Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach
Abstract
:1. Introduction
1.1. Pedestrian and the Meso-Scale Level in SLODs: Roads Network
- Areal Spaces (ASs): e.g., squares. These are spaces that express the habitat of the city, as well as places to meet and aggregate. From the urban point of view, the square can be defined as a free space, partially or fully surrounded by buildings. The shape, the location, the function, and the aesthetic expression of the square historically follows urban evolution, in which the main functions of a place of passage, place of utility, or place of stay can be combined or entirely grouped together. The importance of the square further increases as an urban space if it includes civil or religious buildings that are part of a city’s monumental heritage.
- Linear Spaces (LSs): Spaces of public use, identifiable as roads and streets, including those connecting ASs. They are often the most vital public spaces in cities.
1.2. SLODs Risk from the Pedestrian Perspective
- Babies (0–5 years): their organs are still developing, and their immune system is not yet accustomed to certain critical conditions in the outdoor environment. In addition, paediatric diseases can easily become worse when babies are exposed to high temperatures and pollutants.
- Young people (6–18 years): the effects of SLODs are lower than those of babies due to their growth, but prolonged exposure to these conditions could still result in permanent damage.
- Frail health: this group includes individuals with a particular health condition that may endanger them when they are exposed to certain hazards [36]. In particular, fragilities related to SLODs are: respiratory (e.g., asthma and allergies), cardiovascular and metabolic (diabetes) diseases and syndromes.
- Adults: this group can be assumed to include any other pedestrians not in the previous categories.
1.3. How to Improve Pedestrian SLODs Risk Assessment?
1.4. Work Aims
2. Phases, Materials and Methods
- Physical vulnerability assessment depending on the BE geometric and morphological characteristics and on its hazards. Open-source data collection tools are used to this end (Section 2.1). This phase defines two physical vulnerability indexes Pv, one for increasing temperature and one for air pollution, both organized in 5 classes in an RMA-based approach.
- Exposure and social vulnerability assessment depending, respectively, on the intended uses of buildings and open spaces in the BE, and on the groups of pedestrians (by age, by health fragilities) who can attend the B, (Section 2.2). This phase defines an exposure index E and a social vulnerability index Sv, both organized into 5 classes in the RMA-based approach.
- Overall risk matrix assessment by first combining Pv, E and Sv for each risk by itself, and then in a combined manner. Related meso-scale maps are also provided (Section 2.3).
2.1. Physical Vulnerability Assessment
- Road layout, defining the dimensions and function of features that characterize them, such as traffic dividers, vehicle lanes (trams, buses, etc.), sidewalks and bike paths [2,14,19,20,43]. Such kinds of data can be collected from the satellite maps of Google maps, using the special measurement tool provided on the website.
- Reliable traffic levels [17], according to traffic data provided by online maps (Google Maps and OpenStreetMap) [53,54] provided by an existing methodology [47]. This method overcomes the problem of the accuracy of the simulations because it is based on direct observations of reality. The first step is the collection of data by observing Google Maps traffic maps at hourly intervals from Monday to Friday, considering the “Typical traffic" option that provides average traffic levels from 06:00 to 23:00. The period from 23:00 to 06:00 (not covered by Google Maps surveys) was regarded as homogeneous and corresponding to the lowest level of traffic recorded during the day. This simplification was considered acceptable because of the low level of traffic during the night-time and the absence of people on the road. Then, to allow a more accurate assessment, the road types were defined according to their importance in the urban network and the main geometric characteristics, using the same sources of the road layout parameters. Each road type can be correlated to the service range per lane, defined as the number of vehicles equivalent to the hour and therefore the total service range, as prescribed by the Highway Code, issued by the Italian Ministry of Infrastructure and Transport [55]. The final step is the recognition of the overall traffic model defined as the level of comfort (LoC) for drivers and represented in Table 1. Numerical values (0.2–1.2) were assigned to each level to allow a quantitative assessment in terms of the number of equivalent vehicles passing through the unit of journeys in one hour. This classification was made based on the six LOS (levels of services) defined by the highway capacity manual (HCM 1985-2022) [56], which evaluates the amount of traffic flows that will be able to travel the infrastructure under analysis, defined according to a pejorative scale from A to F to which comfort levels are assigned (remarkable-not perceived). For each open space detected, a single weekly profile is defined, taking into account the worst combination of those observed in working days. The approach provides a qualitative representation of traffic models on an hourly scale.
2.2. Exposure and Social Vulnerability Assessment
- Identifying the use classes to be assigned to the buildings and the open spaces in the BE: six use classes have been identified based on the use of the buildings and the categories of users attending these spaces. Buildings and urban spaces are grouped into improved homogeneous categories (from A to F), as shown in Table 5. Each category is defined according to the type of space, the open spaces or buildings, and the attractiveness and comfort of the urban space. Given the context of the case study (see Section 2.4), this work adopts local regulations (L.R. n. 12, 11 March 2005), which reflect the general intended uses of the BE. This assumption is suitable for assessments on the entire Italian territory but remains valid even for case studies outside the national borders sharing similarly intended use typologies and BE use features since the classification has also been based on definitions from previous research all over the World [67,68,69,70,71,72].
- The detection of the use classes (Table 5) of buildings and open spaces in the BE and their spatio-temporal features: where available, GIS tools could support and facilitate the labelling process. Google Maps can also provide data primarily on facilities open to the public and on production (i.e., offices, schools, hospitals, homeless centres, theatres, factories). In addition, for each public facility and commercial activity, this tool offers additional information, such as its name, address, and opening times. In this work, this analysis was conducted on working days to hypothesize the flow of pedestrians in terms of residents (moving out from the area) and regular visitors or workers (moving into the area).
- Estimating the maximum admissible occupancy in terms of the number of people (pp), for buildings and open spaces in the BE: the geometrical characteristics of the adjacent buildings and open spaces intended were detected to determine the maximum number of pedestrians in the BE. In this sense, this work conservatively assumes that each user in the BE can be a potential pedestrian, thus being exposed to SLODs outdoors. BE users can be distinguished into indoor users, which are calculated as described below, and outdoor users, calculated by the method described in the next point. The occupant load factors (pp/m2) of the Fire Prevention Code (D.M. 3 August 2015) are employed to calculate the number of people in the building according to a quick approach to exposure assessment, since it varies depending on the use classes, as also suggested by conservative approaches of previous works [11]. Table 6 provides a brief overview of occupant load factors for outdoor areas, based on their typology. The total area of each building/open space is calculated using the Google Maps measurement tool (which allows calculating the areas directly on the map) and multiplied by the corresponding occupant load factor to obtain the maximum admissible occupancy.
- Assessing the additional crowding level of outdoor spaces: levels of services (LOSs) [3,74] are used to describe the presence of outdoor users, in particular, pedestrians using walking areas in the outdoor spaces, according to Section 2.1 analysis of the road layout [3,74]. Thus, this analysis attempts to include the additional burden in terms of people exposed as a result of walking activities that are not directly related to the use classes hosted within the evaluated BE. LOS A [75] (Table 6) is considered a reference for pedestrian areas to account for a standard area in which pedestrians can move freely without being restricted or influenced by others.
Intended Use of Open Spaces | Description | Quick Occupant Load Factor |
---|---|---|
Carriageway | Areas implying exclusive use of vehicles. | 0.0 pp/m2 |
Pedestrian Areas | Areas for exclusively pedestrian use assumed considering a low level of crowding in ordinary conditions (LOS A), during daylight hours. Users of these areas are considered “external users only”. | 0.1 pp/m2 |
Dehor | Generally related to outdoor areas of bars and restaurants. | 0.1 pp/m2 |
- Estimating the temporal variations of people exposed in the BE: the temporal variation of exposure is obtained considering the opening times of activities hosted in public buildings and open spaces described in Table 5 and the habits of the residents, according to the general rules of previous works [11]. The hourly values are then normalized for the maximum total value during the day, calculated between 0 and 1. In this way, these normalized values can also be used to directly compare the exposure profiles of the different LS or AS analysed. Then, pedestrian exposure E classes are divided into 5 classes, depending on the normalized value ranges, as represented in Table 7, thus assuming the same Pv number of classes for homogeneity purposes in the next RMA-based assessment tasks. It is worth emphasizing that this approach follows a conservative standpoint, in which we can assume that all the people hosted in the BE could potentially walk outside during each given daytime, thus being “potential” pedestrians.
Pedestrian Exposure E Classes | Range of Normalized Exposure | Risk Multiplier for E |
---|---|---|
I | lower or equal than 0.2 | 1.00 |
II | 0.2 (excluded) to 0.4 (include) | 2.00 |
III | 0.4 (excluded) to 0.6 (included) | 3.00 |
IV | 0.6 (excluded) to 0.8 (included) | 4.00 |
V | 0.8 (excluded) to 1.00 (included) | 5.00 |
- Assessing the social vulnerability in the BE: according to Section 1.2 literature overview, people are divided into 5 categories according to their age, habits and health conditions. Population census data, which are be available online for the given area [11], are used to quickly assess the distribution of people depending on their age, thus calculating their number in respect of the total number of pedestrians in the BE (see above). The social vulnerability based on such demographic groups is firstly associated with the exposure values by providing each of them a weight (w) based on their susceptibility to such hazard according to Equation (1), thus improving previous methods [11]:
2.3. Overall Risk Matrix Assessment
2.4. Presentation of the Case Study
- Average concentration of sensitive population (over 65 and under 5) and a fair concentration (highest in Città Studi) of schools and accommodation facilities for the elderly and disabled.
- Heavy density of public transportation.
- Low level of risk-mitigation strategies implemented due to low green coverage and high-level building density [79].
3. Results
3.1. Hazard Estimation and Physical Vulnerability
3.2. Exposure Peak and Social Vulnerability
- wb = 0.45
- wy = 0.20
- we = 0.31
- wad = 0.04
3.3. Risk Index
- wH = 0.50
- wP = 0.50
4. Discussion
- The data collected have been processed to obtain a series of synthetic criteria, easily interpretable and adaptable to any type of urban BE, as they can be derived using commonly used tools such as Google Maps. For example, green infrastructure can be assessed by observing the BE using Google Street View and noting the criteria outlined in Table 2.
- Matrix scale assessments (RMA) enable comparing the same AS/LS or several ASs/LSs in terms of specific features (i.e., each risk factor, and each parameter concerning vulnerability and exposure) and their response to SLODs (in a single and multi-risk perspective). In this sense, the method focuses on the aspects characterizing pedestrian risk, as it relies on the characterization of the space where pedestrians move and on the possible quantity of pedestrians using the BE.
- The parameters of the method can be further explored to create scenarios that can be analysed in more detail with simulation tools, both oriented towards pedestrian dynamics and SLODs modelling.
- In view of point 3, the single-risk-oriented assessment can allow decision makers (i.e., local authorities) to understand which of the two SLODs is more impactful in the analysed context, thus being able to address future risk-mitigation strategies. Similarly, the multi-hazard assessment can help them to recognize which of the ASs or LSs being analysed is the most risky and to identify the most appropriate response for each case. Nevertheless, a full comparison of the different ASs/LSs should shift from normalizing the exposure for each BE to normalizing the exposure for the maximum exposure in the BEs to be compared. In this case, the normalization of the exposure could take advantage of the pedestrian density in the outer areas, thereby having a single reference value for all the BE.
- The possibility of updating pollutant concentration and weather data through direct detection campaigns for each case study, including microscopic hazard assessment. In this sense, the approach proposed by this work can be also used by adopting a grid for the urban BE representation (e.g., 5 m × 5 m; 10 m × 10 m). This means that all the risk factors and parameters must be micro-scaled to note differences in the same AS/LS without changing the overall methodological approach.
- The integration of in situ analysis and measurements to improve the reliability of data on the specific scenario, or even their substitution with data collection from exclusively open source materials (i.e., Google Maps and Streetview), which are likely available in much of the industrialized world but that may not be so readily available in other countries. In particular:
- a.
- Introduce more information than the typical traffic fleet of the area analysed (vehicle type, power type, etc.).
- b.
- Use in situ analysis for pedestrian traffic level to improve the quantification of possible flows over the daytime, rather than using conservative but simplified assessment assumptions (i.e., “all the building occupants can be potential pedestrians at each time of the day”).
- c.
- In situ measurements to estimate actual albedo values, to consider separately the materiality and climatic characteristics of the analysed area. The use of the UTCI can be similar for different areas with diverse materiality and weather conditions, but not analysing them separately hinders planning and selecting mitigation strategies.
- Define different priorities in the risk-assessment tasks and goals by the decay managers who conduct different scenarios analyses using the AHP methodology. In fact, the AHP integration in the whole framework allows one to quantitatively assess the consistency of weights of the factors depending on the initial (e.g., literature-based) assumptions. For instance, the multi-risk index weights can be varied depending on the priority goals to be faced in the urban BE.
- Introduce additional social vulnerability factors rather than the sensitivity towards the SLOD effects, to include social, economic and cultural issues affecting the individual available resources to face ill effects of the environment.
- Introduce different exposure and social vulnerability scenarios, rather than using peak exposure and statistics on age at the whole district level. In this sense, probabilistic approaches could also be used to evaluate variations in the number of people in the BEs. Since this work relies on the assessment of typical working days, future works could apply the method to other typical scenarios to consider such as the weekend or holiday periods, during which user habits can be very different from the working days and business activities have different opening hours. Furthermore, these study conditions could be influenced by the contextual conditions in which the analysis was performed, i.e., restrictions to contain the COVID-19 pandemic that severely impacted pedestrians’ freedom of movement.
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Code | Description | Level of Comfort | Factor |
---|---|---|---|
A | Drivers do not suffer interference at their own gear, they have high possibilities of choosing the desired speeds (free). | Remarkable | 0.2 |
B | The higher density compared to that of level A begins to be felt by drivers who suffer slight conditioning to the freedom of manoeuvre and the maintenance of the desired speeds. | Discreet | 0.4 |
C | The freedom of travel of individual vehicles is significantly affected by mutual interference that limits the choice of speeds and manoeuvres within the current. | Modest | 0.6 |
D | It is characterized by high density but still by the stability of outflow; speed and freedom of manoeuvre are strongly conditioned; modest demand increases can create problems with the regularity of travel. | Low | 0.8 |
E | The average speeds of the individual vehicles are low (about half of those of level A) and almost uniform; there is practically no possibility of manoeuvring within the current; the motion is unstable since small increases in demand or small disturbances (slowdowns, for example) can no longer be easily reabsorbed by speed decreases and thus triggers congestion. | Very Low | 1.0 |
F | The flow is forced: this condition occurs when the traffic demand exceeds the disposal capacity of the useful road section for which there are queues of increasing length, very low runoff speeds, and frequent stops of motion. | Unrecognize | 1.2 |
Parameter | Description | Impact on the Decrease in Severity Levels | Impact on Pv |
---|---|---|---|
Increasing Temperature | |||
Green Cover | Includes the presence, type and effect of Green Infrastructures in the BE [46,59,60]. | H: areal or linear green (mitigating and adaptive effect) A: linear green, direct shade on the road, especially on sidewalks (local effect) L: green areas, parks or green areas that do not have a direct effect on the road (shade) but still have a mitigating function (well on the scale of the neighbourhoods, less on the local scale of the canyon) N: no type of green infrastructures present | The presence of green impacts the hourly variation of physical vulnerability, especially in the daytime. Therefore, it is further integrated concerning the newly defined combination. |
Albedo | The UTCI index [27] is used to assess the link between the external environment and human comfort [61]. | H: comfort (until 26°) A: moderate stress (27–31°) L: strong stress (>32°) | This parameter is the dominant variable in the Pv assessment. |
height/width ratio | The main dimensional ratios of the open spaces of the BE (geometry and morphological structure) are calculated, and then the temperature change and the orientation of the dominant direction of wind flow are assessed [62,63]. | H: height/width ≈ 1 A: height/width < 1 L: height/width ≥ 2 | This parameter defines the intermediate conditions of risk to be subdivided into three homogeneous subcategories. |
Air Pollution | |||
Traffic | Levels of traffic (Section 2.1) are detected in the various streets of the open spaces considered, taking as reference the worst daily combination among those observed (working week) [24,36,47,64]. | H: LoC REMARKABLE (code A) A: LoC DISCREET (code B) L: LoC MODEST (code C) N: LoC LOW or more (code D, E, F) | This parameter is the dominant variable in the Pv assessment. |
Elements that capture pollutants | The density, spacing and position (in rows or parks) of the trees are evaluated. The presence of hedges, as a barrier between the road to the sidewalk [8,35,38]. | H: hedges, trees with little thick crowns and well-spaced so as not to hinder wind flows (more pronounced effect in regular space, less in deep canyons) A: trees (same as “H”) L: trees with dense foliage or lack of green | The elements that capture pollutants, in particular the presence of green infrastructure, play an important action mitigating the pollution produced by traffic. Therefore, it is further integrated concerning the defined combination. |
Morphology and wind speed | The relationship between morphology and orientation of open spaces (LS and AS) with wind direction. To assess whether the conditions are favourable or unfavourable to the dispersion of pollutants [7,24,65]. | H: high buildings alternating with open spaces, parallel wind A: reduction in open spaces and lower buildings (continuous fronts) L: 45° wind or perpendicular to the dominant direction of the open spaces | This parameter defines the intermediate conditions of risk to be subdivided into three homogeneous subcategories. |
Physical Vulnerability PvH Classes for Increasing Temperature | Common Combination of [Green Cover; Albedo; Height/Width Ratio] | Risk Multiplier for PvH |
---|---|---|
Negligible I | [H; H; H] a,b or [H; H; A] a,b or [H; H; L] a,b | 1.00 |
Low II | [H; A; H] a,b [H; A; A] a,b [H; A; L] a,b | 2.00 2.33 2.66 |
Medium III | [A; L; H] a,c [A; L; A] a,c [A; L; L] a,c | 3.00 3.33 3.66 |
High IV | [L; L; H] c [L; L; A] c [L; L; L] c | 4.00 4.33 4.66 |
Extreme V | [N; L; H] c or [N; L; A] c or [N; L; L] c | 5.00 |
Physical Vulnerability PvP Classes for Air Pollution | Common Combination of [Traffic; Elements that Capture Pollutants; Morphology and Wind Speed] | Risk Multiplier for PvP |
---|---|---|
Negligible I | [H; H; H] a or [H; H; A] a or [H; H; L] a | 1.00 |
Low II | [A; A; H] a [A; A; A] a [A; A; L] a | 2.00 2.33 2.66 |
Medium III | [L; L; H] b [L; L; A] b [L; L; L] b | 3.00 3.33 3.66 |
High IV | [N; L; H] b [N; L; A] b [N; L; L] b | 4.00 4.33 4.66 |
Extreme V | [N; L; H] b or [N; L; A] b or [N; L; L] b | 5.00 |
Category | Examples | Definition and References | Code |
---|---|---|---|
sensitive | Schools, nursing homes, social welfare facilities, hospitals, etc. | Buildings characterized by social- or healthcare-intended uses imply the concentration of sensitive users due to their age or health fragilities [6,72]. The position of these places in the BE implies a local increase in vulnerability as frail health are more susceptible to increasing temperature and climate change [67,68]. | A |
commercial | Shops, bars, restaurants, etc. | Particularly attractive urban spaces/buildings thanks to the activities that can be carried out and the opportunity to meet people [69]. The fact that such buildings are often air-conditioned makes them strategic for sensitive users [70,73]. | B1 |
culture/ services | Universities, places of worship, culture and entertainment (churches, cinemas, theatres, museums, etc.), social services, sports services (gyms, sports centres), transport services (railway stations, airports, etc.) | B2 | |
business | Banks, insurance, research centres, private offices, professional studios, etc. | Buildings for public use and open to the public. The management activities (offices) and of service to companies and persons offering specialized services (professional offices, specialized clinics, sector shops, etc.). The ideal density of people is less than that of commercial activities, and there are mainly workers. | C |
production | Factories, local businesses, couriers, warehouses, construction sites, labs, workshops, etc. | Buildings mainly hosting private activities and, in any case, reserved for authorized occupants. | D |
residential | Homes, colleges, monasteries, hotels, etc. | The position of the houses in the urban context and the construction characteristics are dominant in the exposure [67]. The guests are mainly residents or people who spend a lot of time in these spaces. | E |
open spaces | Parks, squares, avenues, etc. | Open spaces are strongly influenced by weather, seasons, morphology and surface conditions. The intended uses of these spaces may vary on certain days of the week or seasons and change the crowding [71]: 1—Presence of events (markets, concerts, special events, etc.) 2—Everyday use | F |
Social Vulnerability Sv Classes | Range of Social Vulnerability Intensity | Risk Multiplier for Sv |
---|---|---|
Negligible I | 0 (included) to 0.25 (excluded) | 1.00 |
Low II | 0.25 (included) to 0.50 (excluded) | 2.00 |
Medium III | 0.5 (included) to 0.75 (excluded) | 3.00 |
High IV | 0.75 (included) to 1.00 (excluded) | 4.00 |
Extreme V | 1.00 | 5.00 |
Case Study | |||||||||
---|---|---|---|---|---|---|---|---|---|
Parameter | Characteristic | L1 | L2 | L3 | L4 | L5 | L6 | L7 | A1 |
Green Cover | Type of green infrastructure (areal) | Green park and trees | Green park and trees | - | - | Green park and trees | Green park and trees | Green park and trees | Green park and hedges |
Type of green infrastructure (linear) | Trees | Trees | - | - | - | Trees | - | Trees | |
Height/width ratio | 0.80 | 0.80 | 0.80 | 0.80 | 1.00 | 0.40 | 0.70 | 0.21 | |
Morphological Structure | Geographical Orientation | SO-NE | SO-NE | N-S | N-S | O-E | N-S | N-S | - |
Traffic | Type of road | Two-way | Two-way | One-way | One-way | One-way | One-way | Two-way | Both |
LoC (max) | D | D | D | C | C | C | C | C | |
Elements that capture pollutants (trees and hedges) | Deciduous trees | Deciduous trees | - | - | Deciduous trees | Deciduous trees | Deciduous trees | Hedges | |
Use classes | B1, B2, C, E | B1, B2, C, E | A, B2, E | A, B2, E | E, F | A, B1, B2, C, E, F | B1, B2, C, D, E | B1, B2, C, E, F |
Functional Classes | Target (Age) | % |
---|---|---|
Babies | 0–5 | 5% |
Young People | 6–18 | 11% |
Adults | 19–64 | 62% |
Elderly | 65+ | 22% |
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Salvalai, G.; Blanco Cadena, J.D.; Sparvoli, G.; Bernardini, G.; Quagliarini, E. Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach. Sustainability 2022, 14, 11233. https://doi.org/10.3390/su141811233
Salvalai G, Blanco Cadena JD, Sparvoli G, Bernardini G, Quagliarini E. Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach. Sustainability. 2022; 14(18):11233. https://doi.org/10.3390/su141811233
Chicago/Turabian StyleSalvalai, Graziano, Juan Diego Blanco Cadena, Gessica Sparvoli, Gabriele Bernardini, and Enrico Quagliarini. 2022. "Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach" Sustainability 14, no. 18: 11233. https://doi.org/10.3390/su141811233