With the increase in population, inhabited areas tend to grow closer and closer to industrialised regions, where these industrial zones often include chemical sites. As a result, governmental organisations started using Quantitative Risk Assessment (QRA) criteria to be able to decide whether risks to the exposed population are still acceptable or not.
For these regulatory QRAs, risk criteria like “Individual Risk” (chance of dying at a location due to a chemical accident) and “Societal Risk” (chance of having a large number of people dying) are being used. This way, a QRA has become an important instrument in urban development planning in many densely populated countries.
Individual Risk is typically illustrated using iso-risk contours on a map, while Societal Risk is drawn as an f-N curve which typically includes acceptance lines. However, the f-N curve concept is often difficult to comprehend by local authorities and land-use planners. That is why, a few years ago, the Dutch authorities identified the need for a geographic representation of Societal Risk, which would illustrate the most affected areas.
This blog post will provide some background about these geographic presentations of Societal Risk and explain how to interpret their results when using Gexcon’s risk modelling software RISKCURVES.
Societal Risk explained
Societal Risk is the cumulative probability per year that at least 10, 100 or 1000 people will be killed as a direct result of their presence within the impact area of an establishment and the occurrence of an event in which a hazardous chemical is involved.
Societal Risk is often presented as an f-N curve where F stands for frequency (/year) and N for the number of fatalities. A so-called “guide value” line can be drawn in the f-N curve to illustrate a maximum level as a risk acceptance criterion applicable. This guide value (black line in Figure 2) determines how many fatalities are accepted for different yearly frequencies. Unfortunately, there is no global consensus about what societal risk level can be considered acceptable. Therefore, the slope and the starting point of this guide value line might differ, depending on the local regulations and requirements.
The severity of a resulting f-N curve can be quantified using two additional concepts: the guide ratio and the expected value.
- The guide ratio reflects the ratio to the “accepted” guide value. If the guide ratio is, for example, 10, the risk acceptance criterion is exceeded by a factor of 10. A guide ratio lower than 1 would imply that the risk is (that fraction) lower than the acceptance line.
- The expected value is the area below the f-N curve. It is calculated by multiplying the total number of fatalities by the yearly frequency of the loss of containment scenarios. Therefore, it provides the expected number of yearly fatalities for the scenarios. This expected value is also typically referred to as “Potential Loss of Life” (PLL).
Unfortunately, the Societal Risk f-N curve is a rather simple 2D graph, which merely illustrates “acceptable risk” or “not acceptable risk”. However, the origin of problems is completely obscured. Consequently, local authorities and land-use planners often find it difficult to comprehend.
Although it is created using geographically distributed population and location-specific accident scenarios, the f-N graph does not give any information on where this happens (which population contributes to this Societal Risk) or which areas are safer or less affected by Societal Risk (still having the possibility for urban development).
That is why a few years ago, an area-specific visualisation for Societal Risks, called “Societal Risk Maps”, were developed, and implemented in Gexcon’s QRA software RISKCURVES.
The use of Societal Risk maps
The geographical presentation of Societal Risk is very convenient as it gives information such as:
- Where are larger numbers of people being threatened by a potential accident?
- Which population is contributing to the Societal Risk?
- How much space is available to start urban development without exceeding Societal Risk limits?
- Which areas are safer or less affected by urban development?
Societal Risk Maps are exclusive of RISKCURVES and allow the user to quickly validate, for instance, the influence of a change in population distribution as a result of urban development plans. Societal Risk Maps are not a new risk criterion but a visualization method to geographically represent Societal Risk.
Since risks from transport activities are also incorporated, it is also possible to vary transport intensities or changes to transport routes. The geographical feedback provided by the maps appeared to be very useful in the communication between risk evaluation experts and spatial planners.
Types of Societal Risk maps
There are two types of Societal Risk Maps implemented in RISKCURVES: Societal Risk Area Map and Societal Risk Contribution Map.
Before defining those two, it is important to understand that this type of Societal Risk considers risks from the receivers’ perspective, not from the perspective of the source causing the risks. Thus, the f-N curve for a location refers to the Societal Risk of all scenarios reaching that location. This makes quantifying aggregated risk from various sources (both transport and stationary) possible.
Societal Risk (SR) area map
What is it? The SR Area Map is a geographical representation that illustrates the societal risk level for scenarios that affect areas on the map. The colours in the map represent the guide value ratio of the f-N curve for that location.
Interpretation: This map is presented using colours illustrating Societal Risk ranging from low (green) to high (red):
- Red coloured areas represent the regions with a Societal Risk above the risk acceptance criterion. Thus, the corresponding f-N curves for each geographical grid are above the guide value.
- Green coloured areas represent the regions that do not pose a threat in terms of Societal Risk. Thus, the corresponding f-N curves for each geographical grid are below the guide value.
- Orange coloured areas represent the limit of the risk acceptance criterion. Thus, the f-N curves on each of those geographical grids are right on top of the guide value.
Application: The SR Area Map is often used as an urban development planning tool as well as to understand the geographic distribution of Societal Risk. The Societal Risk Area Map will highlight the areas that present problems and still have the potential for population growth.
Societal Risk (SR) contribution map
What is it? The SR Contribution Map is a geographical representation of which areas contribute the most (in relative terms) to the Societal Risk. Therefore, it shows the “hotspots” that might potentially pose a threat in terms of Societal Risk.
Interpretation: The areas having a higher contribution to the Societal Risk will be more red. However, those red areas do not necessarily have a corresponding f-N curve that exceeds the risk acceptance criterion (i.e., the guide value). A red area merely indicates that it contributes a lot (or highly) to the total Societal Risk. Therefore, the colour applied in SR Contribution Maps should be regarded as a “relative contribution” to the existing Societal Risk around that location.
Application: The SR Contribution Map is typically used for emergency response and risk reduction. It indicates which population areas need focus in preparation plans or considering risk reduction measures (potentially leading to the relocation of activities or population).
Societal Risk maps in RISKCURVES
The figures below show multiple examples of how these two geographical representations provide different valuable information.
Rail transport through a city
The figure below illustrates the SR Area Map (left) and the SR Contribution Map (right) for the same scenarios of rail transport through the city of Dordrecht.
The SR Area Map (left) shows a specific local orange / red area around the transportation route having a Societal Risk exceeding the risk acceptance criterion. This situation is created by short-distance high consequence BLEVE fireball scenarios combined with toxic scenarios reaching larger distances, thus, affecting a larger populated area.
The SR Contribution Map (right) shows the areas that contribute the most to the total Societal Risk, which has the highest population density. The red areas do not necessarily exceed the risk acceptance criterion but provide very valuable information on where evacuation actions should focus. In contrast, risk reduction actions around those locations are most effective.
Evaluation of change in population density
A very common situation where SR Maps come in handy is to evaluate how the addition of several apartment buildings would affect the Societal Risk, as there is a nearby industrial facility.
The f-N curve below compares Societal Risk for the old population and the expanded population.
It is clear from the f-N curve that Societal Risk increases when the population is expanded. However, how do urban planners decide whether it is safe to expand the population? And if so, which areas are safer or less affected by the surrounding industrial activity? The answers to these questions cannot be found in the results provided by the f-N curve.
That is exactly the type of situation where SR Maps come in handy. The figure below shows the SR Area Map for the current population (left) and the expanded population (right).
This geographical representation shows very clearly how the expansion of population affects the total Societal Risk and which areas are the most affected by this.
Rotterdam study
The figure below illustrates a conceptual study of the city of Rotterdam where several dangerous activities, including LPG road transportation, were evaluated.
The SR Contribution Map (right) clearly showed the areas affected by LPG transport (i.e., little red dots), which are the areas that exceed the risk acceptance criterion for road transportation. This was caused by the fact that LPG transport (involving a potential BLEVE scenario) occurred on a highway very close to densely populated areas.
However, it wasn’t until all scenarios were evaluated in an SR Area Map (left) that other scenarios significantly contributed to the total Societal Risk. This SR Area Map showed that at the centre of the harbour, the (un)loading and storage of a highly toxic substance was also leading to a very high number of victims, which affected a huge portion of the city. Thanks to this study, it was possible to conclude that no further urban development could take place within the entire city.
What often happens for toxic dispersion events is that although the toxic cloud may reach a vast area, the actual lethality for the exposed zone is limited (because many people will be partially protected because they are staying indoors). However, that still leads to many fatalities affecting a substantial area of the city, which was only shown when the SR Area Map was evaluated.
These two different ways of representing geographical societal risk helped the government in different ways:
- The SR Area Map (left) helped plan urban development and pinpoint safety problems.
- The SR Contribution Map (right) helped with emergency response planning, to pinpoint areas for redevelopment or relocation of population, and as guidance for rerouting the LPG transport.
