Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking.

Wildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland-urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts. Supplementary Information: The online version contains supplementary material available at 10.1007/s10694-023-01371-1.

The Egress Enabler: Development and psychometric evaluation of an instrument to measure egressibility.

BACKGROUND: Egressibility has been defined as a person-environment fit issue and describes accessibility to means of evacuation. Although egressibility concerns everyone, it has become a useful concept particularly in relation to safety and accessibility for people with functional limitations, commonly highlighted as a vulnerable group in egress scenarios. Egressibility is an important safety factor, but there has been limited efforts trying to quantify it. OBJECTIVE: The aim has been to develop an instrument to measure egressibility in public buildings, as well as conducting initial psychometric testing of the instrument. METHODS: The Egress Enabler is based on the previously developed Housing Enabler instrument. The Egress Enabler was developed in several steps by an interdisciplinary team, incorporating an expert panel and a case study. RESULTS: Evaluation of content validity was in line with previous similar efforts, inter-rater reliability was considered "good" to "excellent" by means of intraclass correlation, and qualitative assessment of construct validity showed theoretically sound results. CONCLUSIONS: It is suggested that an instrument like the Egress Enabler is needed for a systematic evaluation of egressibility during design. construction or operation. This is needed for ensuring equal access to egress for people with functional limitations.

EXPOSED: An occupant exposure model for confined spaces to retrofit crowd models during a pandemic.

Crowd models can be used for the simulation of people movement in the built environment. Crowd model outputs have been used for evaluating safety and comfort of pedestrians, inform crowd management and perform forensic investigations. Microscopic crowd models allow the representation of each person and the obtainment of information concerning their location over time and interactions with the physical space/other people. Pandemics such as COVID-19 have posed several questions on safe building usage, given the risk of disease transmission among building occupants. Here we show how crowd modelling can be used to assess occupant exposure in confined spaces. The policies adopted concerning building usage and social distancing during a pandemic can vary greatly, and they are mostly based on the macroscopic analysis of the spread of disease rather than a safety assessment performed at a building level. The proposed model allows the investigation of occupant exposure in buildings based on the analysis of microscopic people movement. Risk assessment is performed by retrofitting crowd models with a universal model for exposure assessment which can account for different types of disease transmissions. This work allows policy makers to perform informed decisions concerning building usage during a pandemic.

New "Smart" Systems for Atmospheric Aerosol and Reactive Gas Sampling in Ambient Air.

Nowadays a recognized need for accurate observations of atmospheric aerosols (AEs) and reactive gases (RGs) exists in the framework of regional, national and global near-surface networks based on permanent or mobile measurement stations. In this context, a paramount and not-trivial issue is related to the correct execution of continuous sampling of ambient air and its subsequent distribution to measurement analyzers hosted inside the stations. Sampling artifacts must be minimized for obtaining reliable pictures of ambient air composition. To respond to this need, a suite of novel "smart" and relatively low-cost systems for the continuous sampling of ambient air was developed in the framework of the 2012⁻2015 I-AMICA Project. These systems were designed to execute AE and RG measurements according with WMO/GAW and ACTRIS recommendations and standard operation procedures. A particular attention was dedicated to the stabilization and control of the sampling flow rates and temperatures. The analysis of one full year of operations at the WMO/GAW regional station of Capo Granitola (GAW ID: CGR, Italy), allowed to conclude that these systems are effective in meeting the technical requirements for correct execution of AE and RG measurements.

Dissuasive exit signage for building fire evacuation.

This work presents the result of a questionnaire study which investigates the design of dissuasive emergency signage, i.e. signage conveying a message of not utilizing a specific exit door. The work analyses and tests a set of key features of dissuasive emergency signage using the Theory of Affordances. The variables having the largest impact on observer preference, interpretation and noticeability of the signage have been identified. Results show that features which clearly negate the exit-message of the original positive exit signage are most effective, for instance a red X-marking placed across the entirety of the exit signage conveys a clear dissuasive message. Other features of note are red flashing lights and alternation of colour. The sense of urgency conveyed by the sign is largely affected by sensory inputs such as red flashing lights or other features which cause the signs to break the tendencies of normalcy.

A dynamic approach for the impact of a toxic gas dispersion hazard considering human behaviour and dispersion modelling.

The release of toxic gases due to natural/industrial accidents or terrorist attacks in populated areas can have tragic consequences. To prevent and evaluate the effects of these disasters different approaches and modelling tools have been introduced in the literature. These instruments are valuable tools for risk managers doing risk assessment of threatened areas. Despite the significant improvements in hazard assessment in case of toxic gas dispersion, these analyses do not generally include the impact of human behaviour and people movement during emergencies. This work aims at providing an approach which considers both modelling of gas dispersion and evacuation movement in order to improve the accuracy of risk assessment for disasters involving toxic gases. The approach is applied to a hypothetical scenario including a ship releasing Nitrogen dioxide (NO2) on a crowd attending a music festival. The difference between the results obtained with existing static methods (people do not move) and a dynamic approach (people move away from the danger) which considers people movement with different degrees of sophistication (either a simple linear path or more complex behavioural modelling) is discussed.

Variable Message Signs for road tunnel emergency evacuations.

This paper investigates the design of Variable Message Signs (VMS) as a way-finding aid for road tunnel emergency evacuations. The use of the Theory of Affordances is suggested to provide recommendations on the design of VMS. A preliminary evaluation of 11 selected VMS systems was performed and 6 of them were further evaluated using an affordance-based within subject stated-preference questionnaire administered to a sample of 62 participants. Results are used to provide recommendations on the characteristics of the VMS systems, such as (1) size of the sign (large or small); (2) use of flashing lights; (3) colour scheme; (4) message coding (i.e., text, pictograms or a combination of them). The best performing VMS features for road tunnel emergency evacuation included the use of larger signs, flashing lights, the combination of emergency exit pictorial symbol in green in one panel and text in amber in the other panel.