducing risks appropriate across all settings.

2.Adaptation planning and implementation can be enhanced through complementary actions across levels, from individuals to governments.

3.A first step towards adaptation to future climate change is reducing vulnerability and exposure to present climate variability. Strategies include actions with cobenefits for other objectives.

4.Adaptation planning and implementation at all levels of governance are contingent on societal values, objectives, and risk perceptions. Recognition of diverse interests, circumstances, social-cultural contexts, and expectations can benefit decision-making processes.

5.Indigenous, local, and traditional knowledge systems and practices, including indigenous peoples’ holistic view of community and environment, are a major resource for adapting to climate change.

6.Decision support is most effective when it is sensitive to context and the diversity of decision types, decision processes, and constituencies.

7.Integration of adaptation into planning and decision-making can promote synergies with development and disaster risk reduction.

8.Poor planning, overemphasising short-term outcomes, or failing to sufficiently anticipate consequences can result in maladaptation.

Climate adaptation engineering integrates the previously mentioned items on a general risk-based decision support framework that could be applied to many infrastructure applications. Fig. 1.2 summarises the major steps in developing risk-based decision support for assessing the risks, costs, and benefits of climate adaptation measures. The following sections will describe the different components of this framework.

Fig. 1.2 Flowchart of decision support framework for assessing cost-effectiveness of adaptation measures.

1.4 Climate Change Emission Scenarios

Future climate is projected by defining carbon emission scenarios in relation to changes in population, economy, technology, energy, land use, and agriculture—a total of four scenario families, that is, A1, A2, B1, and B2 were used in the IPCC’s Third and Fourth Assessment Reports in 2001 and 2007, respectively. The A1 scenarios indicate very rapid economic growth, a global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies, as well as substantial reduction in regional differences in per capita income. Subcategories of A1 scenarios include A1FI and A1B, which represent the energy in terms of fossil intensive and a balance across all sources, respectively. The A2 scenarios are based on a very heterogeneous world. The underlying theme is that of strengthening regional cultural identities, high population growth, and less concern for rapid economic development. The B1 scenarios are more integrated and more ecologically friendly than A1 scenarios with rapid changes towards a service and information economies, and reductions in material intensity and the introduction of clean and resource efficient