Examining How Federal Infrastructure Policy Could Help Mitigate and Adapt to Climate Change: Hearing Before the H. Comm. on Transp. & Infrastructure, 116th Cong., Feb. 26, 2019 (Statement of Vicki Arroyo)

As the Fourth National Climate Assessment, released in November, describes, the United States is already experiencing serious impacts of climate change—and the risks to communities all across the country are growing rapidly. These findings, along with those in the 2018 Intergovernmental Panel on Climate Change (IPCC)report, are clear and should be a call to immediate action. Even if we manage to limit planetary warming to just 2 degrees C, the world will still face increased chances of economic and social upheaval from more severe flooding, droughts, heatwaves, and other climate impacts as well as devastating environmental consequences, the IPCC report warns. The scientific consensus as described in the IPCC Special Report is that countries around the world must rapidly decarbonize their economies, cutting greenhouse gas emissions in half by 2030 and to near zero by 2050. Yet the current trends are going in the wrong direction. Despite our increasing understanding of the narrowing window to act, U.S. GHG emissions increased by 3.4% in 2018, according to a January report from the Rhodium Group. Clearly more action is needed. The encouraging news is that many states and cities have committed to taking action. They are taking steps to reduce emissions through legislation, executive orders, and pledges made in collaborations such as the US Climate Alliance –now covering roughly half the US population and GDP. In my testimony, I will be focusing on the transportation sector, which is the largest contributor of GHG emissions in the United States, and is already facing significant impacts from climate change. Federal standards have been important in increasing efficiency and reducing emissions, yet transportation-sector emissions are increasing as more vehicle miles are driven, more freight is transported in trucks, and airline travel continues to grow. Transportation is becoming an increasingly large share of U.S. economy-wide emissions as the power sector decarbonizes as a result of market shifts and policy. There is an urgent need, therefore, to transition to a low-carbon transportation system. Such a transition would not only reduce emissions and fight climate change, it also would bring additional important benefits, including protecting public health by reducing conventional air pollution, providing more mobility options, and driving innovation and economic growth through policy action and through public and private investment

A planning approach to the automated synthesis of template-based process models

The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

A classification of mitigation strategies for natural hazards: implications for the understanding of interactions between mitigation strategies

The unexpectedly poor performances of complex mitigation systems in recent natural disasters demonstrate the need to reexamine mitigation system functionality, especially those combining multiple mitigation strategies. A systematic classification of mitigation strategies is presented as a basis for understanding how different types of strategy within an overall mitigation system can interfere destructively, to reduce the effectiveness of the system as a whole. We divide mitigation strategies into three classes according to the timing of the actions that they prescribe. Permanent mitigation strategies prescribe actions such as construction of tsunami barriers or land-use restrictions: they are frequently both costly and “brittle” in that the actions work up to a design limit of hazard intensity or magnitude and then fail. Responsive mitigation strategies prescribe actions after a hazard source event has occurred, such as evacuations, that rely on capacities to detect and quantify hazard events and to transmit warnings fast enough to enable at risk populations to decide and act effectively. Anticipatory mitigation strategies prescribe use of the interpretation of precursors to hazard source events as a basis for precautionary actions, but challenges arise from uncertainties in hazard behaviour. The NE Japan tsunami mitigation system and its performance in the 2011 Tohoku disaster provide examples of interactions between mitigation strategies. We propose that the classification presented here would enable consideration of how the addition of a new strategy to a mitigation system would affect the performance of existing strategies within that system, and furthermore aid the design of integrated mitigation systems

Reducing social vulnerability to environmental change : building trust through social collaboration on environmental monitoring

ABSTRACT: The occurrence of natural and socially driven catastrophic events has increased in the last few decades in response to global environmental changes. One of the most societally relevant challenges in managing the effects of these events is the establishment of risk management strategies that focus on managing vulnerability, particularly in disfavored countries, and communities among them. Most cases of enhanced vulnerability occur in, but are not limited to, developing countries, where the combination of social inequity, inappropriate use of natural resources, population displacement, and institutional mistrust, among other factors, make risk management particularly challenging. This paper presents a vulnerability-centered risk management framework based on social cohesion and integration principles that, combined with scientific, technical, and popular knowledge, lead to the development of social networks of risk reduction. This framework is intended as a strategy to strengthen early warning systems (EWS), where the human-related factor is among their most challenging components. Using water-related hazards as a case study, this paper describes the experience of the conformation of a social network for environmental monitoring using this model example on vulnerability reduction in the rural areas of the central Andes in Colombia. This experience allowed the effective conformation of a social network for environmental monitoring in 80 municipalities of Colombia, where communities developed a sense of ownership with the instrumentation and the network, strengthening links with local authorities and contributing to more efficient EWS. More generally, the authors highlight the need to develop vulnerability-centered risk management via community-building strategies, particularly for areas where little can be done to decrease the occurrence of catastrophic events

The Global Risks Report 2016, 11th Edition

Now in its 11th edition, The Global Risks Report 2016 draws attention to ways that global risks could evolve and interact in the next decade. The year 2016 marks a forceful departure from past findings, as the risks about which the Report has been warning over the past decade are starting to manifest themselves in new, sometimes unexpected ways and harm people, institutions and economies. Warming climate is likely to raise this year's temperature to 1° Celsius above the pre-industrial era, 60 million people, equivalent to the world's 24th largest country and largest number in recent history, are forcibly displaced, and crimes in cyberspace cost the global economy an estimated US$445 billion, higher than many economies' national incomes. In this context, the Reportcalls for action to build resilience – the "resilience imperative" – and identifies practical examples of how it could be done.The Report also steps back and explores how emerging global risks and major trends, such as climate change, the rise of cyber dependence and income and wealth disparity are impacting already-strained societies by highlighting three clusters of risks as Risks in Focus. As resilience building is helped by the ability to analyse global risks from the perspective of specific stakeholders, the Report also analyses the significance of global risks to the business community at a regional and country-level

Emergency Services Workforce 2030: Changing landscape literature review

The Changing Landscape Literature Review collates a high-level evidence base around seven major themes in the changing landscape (i.e., the external environment) that fire, emergency service, and rural land management agencies operate in, and which will shape workforce planning and capability requirements over the next decade. It is an output of the Workforce 2030 project and is one of two literature reviews that summarise the research base underpinning a high-level integrative report of emerging workforce challenges and opportunities, Emergency Services Workforce 2030. Workforce 2030 aimed to highlight major trends and developments likely to impact the future workforces of emergency service organisations, and their potential implications. The starting point for the project was a question: What can research from outside the sphere of emergency management add to our knowledge of wider trends and developments likely to shape the future emergency services workforce, and their implications? The seven themes included in the Changing Landscape Literature Review are: 1) demographic changes, 2) changing nature of work, 3) changes in volunteering, 4) physical technology, 5) digital technology, 6) shifting expectations, and changing risk. A second, accompanying literature review, the Changing Work Literature Review, focuses on another nine themes related to emergency service organisation’s internal workforce management approaches and working environments

Influencing Factors for Use of Unmanned Aerial Systems in Support of Aviation Accident and Emergency Response

The purpose of this research paper was to examine the influencing factors associated with the use of unmanned aerial system (UAS) technology to support aviation accident and emergency response. The ability of first responders to react to an emergency is dependent on the quality, accuracy, timeliness, and usability of information. With aviation accidents such as the Asiana Airlines Flight 214 crash at San Francisco International Airport, the ability to sense and communicate the location of victims may reduce the potential for accidental passenger death. Furthermore, the ability to obtain information en-route to an accident may also to assist to reduce overall response and coordination time of first responders (e.g., Aviation Rescue and Firefighting [ARFF]). By identifying and examining current and potential practices, capabilities, and technology (e.g., human-machine-interface [HMI], human factors, tools, and capability modifiers) a more comprehensive model of the influencing factors is established to further support the growing body of knowledge (i.e., safety, human computer interaction, human-robot systems, socio-economical systems, service and public sector systems, and technological forecasting). A series of recommendations regarding the technology and application are provided to support future development or adaptation of regulations, policies, or future research. --from the article

A Proof-of-Concept of Integrating Machine Learning, Remote Sensing, and Survey Data in Evaluations: The Measurement of Disaster Resilience in the Philippines

Disaster resilience is a topic of increasing importance for policy makers in the context of climate change. However, measuring disaster resilience remains a challenge as it requires information on both the physical environment and socio-economic dimensions. In this study we developed and tested a method to use remote sensing (RS) data to construct proxy indicators of socio-economic change. We employed machine-learning algorithms to generate land-cover and land-use classifications from very high-resolution satellite imagery to appraise disaster damage and recovery processes in the Philippines following the devastation of typhoon Haiyan in November 2013. We constructed RS-based proxy indicators for N=20 barangays (villages) in the region surrounding Tacloban City in the central east of the Philippines. We then combined the RS-based proxy indicators with detailed socio-economic information collected during a rigorous-impact evaluation by DEval in 2016. Results from a statistical analysis demonstrated that fastest post-disaster recovery occurred in urban barangays that received sufficient government support (subsidies), and which had no prior disaster experience. In general, socio-demographic factors had stronger effects on the early recovery phase (0-2 years) compared to the late recovery phase (2-3 years). German development support was related to recovery performance only to some extent. Rather than providing an in-depth statistical analysis, this study is intended as a proof-of-concept. We have been able to demonstrate that high-resolution RS data and machine-learning techniques can be used within a mixed-methods design as an effective tool to evaluate disaster impacts and recovery processes. While RS data have distinct limitations (e.g., cost, labour intensity), they offer unique opportunities to objectively measure physical, and by extension socio-economic, changes over large areas and long time-scales.Zunehmende Wetterextreme und Naturkatastrophen sind Folgen des Klimawandels. Aufgrund dieser steigenden Risiken rückt die Resilienz der Bevölkerung im Katastrophenfall als zentrales Thema in den Vordergrund und hat zunehmende Bedeutung für politische Entscheidungstragende. Dennoch bleibt die Messung des mehrdimensionalen Konzepts der Katastrophenresilienz eine Herausforderung, da sie Informationen sowohl über die physische Umgebung als auch sozioökonomische Faktoren erfordert. In dieser Studie wird eine Methode entwickelt, um aus Fernerkundungsdaten (RS-Daten) Indikatoren zu entwickeln, die Aspekte des sozioökonomischen Wandels approximieren und somit messbar machen (Proxy-Indikatoren). Zu diesem Zweck wurden Algorithmen des maschinellen Lernens eingesetzt. Mit Hilfe dieser Algorithmen wurden aus hochauflösenden Satellitenbildern Klassifizierungen für Landstruktur und Landnutzung konstruiert, um Katastrophenschäden und iederaufbauprozesse auf den Philippinen nach der Zerstörung durch den Taifun Haiyan im November 2013 zu messen. Aus den RS-Daten wurden die Indikatoren für N=20 Barangays (Dörfer) in der Region um die Stadt Tacloban im zentralen Osten der Philippinen berechnet. Diese auf RS-Daten basierenden Indikatoren wurden mit detaillierten sozioökonomischen Informationen kombiniert, die für eine DEval-Evaluierung im Jahr 2016 erhoben wurden. Die Ergebnisse der statistischen Analyse zeigen, dass der schnellste Wiederaufbau nach der Katastrophe in städtischen Barangays zu beobachten war, die ausreichend staatliche Unterstützung (Subventionen) erhielten und über keine Katastrophenerfahrung verfügten. Im Vergleich hatten soziodemografische Faktoren allgemein stärkere Auswirkungen auf die frühe (0-2 Jahre) als auf die spätere (2-3 Jahre) Wiederaufbauphase. Es konnte nur ein bedingter Bezug zwischen der deutschen Entwicklungszusammenarbeit und den Wiederaufbauerfolgen festgestellt werden. Diese Studie versteht sich als Nachweis der Machbarkeit, weniger als detaillierte statistische Analyse. Sie belegt, dass hochauflösende RS-Daten und Techniken des maschinellen Lernens innerhalb eines integrierten Methodendesigns als effektives Werkzeug zur Bewertung von Katastrophenauswirkungen und Wiederherstellungsprozessen eingesetzt werden können. Trotz spezifischer Einschränkungen (hohe Kosten, Arbeitsintensität etc.) bieten RS-Daten einzigartige Möglichkeiten sowohl Umweltbedingungen als auch sozioökonomische Veränderungen über große Gebiete und lange Zeiträume hinweg objektiv messen zu können

Potential applications of unmanned ground and aerial vehicles to mitigate challenges of transport and logistics-related critical success factors in the humanitarian supply chain

The present decade has seen an upsurge in the research on the applications of autonomous vehicles and drones to present innovative and sustainable solutions for traditional transportation and logistical challenges. Similarly, in this study, we propose using autonomous cars and drones to resolve conventional logistics and transport challenges faced by international humanitarian organizations (IHOs) during a relief operation. We do so by identifying, shortlisting, and elaborating critical success factors or key transport and logistics challenges from the existing humanitarian literature and present a conceptual model to mitigate these challenges by integrating unmanned ground (UGVs) and aerial vehicles (UAVs) in the humanitarian supply chain. To understand how this novel idea of using UGVs and UAVs could help IHOs, we drafted three research questions, first focusing on the identification of existing challenges, second concentrating on remediation of these challenges, and the third to understand realization timeline for UGVs and UAVs. This lead to the development of a semi-structured, open-ended questionnaire to record the respondents’ perspectives on the existing challenges and their potential solutions. We gathered data form, ten interviewees, with substantial experience in the humanitarian sector from six IHOs stationed in Pakistan and Austria. In light of the feedback for the second research question, we present a conceptual model of integrating UAVs and UGVs in the relief chain. The results of the study indicate that technological advancement in mobility withholds the potential to mitigate the existing challenges faced by IHOs. However, IHOs tend to be reluctant in adapting UGVs compared to UAVs. The results also indicate that the adaptation of these technologies is subject to their technical maturity, and there are no significant differences in opinions found between the IHOs from Pakistan and Austria

Enhancing Warnings

Warnings are part of our everyday life, whether traffic lights, food health warnings, the weather, advice from colleagues, or moralistic stories. Warnings serve to provide cautionary advice, give advance notice of something, and generate awareness to trigger consequent decisions and actions. Warnings are seldom considered beyond the issuance of a warning, yet warnings are far more complex, requiring a comprehensive tool and system to help implement preventative, mitigative, and disaster risk-reductive actions. Warnings are not just a siren or phone alert but should be a long-term social process that is a carefully crafted, integrated system of preparedness involving vulnerability analysis and reduction, hazard monitoring and forecasting, disaster risk assessment, and communication. Together, these activities enable a wide range of leaders and others – such as individuals, local groups, governments, and businesses – to take timely and effective action to reduce disaster risks in advance of hazards. Warnings are represented via different iconographies and communicated via different mediums that usually express some form of threshold or tipping point. These vary enormously contingent on the hazard, and social, political, and economic context of the warning. Warnings should provide actionable guidance that is integrated into everyday life and behaviour, providing transparency and credibility to help manage risk in emerging and ongoing situations. Warnings must operate beyond the silos frequently seen in institutions, for different vulnerabilities, different hazards, and different stakeholders to become a long-term social process that can serve to bring together these diverse issues. This report examines how this can be implemented providing key case-study examples of lessons learnt and guidance on how to build effective warning systems. To enhance a warning requires placing it as part of a warning system, a long-term social process that embodies the 3 I’s ( Imagination, Initiative, Integration) and 3 E’s (Education, Exchange, Engagement). The authors offer three recommendations and provide guidance on how to implement these recommendations: Develop effective warnings that consider multiple-hazards, cascading events, and integration across stakeholders. Adopt a public engagement and outreach programme that empowers people to identify and fulfil their own needs regarding warnings for enhancing preparedness and response behaviours and actions. Create and support mechanisms to overcome silos and territorialism and instead encourage idea and action exchange for building trust and connections that support action when a major situation arises