Maximum entropy-based modeling of community-level hazard responses for civil infrastructures

Perturbed by natural hazards, community-level infrastructure networks operate like many-body systems, with behaviors emerging from coupling individual component dynamics with group correlations and interactions. It follows that we can borrow methods from statistical physics to study the response of infrastructure systems to natural disasters. This study aims to construct a joint probability distribution model to describe the post-hazard state of infrastructure networks and propose an efficient surrogate model of the joint distribution for large-scale systems. Specifically, we present maximum entropy modeling of the regional impact of natural hazards on civil infrastructures. Provided with the current state of knowledge, the principle of maximum entropy yields the ``most unbiased`` joint distribution model for the performances of infrastructures. In the general form, the model can handle multivariate performance states and higher-order correlations. In a particular yet typical scenario of binary performance state variables with knowledge of their mean and pairwise correlation, the joint distribution reduces to the Ising model in statistical physics. In this context, we propose using a dichotomized Gaussian model as an efficient surrogate for the maximum entropy model, facilitating the application to large systems. Using the proposed method, we investigate the seismic collective behavior of a large-scale road network (with 8,694 nodes and 26,964 links) in San Francisco, showcasing the non-trivial collective behaviors of infrastructure systems

Proceedings of the International Workshop on 'Combined Environmental Exposure: Noise, Air Pollutants and Chemicals'

The issue of combined exposure to noise, air pollution and chemicals has raised recently the interest of several bodies of the European Commission such as DG Environment, DG SANCO and DG Research in the context of the EC 7th Framework Programme. There are open questions whether prevailing environmental concentrations of air pollutants and chemicals can lead to ototoxic health impacts. Therefore this issue needs to be thoroughly explored and investigated to help the EC to revise the existing standards and guidelines concerning combined exposure to noise, air pollutants and chemicals. The aim of the workshop was to review and discuss the existing scientific evidence whether prevailing environmental exposures to single and concomitant agents together with noise could lead to ototoxic or other health impacts. The final aim was to identify the research needs and to give recommendations for research and policy making in the EU level. It was agreed that research in the future should be focused on really established combinations (high correlations) and interactions (known effect) with main perspective on the traffic bundle of exposure. It was also discussed and agreed upon that the best knowledge exists on the health effects due to combined exposure to noise and solvents or heavy metals in occupational environments, especially on most of the auditory and non-auditory effects. Possible factors that may have confounding or aggravating effects on the results of noise studies were identified. Such factors are: age, gender, smoking, obesity, alcohol, socio-economic status, occupation, education, family status, active military, experience, hereditary disease, medication, medical status, race and ethnicity, physical activity, noisy leisure activities, stress reducing activities, diet & nutrition, housing condition (crowding), and residential status. Research priorities and recommendations for the future. The highest priority was given to issues related to research on noise and outdoor air pollutants. This is due to the fact that it may concern the largest population compared to the other stressors in this analysis and there is some evidence of serious health outcomes such as cardiovascular effects. The next priority was given to the research on the effects of noise and solvents in occupational settings and to research on noise and organophosphates. In the future research, priority should be given to: 1. evaluation of existing data collections whether re-analyses are possible with respect to combined exposure from traffic sources (road, rail and air), 2. analyses of existing data concerning noise and other stressors interactions in both occupational and environmental settings, 3. detailed assessment of combined exposures to noise, vibrations and PM, CO, NOx, and VOCs with specific studies in urban areas and, especially, cardiovascular health endpoints should be studied as priority health endpoints, 4. identification of causal mechanisms through careful review of toxicological experimental studies.JRC.I.5-Physical and chemical exposure

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Adverse Effects of Long Term Exposure to Road Traffic Noise

__Abstract__ Road traffic is a prominent source of environmental noise exposure in urbanized areas. Because of its common presence, traffic is a source of exposure that is not easy to avoid. As a consequence, it is affecting a substantial proportion of residents in their homes, and in their living environment more in general. In view of reducing the number of people affected by environmental noise exposure, the European Environmental Noise Directive (END) was adopted in 2002, geared towards the assessment and management of environmental noise

Harmonised ambient air pollution and road traffic noise exposures linked to cardiovascular outcomes in European cohorts

Ambient air pollution and traffic-related noise are the two leading environmental risk factors for health in Europe. Associations between long-term exposure to air pollution or noise and cardiovascular diseases (CVD) were not entirely consistent across previous studies in adults. Moreover, noise may confound the relationship between air pollution and CVD, and vice versa. This PhD project was conducted to study the separate and joint effects of both air pollution and noise on 1) CVD blood biochemistry including C-reactive protein, blood lipids and glucose and on 2) incident CVD outcomes. Health and exposures data were harmonised across four European cohorts (EPIC-Oxford, HUNT, LifeLines, UK Biobank), as part of the EU-funded BioSHaRE project. All harmonised data were virtually pooled for individual-level analyses in DataSHIELD, a novel statistical tool to perform a ‘compute to data’ statistical approach. The cross-sectional analyses on biochemistry data generally suggested that both air pollution and noise were significantly associated with adverse changes in markers of systemic inflammation, blood lipids and glucose. The significant association between road traffic noise and C-reactive protein or triglycerides was confounded by air pollution whilst both air pollution and noise were significantly and independently associated with elevated blood glucose levels. Incident analyses suggested a possible increased risk for both particulate matter (PM) and gaseous air pollution on incident cerebrovascular disease but a null association for ischaemic heart disease (IHD). Daytime noise was associated with a non-significantly increased risk for incident IHD but evidence for cerebrovascular disease was inconclusive. Both air pollution and noise effects on CVD outcomes were independent from each other. This PhD study provides some novel evidence of both air pollution and noise on CVD biochemistry and incident CVD outcomes, and is a substantial addition to the current knowledge of cardiovascular health effects of both ambient air pollution and traffic noise.Open Acces

A framework for integrated environmental health impact assessment of systemic risks

Traditional methods of risk assessment have provided good service in support of policy, mainly in relation to standard setting and regulation of hazardous chemicals or practices. In recent years, however, it has become apparent that many of the risks facing society are systemic in nature – complex risks, set within wider social, economic and environmental contexts. Reflecting this, policy-making too has become more wide-ranging in scope, more collaborative and more precautionary in approach. In order to inform such policies, more integrated methods of assessment are needed. Based on work undertaken in two large EU-funded projects (INTARESE and HEIMTSA), this paper reviews the range of approaches to assessment now in used, proposes a framework for integrated environmental health impact assessment (both as a basis for bringing together and choosing between different methods of assessment, and extending these to more complex problems), and discusses some of the challenges involved in conducting integrated assessments to support policy

The influence of noise, vibration, cycle paths, and period of day on stress experienced by cyclists

Urban and transport planners need to assess the stressful conditions experienced by cyclists, considering that highly stressful situations can discourage people from cycling as a transport mode. Therefore, this study has two objectives: (1) to present a method for monitoring stress and other environmental factors along cycling routes using smart sensors; and (2) to analyze the influence of noise, vibration, presence of cycle paths, and the period of the day on stress experienced by cyclists. Data were collected in the city of Sao Carlos, Brazil, using stress and noise sensors, accelerometers, and Global Positioning System (GPS). Primarily, heat maps generated from the data made it possible to identify critical points of stress along the routes. In addition, the results of a logistic regression model were analyzed to identify the influence of the studied variables on stress. Although high levels of noise increased the odds of experiencing stress by 4%, very uncomfortable vibrations increased the odds by 14%, and the presence of cycle paths reduced the odds by 8%, an analysis of p-values and odds ratio confidence intervals shows, with a 95% confidence level, that only the period of the day influenced stress, as confirmed by the data. In this case, the odds of having stress increased by 24% in the afternoon rush hour compared to the morning rush hour

Critical Market Crashes

This review is a partial synthesis of the book ``Why stock market crash'' (Princeton University Press, January 2003), which presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. The study of the frequency distribution of drawdowns, or runs of successive losses shows that large financial crashes are ``outliers'': they form a class of their own as can be seen from their statistical signatures. If large financial crashes are ``outliers'', they are special and thus require a special explanation, a specific model, a theory of their own. In addition, their special properties may perhaps be used for their prediction. The main mechanisms leading to positive feedbacks, i.e., self-reinforcement, such as imitative behavior and herding between investors are reviewed with many references provided to the relevant literature outside the confine of Physics. Positive feedbacks provide the fuel for the development of speculative bubbles, preparing the instability for a major crash. We demonstrate several detailed mathematical models of speculative bubbles and crashes. The most important message is the discovery of robust and universal signatures of the approach to crashes. These precursory patterns have been documented for essentially all crashes on developed as well as emergent stock markets, on currency markets, on company stocks, and so on. The concept of an ``anti-bubble'' is also summarized, with two forward predictions on the Japanese stock market starting in 1999 and on the USA stock market still running. We conclude by presenting our view of the organization of financial markets.Comment: Latex 89 pages and 38 figures, in press in Physics Report