The DTL describes the exposure conditions, in terms of airborne concentration and duration of exposure, which would produce a particular level of toxicity in the general population. One level of toxicity used by HSE in relation to the provision of land use planning (LUP) advice is termed the Specified Level of Toxicity (SLOT). HSE has defined the LUP SLOT as:

As discussed in by Turner and Fairhurst (1993), these criteria are fairly broad in scope, reflecting the fact that: industrial grade acetonitrile

Importantly, the criteria are also relatively easy for non-scientists to understand in terms of the overall health impact.

The toxicity expressed by a given substance in the air is influenced by two factors, the concentration in the air (c) and the duration of exposure (t). A functional relationship between c and t can be developed, such that the end product of this relationship is a constant:

This constant is known as the Toxic Load. In HSE, the Toxic Load relating to the LUP SLOT is known as the SLOT Dangerous Toxic Load or SLOT DTL. For a number of gases the relationship between c and t is simple:

Toxic Load = c x t

This relationship is sometimes known as the Haber law. As an example, animal toxicity data for methyl isocyanate indicates that the LUP SLOT is produced by each of these c and t pairs:

In this example the constant, or SLOT DTL, is 750 ppm.min (that is 150 x 5, 25 x 30, etc.).

However, the equation c x t = constant does not apply to all substances, so the following general equation has been developed:

For methyl isocyanate, n in the cn.t relationship is 1. In the case of sulphur dioxide, n = 2 and animal toxicity data suggest that the following pairs of c and t will each produce the LUP SLOT:

Here, the constant, or SLOT DTL, is 4.6 x 106 ppm2.min (that is 9652 x 5, or 3952 x 30).

How does HSE determine the c and t relationship, or DTL, which would produce the LUP SLOT for a given substance? In general, the absence of human data means that we rely heavily on animal data. If information is available concerning accidental chemical exposures to humans causing severe toxicity (comparable to the LUP SLOT), it usually lacks any quantification of the duration of exposure and associated inhalation conditions. Unfortunately the available, directly relevant animal data is also usually very limited. So, a pragmatic approach, based on the data that are most likely to be available, is adopted. This involves single exposure mortality data (usually LC50 tests over a known duration) designed to identify exposure conditions that produce mortality in 50% of a group of animals. The methodology is presented in detail in the Turner and Fairhurst (1993) paper, but some key points are noted here.

The starting point is to work from single, short-term (ie up to 4 hours duration) inhalation exposure studies in animals. In a real-life major accident situation, residents in the vicinity of a COMAH site might be exposed for a matter of minutes as the toxic cloud might be dispersed rapidly by wind. However, in some weather conditions, people could be exposed for a matter of hours. Looking at the SLOT criteria, it can be seen that they reflect exposure conditions just on the verge of causing a low percentage of deaths in the exposed population. Hence, we take conditions producing around 1% mortality in animals as being representative of SLOT conditions. To directly observe 1% mortality (LC1) a group size of at least 100 animals is needed, whereas group sizes of 5 or 10 rats or mice are typically used in routine toxicity tests. In deriving the DTL, the available acute toxicity data from different species is compared and the data from the most sensitive animal species is used, unless there are good grounds to consider that this would be inappropriate.

Where there are sufficient dose-response data points it might be possible to derive the 1% mortality conditions using probit analysis or estimate the values by judgement. Where insufficient data are available to do this, then we take a default approach of simply dividing the LC50 by 4. We should now have one value of t and one value of c, which when taken together represent an estimate of the exposure conditions producing the LUP SLOT.

The next step is to determine the value of n in the cnt = DTL equation. If the LC50 has been experimentally determined for several time periods, preferably within the same study, then n can be calculated using a linear regression approach. If there are no data to derive n, then n is usually taken to be 1, as a default position.

We can now insert the pair of c and t values representing one set of exposure conditions predicted to produce the LUP SLOT together with the value of n into the cnt = DTL equation. The DTL equation can be used to calculate all sets of exposure conditions that would produce the LUP SLOT.

A similar procedure can be followed to derive a toxic load equation to predict exposure conditions producing any other specified level of toxicity that may be of interest. For example a DTL relating to the mortality of 50% of an exposed population, a specified level known as the SLOD DTL, can be determined (see Franks et al 1996 for more information).

There are many limitations to the approach described above, such as difficulties extrapolating animal data to humans, lack of relevant toxicity data, the use of animal data of poor or unknown quality, frequent use of the default assumption that n in the cnt = DTL equation is equal to 1 and uncertainties about the universal applicability of the cnt concept. However, the described approach is probably the best that can be achieved with the available data and current state of scientific knowledge. HSE believes that it is important in regulatory toxicology to use consistent and transparent methodology, and this approach remains central to our DTL assessments.

Sometimes there is a need for a DTL for a substance with no acute toxicity data. One way around this problem is to base the DTL assessment on the known toxic properties of a structurally related substance- known as a read-across, or SAR approach. This is an uncertain process that requires a high level of professional judgement. Alternatively, it may be recommended that data relating to an exemplar substance be used. Exemplar substances are usually the most toxicologically potent substances among those that have previously been assessed by HSE. The exemplar should have similar physical properties (e.g. solid, liquid or gas) to the substance for which a DTL cannot be determined.

When preparing Safety Reports under the COMAH Regulations, authors are required to provide estimates of the extent (ie hazard ranges and widths) and severity (ie how many people are affected, including the numbers of fatalities) of the consequences of each identified major accident hazard. For an evenly distributed population, the number of fatalities resulting from a toxic release may be approximated by estimating the number of people inside the concentration contour leading to an LD50 dose (ie SLOD DTL). This approximation results from the assumption that those people inside the SLOD contour who do not die (due to factors such as physiology, fitness levels, etc) will be balanced by an approximately equal number outside the SLOD contour who do die (again, due to factors such as physiology, state of health etc.)

Further, the number of people injured (serious and minor) by the release may be approximated by the number people estimated to be between the SLOD and SLOT DTL contours (ie the SLOT DTL contour is taken as a pragmatic limit for injuries).

When estimating the numbers of people affected, authors should bear in mind that a proportion of the population will be indoors. This will provide a degree of protection against the effects of the release as compared to being outdoors. The level of protection is related to the rate at which air and toxic material enters the building and may be measured in air changes per hour (ACH). Models exist (see Davies and Purdy, 1986) to determine the outdoor concentration required to give an indoor SLOT or SLOD DTL dose. This (usually higher) outdoor concentration effectively defines the hazard range for people inside buildings.

Acrylic acid chloride, 2-Propenoyl chloride, Propenoyl chloride

2,2'-Iminodi-(ethylamine), N-(2-Aminoethyl)-1,2-ethanediamine

Propyl chlorocarbonate; Formic acid, chloro-, propyl ester; Carbonochloridic acid, propyl ester

Acetylene tetrachloride; sym-Tetrachloro ethane; 1,1-Dichloro-2-2, dichloroethane

Sulfinyl chloride, Sulphur chloride oxide, Sulphur oxychloride, Sulphurous dichloride, Sulphurous oxychloride, Thionyl dichloride

P Provisional value. Please refer to HSE for further details. Back to reference of note 'p'

1. Data available for carbon dioxide indicate that it does not meet the criteria for classification as a dangerous substance. Back to reference of footnote 1

Acetic acid HSE aims to reduce work-related death, injury and ill health.