Contents
Individual risk expresses the likelihood of a specified injury or death affecting an individual at a defined location or under defined exposure conditions. Barry describes it relative to a fire or explosion source. His location-based contours show the expected frequency of events capable of causing the specified harm, regardless of whether anyone actually occupies the location.[1]
The quantity therefore needs an explicit meaning before it can support a decision. A geographical measure for a continuously exposed hypothetical person differs from the risk experienced by somebody whose presence and protective actions vary. The ABCB Handbook also distinguishes individual risk from the likelihood of multiple deaths within a building. These measures answer related but different questions.[1][2]
An assessment combines the frequency of relevant scenarios with their potential consequences. Its numerical result remains conditional on the selected harm endpoint, exposure assumptions and evidence. Presenting the result as a contour, profile or single value does not remove those conditions.[3][4]
Defining the person, location and harm
The definition of harm sets the question being answered. A calculation concerned with fatality cannot be relabelled as a calculation of any injury. Barry notes uncertainties in fatal thermal, blast and toxic exposures. Assumptions and judgements about these endpoints require documentation, including when the assessment extends from fatalities to injuries.[4]
The exposure description is equally important. A location-based measure can describe the potential for harm at a fixed position without estimating the actual number of people present. This is useful for displaying a geographical pattern. It should not be interpreted as a population casualty estimate merely because the contour crosses an occupied area.[1]
An actual-person interpretation requires assumptions about the circumstances of exposure. Barry identifies population presence and the reliability of mitigation, including evacuation, when extending an assessment to people around a facility. These assumptions distinguish potential exposure from realised consequences. Their treatment needs to remain consistent between the scenario calculations and the reported risk measure.[4]
Within fire risk assessment, individual risk is therefore a defined output rather than a complete description of safety. It can identify locations or scenarios needing attention, but it does not describe every consequence of a fire. Property damage, interruption and the number of people affected may require other outputs alongside the individual measure.[3][1]
The ABCB Handbook lists simple tenability limits, fractional effective dose models and probit functions as forms of human exposure model. These categories describe alternative representations of human response. Their endpoint and interpretation need to be identified before using the outputs in an individual-risk calculation.[5][4]
Combining scenario frequencies and conditional harm
The basic calculation connects how often a scenario occurs with what follows when it occurs. Barry expresses risk as event frequency multiplied by expected consequence and describes summing contributions from selected scenarios. For individual harm, a conditional probability can represent the consequence term, provided its endpoint and exposure assumptions are specified.[3][6]
The following expression is a specialisation of that frequency–consequence approach. It represents the expected annual frequency of the selected harm at a location. The scenarios must be distinct contributions to the model, so that an initiating event and its own outcome branches are not counted twice.[6]
| Symbol | Meaning | Unit |
|---|---|---|
| R(x) | Expected frequency of the selected harm at location x | year−1 |
| fi | Frequency of distinct scenario i | year−1 |
| pi(x) | Conditional probability of the selected harm at x, given scenario i and the stated exposure assumptions | dimensionless |
| x | Defined location | location identifier or spatial coordinates |
Frequency and probability have different units. In this expression, a frequency per year multiplied by a dimensionless conditional probability produces a frequency per year. Calling that result an exact annual probability would introduce a further interpretation that the expression itself does not establish. The report should retain the quantity and units actually calculated.[3][1]
The scenario frequencies already need to incorporate the relevant sequence of events. If a frequency includes failed suppression, that failure should not be applied again within the same contribution without a clear reason. Barry's scenario approach connects initiating conditions, protection performance and outcomes before combining their risk contributions.[6]
Quantitative risk assessment supplies this broader structure. A single exposure calculation gives information about a consequence under selected conditions. It does not establish how often those conditions arise. Conversely, an initiating-event frequency cannot determine individual harm until the subsequent scenario and exposure have been represented.[3][6]
A numerical illustration
Consider three distinct hypothetical scenarios affecting one selected location. Assume a person is present there for the exposure represented in every case. The frequencies and conditional probabilities below are chosen solely to demonstrate arithmetic. They are neither incident data nor recommended design values.[6]
| Scenario | Frequency (year−1) | Conditional probability of harm | Contribution (year−1) |
|---|---|---|---|
| A | 0.001 | 0.10 | 0.000100 |
| B | 0.0002 | 0.50 | 0.000100 |
| C | 0.00005 | 0.90 | 0.000045 |
| Total | Not applicable | Not applicable | 0.000245 |
Scenario A occurs five times as frequently as B, but its conditional probability of harm is one fifth as large. Their contributions are consequently equal. Scenario C has the highest conditional harm probability but the smallest contribution because its assumed frequency is lower. Ranking consequences alone would therefore give a different order from ranking these risk contributions.[3][6]
The first two scenarios each contribute approximately 40.8% of the total; C contributes approximately 18.4%. These proportions can help identify which assumptions drive the result. They do not show which intervention is feasible, reliable or proportionate. Barry treats selecting risk-reduction measures as a subsequent analysis of the available options.[4]
For a second arithmetic case, reduce only B's conditional probability from 0.50 to 0.10. Its contribution becomes 0.000020 per year, and the total becomes 0.000165 per year. This illustrates consequence reduction with unchanged initiating frequencies. It does not demonstrate that a particular protection system can deliver the assumed change.[3][4]
Neither total establishes acceptability. No acceptance threshold, justified scenario frequencies or validated harm relationships have been supplied in this illustration. The example shows how inputs combine and how one selected change affects the output. A building or facility conclusion requires evidence for those inputs and an independently defined decision criterion.[6][7]
Profiles, contours and population measures
A risk profile plots a selected measure against distance or another specified spatial path. A contour connects locations having the same potential individual risk. Barry describes both presentations as ways to communicate the geographical distribution of fire and explosion risk. The harm endpoint and exposure convention must accompany either display.[1]
Contour geometry depends on the scenario analysis. The source presents an industrial layout with different activities and surrounding land uses, rather than a universal circular boundary. A schematic contour therefore cannot substitute for calculated exposure fields. Likewise, a profile along one direction does not describe every other direction around a facility.[1]
Societal risk additionally considers multiple casualties. Barry describes cumulative frequency–fatality curves and the information needed about the exposed population, its presence and mitigation. An individual-risk contour alone does not contain that population information. Two assessments can consequently have similar individual measures while involving different numbers of exposed people.[1][4]
The ABCB Handbook calls for individual and societal risk to be considered together in its comparative building strategy. This makes the distinction relevant even when the assessment compares two designs rather than mapping an industrial site. A design change affecting occupancy can alter the population consequence without an equivalent change in the potential harm at one location.[2]
Evidence, uncertainty and comparison
Scenario frequency estimates can draw on plant records, generic information and expert judgement. Barry discusses their quality alongside maintenance, testing and common-cause effects. A numerical estimate should therefore retain its origin and applicability. A rate drawn from another operating context is not automatically a measured rate for the installation being assessed.[8]
Uncertainty also enters the consequence calculation and the conversion from exposure to harm. Barry recommends documenting the judgements behind human-risk endpoints and discusses uncertainty bands when presenting results. Reporting many decimal places cannot compensate for uncertain inputs. The useful precision of the result depends on the evidence supporting the calculation.[6][4]
The purpose of the comparison determines which output is useful. Barry distinguishes comparisons of design, operational and protection options and warns against presentation that hides resolution or introduces bias. The same endpoint, exposure convention and scenario basis are needed to interpret differences between alternatives. A changed definition can otherwise appear as a changed risk.[4]
The ABCB Handbook illustrates a reference-building approach for deriving comparative individual and societal risk criteria. That historical framework does not provide a universal numerical limit for every building or industrial installation. The selected reference and departures need to be documented so the calculated difference can be related to the assessment's objectives.[7]
Risk reduction can address scenario frequency, consequence severity or both. Barry identifies equipment reliability, ignition prevention, detection and protection among the available approaches. The resulting individual-risk estimate remains conditional on their assumed performance. A useful report therefore connects the numerical result with the specific conditions and measures needed to maintain it.[4]
See also
Notes
- ↑ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 Barry (2002), p. 5-210.
- ↑ 2.0 2.1 Australian Building Codes Board (2020), p. 22.
- ↑ 3.0 3.1 3.2 3.3 3.4 3.5 3.6 Barry (2002), p. 5-176.
- ↑ 4.00 4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 Barry (2002), p. 5-211.
- ↑ Australian Building Codes Board (2020), p. 110.
- ↑ 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7 Barry (2002), pp. 5-208–5-209.
- ↑ 7.0 7.1 Australian Building Codes Board (2020), p. 44.
- ↑ Barry (2002), pp. 5-206–5-207.
References
- Australian Building Codes Board. (2020). Fire safety verification method handbook (Version 1.1).
- Barry, T. F. (2002). Quantitative risk assessment in chemical process industries. In P. J. DiNenno (Ed.), SFPE handbook of fire protection engineering (3rd ed., pp. 5-176–5-213). National Fire Protection Association.