Study on the effectiveness of fire suppression deluge systems in tunnels

The required water flow for adequate deluge system operation during a tunnel fire is currently only prescribed by a few regulatory authorities. Car fires are commonly used as references when addressing water-based suppression; nevertheless, limited public information exists on the amount of water required for correctly suppressing a car fire and the thresholds by which the suppression systems fails to be effective. This paper aims at delivering key experimental outcomes to fill this gap in car tunnel fire suppression. The effectiveness of deluge sprinkler systems was investigated by performing a series of full-scale car fire experiments. These experiments were performed by symmetrically positioning a single car under a single sprinkler nozzle, with activation happening (i.e. the sprinkler going off) at a certain time from ignition (which defines the size of the fire), and carefully gauging the burning behaviour of the car fire. A single car was used as it was deemed as the minimum unit for a fire. Temperatures inside, around, and above the car were measured and infrared camera footage was used to gauge flame heights during the experiment. Results from this study yielded two forms of car fire suppression by a deluge system: gradual and instantaneous. A correlation between heat release rate and required water flow for the deluge system is also presented. Outcomes herein show that a water flow per unit area of 6.6 mm/min is the minimum water flow required to effectively reduce the temperature in the immediate vicinity of a car fire of different sizes

Typology of coastal urban vulnerability under rapid urbanization

Coastal areas are urbanizing at unprecedented rates, particularly in low- and middle-income countries. Combinations of long-standing and emerging problems in these urban areas generate vulnerability for human well-being and ecosystems alike. This baseline study provides a spatially explicit global systematization of these problems into typical urban vulnerability profiles for the year 2000 using largely sub-national data. Using 11 indicator datasets for urban expansion, urban population growth, marginalization of poor populations, government effectiveness, exposures and damages to climate-related extreme events, low-lying settlement, and wetlands prevalence, a cluster analysis reveals a global typology of seven clearly distinguishable clusters, or urban profiles of vulnerability. Each profile is characterized by a specific data-value combination of indicators representing mechanisms that generate vulnerability. Using 21 studies for testing the plausibility, we identify seven key profile-based vulnerabilities for urban populations, which are relevant in the context of global urbanization, expansion, and climate change. We show which urban coasts are similar in this regard. Sensitivity and exposure to extreme climate-related events, and government effectiveness, are the most important factors for the huge asymmetries of vulnerability between profiles. Against the background of underlying global trends we propose entry points for profile-based vulnerability reduction. The study provides a baseline for further pattern analysis in the rapidly urbanizing coastal fringe as data availability increases. We propose to explore socio-ecologically similar coastal urban areas as a basis for sharing experience and vulnerability-reducing measures among them

One simulation, different conclusions—the baseline period makes the difference!

The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period

Archetype analysis in sustainability research : meanings, motivations, and evidence-based policy making

Archetypes are increasingly used as a methodological approach to understand recurrent patterns in variables and processes that shape the sustainability of social-ecological systems. The rapid growth and diversification of archetype analyses has generated variations, inconsistencies, and confusion about the meanings, potential, and limitations of archetypes. Based on a systematic review, a survey, and a workshop series, we provide a consolidated perspective on the core features and diverse meanings of archetype analysis in sustainability research, the motivations behind it, and its policy relevance. We identify three core features of archetype analysis: recurrent patterns, multiple models, and intermediate abstraction. Two gradients help to apprehend the variety of meanings of archetype analysis that sustainability researchers have developed: (1) understanding archetypes as building blocks or as case typologies and (2) using archetypes for pattern recognition, diagnosis, or scenario development. We demonstrate how archetype analysis has been used to synthesize results from case studies, bridge the gap between global narratives and local realities, foster methodological interplay, and transfer knowledge about sustainability strategies across cases. We also critically examine the potential and limitations of archetype analysis in supporting evidence-based policy making through context-sensitive generalizations with case-level empirical validity. Finally, we identify future priorities, with a view to leveraging the full potential of archetype analysis for supporting sustainable development

The role of quantitative cross-case analysis in understanding tropical smallholder farmers’ adaptive capacity to climate shocks

Climate shocks are predicted to increase in magnitude and frequency as the climate changes, notably impacting poor and vulnerable communities across the Tropics. The urgency to better understand and improve communities' resilience is reflected in international agreements such as the Paris Agreement and the multiplication of adaptation research and action programs. In turn, the need for collecting and communicating evidence on the climate resilience of communities has increasingly drawn questions concerning how to assess resilience. While empirical case studies are often used to delve into the context-specific nature of resilience, synthesizing results is essential to produce generalizable findings at the scale at which policies are designed. Yet datasets, methods and modalities that enable cross-case analyses that draw from individual local studies are still rare in climate resilience literature. We use empirical case studies on the impacts of El Niño on smallholder households from five countries to test the application of quantitative data aggregation for policy recommendation. We standardized data into an aggregated dataset to explore how key demographic factors affected the impact of climate shocks, modeled as crop loss. We find that while cross-study results partially align with the findings from the individual projects and with theory, several challenges associated with quantitative aggregation remain when examining complex, contextual and multi-dimensional concepts such as resilience. We conclude that future exercises synthesizing cross-site empirical evidence in climate resilience could accelerate research to policy impact by using mixed methods, focusing on specific landscapes or regional scales, and facilitating research through the use of shared frameworks and learning exercises

understanding and tackling poverty and vulnerability in mountain livelihoods in the hindu kush himalaya

This chapter critically reviews the existing knowledge on livelihoods, poverty, and vulnerability in the Hindu Kush Himalaya (HKH). Development in mountain areas and the practices of people in these areas are uniquely conditioned by distinct characteristics that we term "mountain specificities". Some of these specificities—such as inaccessibility, fragility, and marginality—constrain development. Others—such as abundant biological diversity, ecological niches, and adaptation mechanisms—present development opportunities for mountain people

Vulnerability and its discontents: the past, present, and future of climate change vulnerability research

The concept of vulnerability is well established in the climate change literature, underpinning significant research effort. The ability of vulnerability research to capture the complexities of climate-society dynamics has been increasingly questioned, however. In this paper, we identify, characterize, and evaluate concerns over the use of vulnerability approaches in the climate change field based on a review of peer-reviewed articles published since 1990 (n = 587). Seven concerns are identified: neglect of social drivers, promotion of a static understanding of human-environment interactions, vagueness about the concept of vulnerability, neglect of cross-scale interactions, passive and negative framing, limited influence on decision-making, and limited collaboration across disciplines. Examining each concern against trends in the literature, we find some of these concerns weakly justified, but others pose valid challenges to vulnerability research. Efforts to revitalize vulnerability research are needed, with priority areas including developing the next generation of empirical studies, catalyzing collaboration across disciplines to leverage and build on the strengths of divergent intellectual traditions involved in vulnerability research, and linking research to the practical realities of decision-making

Typology of coastal urban vulnerability under rapid urbanization

Coastal areas are urbanizing at unprecedented rates, particularly in low- and middle-income countries. Combinations of long-standing and emerging problems in these urban areas generate vulnerability for human well-being and ecosystems alike. This baseline study provides a spatially explicit global systematization of these problems into typical urban vulnerability profiles for the year 2000 using largely sub-national data. Using 11 indicator datasets for urban expansion, urban population growth, marginalization of poor populations, government effectiveness, exposures and damages to climate-related extreme events, low-lying settlement, and wetlands prevalence, a cluster analysis reveals a global typology of seven clearly distinguishable clusters, or urban profiles of vulnerability. Each profile is characterized by a specific data-value combination of indicators representing mechanisms that generate vulnerability. Using 21 studies for testing the plausibility, we identify seven key profile-based vulnerabilities for urban populations, which are relevant in the context of global urbanization, expansion, and climate change. We show which urban coasts are similar in this regard. Sensitivity and exposure to extreme climate-related events, and government effectiveness, are the most important factors for the huge asymmetries of vulnerability between profiles. Against the background of underlying global trends we propose entry points for profile-based vulnerability reduction. The study provides a baseline for further pattern analysis in the rapidly urbanizing coastal fringe as data availability increases. We propose to explore socio-ecologically similar coastal urban areas as a basis for sharing experience and vulnerability-reducing measures among them