Flexible Workflow for Determining Critical Hazard and Exposure Scenarios for Assessing SLODs Risk in Urban Built Environments

Urban Built Environments (UBE) are increasingly prone to SLow-Onset Disasters (SLODs) such as air pollution and heatwaves. The effectiveness of sustainable risk-mitigation solutions for the exposed individuals’ health should be defined by considering the effective scenarios in which emergency conditions can appear. Combining environmental (including climatic) conditions and exposed users’ presence and behaviors is a paramount task to support decision-makers in risk assessment. A clear definition of input scenarios and related critical conditions to be analyzed is needed, especially while applying simulation-based approaches. This work provides a methodology to fill this gap, based on hazard and exposure peaks identification. Quick and remote data-collection is adopted to speed up the process and promote the method application by low-trained specialists. Results firstly trace critical conditions by overlapping air pollution and heatwaves occurrence in the UBE. Exposure peaks (identified by remote analyses on the intended use of UBEs) are then merged to retrieve critical conditions due to the presence of the individuals over time and UBE spaces. The application to a significant case study (UBE in Milan, Italy) demonstrates the approach capabilities to identify key input scenarios for future human behavior simulation activities from a user-centered approach.

[1]  P. Robinson On the Definition of a Heat Wave , 2001 .

[2]  G. Meehl,et al.  More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century , 2004, Science.

[3]  K. Guntupalli,et al.  Heat-related illnesses. , 1999, Critical care clinics.

[4]  Kees de Hoogh,et al.  Effects of travel mode on exposures to particulate air pollution. , 2008, Environment international.

[5]  W. Botzen,et al.  Combining hazard, exposure and social vulnerability to provide lessons for flood risk management , 2015 .

[6]  P. Sloot,et al.  The impact of pace of life on pedestrian heat stress: A computational modelling approach. , 2020, Environmental research.

[7]  Ana Isabel Miranda,et al.  Pedestrian Exposure to Air Pollution in Cities: Modeling the Effect of Roadside Trees , 2013 .

[8]  T. Poli,et al.  A New Approach to Assess the Built Environment Risk under the Conjunct Effect of Critical Slow Onset Disasters: A Case Study in Milan, Italy , 2021, Applied Sciences.

[9]  Gülen Çağdaş,et al.  Fuzzy logic in agent-based modeling of user movement in urban space: Definition and application to a case study of a square , 2020 .

[10]  Arno Schlueter,et al.  Context-specific urban occupancy modeling using location-based services data , 2020 .

[11]  Gulshan Sharma,et al.  Effect of aging on respiratory system physiology and immunology , 2006, Clinical interventions in aging.

[12]  P. Rajagopalan,et al.  Review on the impact of urban geometry and pedestrian level greening on outdoor thermal comfort , 2016 .

[13]  Riccardo Paolini,et al.  Preparing Weather Data for Real-Time Building Energy Simulation , 2020, ArXiv.

[14]  Peter Hoffmann,et al.  An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas , 2018 .

[15]  Enrico Quagliarini,et al.  EPES – Earthquake pedestrians׳ evacuation simulator: A tool for predicting earthquake pedestrians׳ evacuation in urban outdoor scenarios , 2014 .

[16]  Frank de Leeuw,et al.  Air quality status and trends in Europe , 2014 .

[17]  Prashant Kumar,et al.  Designing vegetation barriers for urban air pollution abatement: a practical review for appropriate plant species selection , 2020, npj Climate and Atmospheric Science.

[18]  C. Borrego,et al.  Modelling of tree-induced effects on pedestrian exposure to road traffic pollution , 2012 .

[19]  S. Tong,et al.  The impact of heatwaves on mortality and emergency hospital admissions from non-external causes in Brisbane, Australia , 2011, Occupational and Environmental Medicine.

[20]  Klaus D Goepel,et al.  Implementation of an Online Software Tool for the Analytic Hierarchy Process (AHP-OS) , 2018, International Journal of the Analytic Hierarchy Process.

[21]  Chao Yuan,et al.  How does weather and climate affect pedestrian walking speed during cool and cold seasons in severely cold areas? , 2020 .

[22]  C. Sioutas,et al.  Traffic-related Air Pollution and Blood Pressure in Elderly Subjects With Coronary Artery Disease , 2010, Epidemiology.

[23]  G. Salvalai,et al.  SLow Onset Disaster Events Factors in Italian Built Environment Archetypes , 2020 .