GB2334575A - Environmental monitor and alarm having an updated allowable measurement range - Google Patents

Abstract

An environmental monitor (10) repeatedly takes a sample from a substance to be monitored and measures a parameter of that sample. The value of the parameter is stored in a memory (32). Once a number of measurements have been made and stored in the memory (32), a calculator (34) within a processor (30) generates a range of permissible values based upon the stored measurements. The processor (30) compares subsequent measurements with the permissible range and, if a given value lies outside the range, an alarm (40) is triggered. In a first embodiment, the range is updated each time a new measurement is made. In an alternative embodiment, the range is only updated when the alarm (40) is triggered. The monitor (10), which is particularly suitable for monitoring the toxicity of waste and potable water supplies, thus provides a moving window of control limits, to minimise the risk of false alarms from naturally occurring background variations in the parameter measured. The measured parameter may be a bio-luminescent signal.

Description

Environmental Monitor This invention relates to an environmental monitor, and particularly, but not exclusively, to a monitor for toxicity in water.

Toxicity is a general term used to describe an adverse effect on a biological system. Toxicants (synthetic chemicals that are toxic) and toxins (natural poisons), cause toxicity. By definition, toxicity can only be measured as a response in a biological system, so chemical estimates of a toxicant cannot be related to the toxic effect of the chemical.

Synergism and antagonism are important concepts in toxicity, whereby mixtures of chemicals may have a greater or lesser effect on an organism than the sum of the effects of the components. For example, the toxicity of phenol is greatly increased in the presence of salt, so chemically identical concentrations of phenol can have widely different toxicities dependent on the other components of a mixture.

Because toxicity is a measure of a response in a biological system, there are several ways of defining it.

In general, toxicity is measured by exposing an organism (e.g., a fish) to different concentrations of a chemical and scoring the effect to produce a dose response curve (i.e., the effect/response plotted against the concentration/dose).

There are, in fact, a number of tests ranging from whole organisms down to single biological molecules, and a range of responses ranging from death to inhibition of an enzyme reaction, that are used to score toxicity. It is also usual to include the exposure time as a fixed parameter in these sorts of measurements.

Toxic effects are divided into acute (usually scored by death) and chronic (usually scored by a change in behaviour over an extended period of time) effects. The most usual measure of toxicity is the effective concentration (EC) or inhibitory concentration (IC) value. The EC/IC value is denoted as a percentage response, e.g., EC50, and EC10 and denotes that concentration (dose) that affects the designated criteria (e.g., death, behaviour trait) in the proportion of the population indicated. That is, EC50 = 10pom indicates that 50% of the population will be affected by a concentration of 10pom.

EC/IC values are usually extrapolated from a dose response curve, and are always associated with an exposure time.

Other measures of toxicity include the N(O)EC = No (observed) effect concentration, the highest concentration that has no effect on the chosen criteria, and the L(O)EC = Lowest (observed) effect concentration, the lowest concentration that has an effect on the chosen criteria. Observed is inserted because it is impossible to provide a negative response, i.e., No effect. Another less popular measure of toxicity is the effective time (ET) or inhibition time which is the time taken to affect a proportion of the population, i.e., ETso = 5 hours indicates that at a fixed concentration it will take 5 hours of exposure for 50% of the test population to be affected.

Clearly, toxicity must be measured biologically and the units of measure are derived values that will have a natural variation associated with the variability of the biological test system.

Toxicity is not always measured as a decrease or death. Some toxicants can increase a parameter, e.g., heart rate, and there is a well established effect called hormesis whereby some chemicals which are inhibitory at high concentrations become stimulatory at low concentrations.

Yet another unit of measurement of toxicity is called gamma (y) and is a normalised ratio of the amount of toxic effect on a sample in comparison with a control sample.

Measurement of toxicity is particularly important in waste water treatment plants and main potable water supply lines. In waste water treatment plants, the influent waste water toxicity is measured. This is to protect the biological treatment plants within the waste water treatment plant from the harmful and expensive effects of an unexpectedly toxic intake.

Typically, the toxicity of the influent to a waste water treatment plant is high, and the sample tested for toxicity is therefore diluted. On the other hand, in potable water supply lines, the toxicity is often low, and no further dilution is therefore necessary.

Commercially available toxicity monitoring equipment is often arranged to draw samples directly from the water or waste, and operates in the following manner.

A sample is drawn automatically from the influent of a waste water treatment plant (and diluted accordingly) or from a potable water supply line. For example, the MicrotoxTM-OS, manufactured by Siemens Environmental Systems Ltd, and supplied by Azur Environmental USA, of Carlsbad, California, USA, samples the water every 17-20 minutes. In the MicrotoxTM-OS, the toxicity is determined by measuring the effect of a toxicant on the bioluminescence of the marine bacterium Vibrio fischeri and then measuring the increase, or more usually the decrease, in the light output from these bacteria.

Although any of the measurement units described above may be used, it is preferable in this case to express the toxicity in terms of gamma. Here, gamma is simply the ratio of the light emitted by the control sample to the light emitted by the test sample. The ratio is shifted such that gamma is zero when the light in the test sample equals the light in the control sample. Mathematically: y=(light in control sample/light in test sample) - 1 Thus, gamma may range from negative values, where the test sample is stimulated by the toxicant, to large positive values (in theory, gamma may tend to infinity, but in practice it is seldom greater than 100) as the light in the test sample becomes low after toxic exposure. In order to allow comparison, gamma is quoted together with an exposure time. A typical exposure time in a waste water treatment plant or a potable water supply line is 5 minutes.

Once gamma is determined, it is compared with preset boundary limits. Thus, if gamma as measured by the equipment is greater than an upper limit, indicating a higher than acceptable toxicity, an alarm may be sounded to warn operators in the waste water treatment plant of a risk to the biological treatment plants. Although a background toxicity in such plants can be tolerated, it is important that the maximum toxicity that can be tolerated is determined. The influent can then be manually or automatically diverted away if that limit is reached.

Similarly with a monitor in a potable water supply line, an alarm can be raised if toxicity becomes greater than a preset amount, and a controller can then shut down that line to avoid a public health risk.

There are significant problems with this approach to toxicity detection, however.

It will be appreciated that setting the boundary limits in the monitoring equipment is of great importance. If the upper limit, for example, is set too low, there may be an unacceptably high number of false positive alarms, thus causing the system to be uneconomic. If on the other hand the upper limit is set too high, too many toxic events are missed and the value of the system is lost.

The toxicity is measured on biological matter, and gamma is a derived value that has a natural variation associated with the variability of the biological test system. In other words, the toxicity value gamma varies, usually in a cyclical manner, due to environmental influences (temperature, machine noise, temporal variations) that are not regarded as toxicity. The amplitude of the variations is usually random, however.

In order to determine the fixed alarm level to be set, the background gamma is first measured. Should this be measured at the trough of one of the cycles, an upper limit may then be set on the equipment which is in fact lower than the background gamma at the peak of its cycle. Conversely, if the background gamma is measured during a period of unusually variable background data there is a risk that the boundary limits may be set too far apart. Toxic events may not then be identified as they fall within the limits previously determined to be background only.

It is therefore an object of the present invention to provide an improved environmental monitor which alleviates the problems of the prior art.

According to the present invention, there is provided an environmental monitor comprising detector means arranged repeatedly to measure the value of a parameter of a substance to be monitored, and processor means including calculating means for generating a permissible range of measured values, based on the measured values, and comparator means for comparing a measured value with the calculated permissible range, the monitor being arranged to actuate an additional means when the measured value lies outside the permissible range of values, the processor means being arranged to update the permissible range, in dependence upon the measured values, as further values are measured.

Thus, the range of acceptable values of the parameter is a moving window which shifts as further values are measured by the detector means. The risk of the range being too large or too small is thereby minimised, since the range is reset as further measurements are made. Additionally, the moving window allows natural, as opposed to special, variations in the parameter to be taken into consideration. In the preferred embodiment, the monitor is adapted to monitor the toxicity of a substance, suitably by measuring the value of gamma.

The technique used to set the boundary limits (known as the upper control limit (UCL) and lower control limit (LCL)) in the present invention is known as Statistical Process Control. It is used as a method of quality control in manufacturing processes, where it is important to maintain a product within acceptable tolerances. The chief purpose of SPC in the manufacturing environment, however, is to allow a controlled process to be improved. In the preferred embodiment of the present invention, the process is not under control, and there is no desire to improve the background gamma, for example.

Further detail of SPC in manufacture is given in, for example, "SPC and Continuous Improvement", by M.H.

Owen, IFS, Bedford (1989).

Preferably, the processor means updates the permissible range only when the monitor indicates that a measured value lies outside the range. Thus, the value of each measurement is compared with a first permissible range until a value lies outside the permissible range. Most preferably, this value is the most recent one measured. Then, a second permissible range is calculated, and the value of subsequent measurements is compared to the second permissible range, and so forth.

The processor means may update the permissible range on the basis of a next predetermined number, n, of measured values once the monitor has indicated that the most recent measured value lies outside the range.

For example, the next 20 measurements may be employed.

In an alternative embodiment, the processor means may update the permissible range each time the detector means measures a further value, for example on the basis of a last predetermined number, n, of measured values. Most preferably, n is 20.

In yet a further preferred embodiment, the processor means updates the permissible range each time the detector means measures a further value, provided that the further value does not lie outside the permissible range. Thus, for example, the processor means may exclude values lying outside the permissible range when generating an updated permissible range. This minimises the risk of subsequently generated permissible ranges being "skewed" by including measured values that were significantly outside the permitted range.

Preferably, the processor means updates the permissible range on the basis of a last predetermined number, n, of measured values that do not lie outside the permissible range. For example, n may be 20.

The monitor may further comprise storage means for storing the measured values of the parameter, the processor means updating the permissible range on the basis of the stored measured values.

Furthermore, the monitor may also comprise a first alarm arranged to be triggered when the comparator means determines that a measured value lies outside the permissible range. In the case where the monitor is monitoring the toxicity of potable or waste water supplies, the first alarm permits an operator of the monitor to shut down the supplies to avoid public health risks in the former case and damage to biological treatment plants in the latter case.

Preferably, the monitor includes a second alarm arranged to be triggered when each of a predetermined number, m, of sequentially measured values is larger than the previously measured value in the sequence.

The second alarm may be arranged to be triggered additionally, or alternatively, when each of the predetermined number, m, of sequentially measured values is smaller than the previously measured value in the sequence.

The second alarm indicates to an operator that there may be an imminent potential hazard, and allows him to plan for a shutdown of potable or waste water lines, for example.

Preferably, the calculating means calculates the mean value of the measured values, the mean value of the difference between consecutive measured values, and the standard deviation of the difference between consecutive readings, the permissible range being between the mean value of the measured values plus 3 standard deviations, and the mean value of the measured values minus 3 standard deviations.

When measuring toxicity, the use of 3 standard deviations gives a 99% confidence limit that a measured value lying outside the permissible range is genuinely due to an unacceptably high toxicity level.

That is, the probability of a false alarm caused by background toxicity is 1%. Other confidence limits may be used, such as one or two standard deviations.

A third alarm may also be included in the monitor. This is preferably arranged to be triggered when the proportion of values within a middle one third of the permissible range differs from the proportion within the remaining two thirds of the permissible range by more than a predetermined amount.

If two thirds of the results fall either outside or inside one standard deviation either side of the mean, this is an indication that the control limits need to be reassessed. The third alarm, in conjunction with the above calculations by the calculating means, permit the permissible range to be narrower when there is a small background toxicity. Conversely, the permissible range is wider when the background variation is high. Applying a narrower range to an uncontrolled process tends to generate more false alarms.

The invention also extends to a waste water treatment plant, or a potable water supply line, including such a monitor.

Furthermore, the invention may extend to a method of monitoring a substance, comprising repeatedly measuring the value of a parameter of the substance, generating a permissible range of values based upon the measured values, comparing a measured value with the permissible range, and actuating additional means when the measured value lies outside the permissible range, the permissible range being updated, based upon the measured values, as further values are measured.

The method is particularly suited to the monitoring of toxicity in water, such as in waste water treatment plants and potable water supply lines. Of course, the system may be applied to any suitable continuous online detector.

The invention can be put into practise in various ways, and one preferred embodiment will now be described with reference to the accompanying drawings in which: Figure 1 shows a schematic diagram of an environmental monitor according to a preferred embodiment of the present invention; Figure 2 shows a flow chart setting out a first mode of operation of the monitor of Figure 1; Figure 3 shows a flow chart setting out a second mode of operation of the monitor of Figure 1; Figure 4 shows a flow chart setting out a third mode of operation of the monitor of Figure 1; Figure Sa show a graph of toxicity versus time, with permissible toxicity limits generated by a prior art environmental monitor, for a first supply of waste water; Figures 5b, Sc and 5d show graphs of toxicity versus time, with permissible toxicity limits generated by monitors operating in first second and third modes respectively, for the first supply of waste water; Figure 6a show a graph of toxicity versus time with permissible toxicity limits generated by a prior art environmental monitor, for a second supply of waste water; Figures 6b, 6c and 6d show graphs of toxicity versus time, with permissible toxicity limits generated by monitors operating in first second and third modes respectively, for the second supply of waste water; Figure 7a show a graph of toxicity versus time with permissible toxicity limits generated by a prior art environmental monitor, for a first supply of potable water; Figures 7b, 7c and 7d show graphs of toxicity versus time, with permissible toxicity limits generated by monitors operating in first second and third modes respectively, for the first supply of potable water; and Figure 8 shows the graph of Figure 5d, with certain data points highlighted.

Referring to Fig. 1, a monitor 10 comprises a housing 15 having a sample inlet 20. The sample inlet 20 takes samples on a regular basis from the substance to be monitored. In the present example, the sample is taken either from a potable water supply line, or from the influent of a waste water treatment plant.

In the latter case, there is always a level of acceptable toxicity, and the operator of the monitor therefore chooses a suitable dilution to "force" a gamma measurement that is effectively zero. This level of dilution denotes an acceptable background. In any event, sample dilution is important as high levels of toxicity in the influent can have a detrimental effect on the bacteria used to measure toxicity (and indeed, on the biological treatment plant employed in the waste water treatment plant) On the other hand, in the case of potable water, there is no acceptable background toxicity and all significant results must be flagged. It is therefore more important with potable water supplies to maximise sensitivity, so that no dilution of the sample is preferable.

The monitor 10 also includes a toxicity measurement device 25, such as the MicrotoxTM-OS previously described, which measures the toxicity of the sample, suitably diluted if necessary.

In the following description, the Vibrio Fischeri bacterium is used to measure the toxicity of the water in terms of gamma, in the manner set out above. Of course, other methods for measuring toxicity, and other units of measurement, can be employed, such as EC50, percentage change, ET, NOEC, LOEC and so forth, as described above. However, gamma is preferred as it may determined from a single sample, whereas the other toxicity units require several tests on a range of sample dilutions.

Before commencing measurements proper, the sensitivity of the monitor 10 is adjusted, in a "learning" :.ode. Samples are taken sequentially at increasing dilution until the toxicity, gamma, is measured at zero. This dilution is then employed for all subsequent measurements, unless an unusual pattern of measurements arises, at which point, the dilution employed may be reviewed, as will be explained.

Once gamma has been measured by the toxicity measurement device 25, the measured value is output to a processor 30, where it is stored in a memory 32. The memory 32 may be volatile, such as a RAM, or it may be a physical storage device such as a magnetic disc.

After a predetermined period, a further sample is drawn into the sample inlet 20, and its toxicity is measured by the toxicity measurement device 25. The toxicity thus measured is also sent to the memory 32 in the processor 30, where it is stored at a different address to the previous measurement. The cycle is continuously repeated to permit monitoring over extended periods.

The cycle time between measurements of toxicity is, in the present example, between 17 and 20 minutes.

This allows the water to be monitored over a period of several days, if desired. In addition, and as will be described below, using a cycle time of about 20 minutes typically enables the monitor 10 to follow the cyclical variations in the background gamma.

Nonetheless, other time periods may be used.

In addition to the memory 32, the processor 30 also includes a calculator 34 and a comparator 36.

Once a number of sample measurements have been collected and stored in the memory 32, the calculator 34 calculates the mean of the stored measurements, and a permissible range around that mean. The mean gamma, and the upper control limit (UCL) and lower control limit (LCL) are then output to a latch or register within the comparator 36. once the latch has been loaded, measurements subsequently made by the toxicity measurement device 25 are sent both to the memory 32 within the processor 30 and, simultaneously, to the comparator 36. The comparator 36 then compares the most recent sample gamma measurement with the UCL and LCL held in the latch. If the most recent measurement lies outside these values (i.e., above the UCL or below the LCL), then a signal is sent to trigger a first alarm 40.

This indicates that the most recent toxicity measurement exceeds the control limits calculated by the calculator 34.

As additional measurements are made on further samples, the calculator 34 repeatedly updates the UCL and LCL on the basis of previous values stored in the memory 32. In other words, as new measurements are made by the toxicity measurement detector 25 and sent to the comparator 36, they are compared against a repeatedly updated UCL and LCL held in the latch in the comparator.

As described above, the first alarm 40 on the monitor 10 indicates when the most recent gamma measurement exceeds the range of permitted gammas between the UCL and LCL. However, further secondary alarms can be included within the monitor 10 as well.

For example, in addition to comparing the most recent gamma measurement to the UCL and LCL held in its latch, the comparator 36 may also compare that most recent measurement with the mean gamma. A second alarm 50 is triggered when the comparator notes a run of a predetermined number of measurements that are all above or all below the mean gamma. Such an alarm might indicate to an operator of the monitor, that the toxicity of the water being monitored is significantly increasing or decreasing, and that action may soon become necessary, or that the sample dilution employed needs to be reviewed.

Using a predetermined number of measurements all above or all below the mean gamma minimises the risk of the second alarm 50 occurring simply due to random fluctuations in the toxicity.

Alternatively, the second alarm 50 can be triggered by a predetermined sequential number of measurements of gamma, each being larger or smaller than the previous measurement. Thus, for example, the comparator may poll the memory 32 for the last seven stored measurements, and when it notes that the previous measurement is larger than the penultimate measurement which in turn is larger than the prepenultimate measurement etc., it may trigger the second alarm 50.

Finally, the monitor 10 may comprise a third alarm 60. This alarm is triggered when there is an unusual pattern or trend, but within the bound'aries of the UCL and LCL, or when the proportion of results within the middle third of the acceptable region (between the UCL and LCL) differs excessively from the remaining two thirds. The relative proportions are a consequence of the manner in which the permissible range is calculated, as explained in further detail below.

This third alarm 60 indicates that the monitor settings and/or dilution level of the sample needs to be reviewed.

Having described the general operation of the monitor 10, a more detailed description of the different modes of operation of the monitor will now be described, with reference to Figures 2, 3 and 4.

Referring to Figure 2, a first mode of operation of the monitor of Figure 1 is shown in the form of a flow diagram. At step 100, when the monitor is first set up to begin monitoring, the processor 30 re-sets a count of the measurement number, m. That is, m = 1.

Next, at step 110, the monitor 10 takes a first measurement gamma(l). This is stored at a first address in memory 32. Approximately 20 minutes later, a further sample enters the sample inlet 20 of the monitor 10, and a second measurement of toxicity, gamma(2) is measured by the toxicity measurement detector 25. This, again, is stored in the memory 32, at a second address.

The monitor repeatedly takes further samples gamma(3), gamma(4) etc., storing each in a separate address in memory 32.

At step 120, and once n measurements of gamma have been taken and stored in memory 32, the calculator 34 calculates the UCL and LCL on the basis of the stored measurements. As previously described, the UCL and LCL are the maximum and minimum permissible values of gamma, respectively.

The UCL and LCL are calculated on the basis of an "X/moving R" analysis. The basic calculations are as follows: If each of the n stored values of gamma is labelled X, and the difference between two consecutive measurements of gamma is R (X and R are both variables), the calculator 34 calculates the mean X (X (BAR)) and the mean R (R(bar)). X(BAR) is simply the sum of the measurements X divided by n, and R(BAR) is the sum of the differences between two consecutive measurements divided by (n - 1).

Next, the calculator determines the standard deviation, a. a is calculated as R(BAR)/1.128, the numerical constant being taken from statistical tables for a sample size of 2 (two consecutive readings).

Finally, the calculator calculates the UCL, which in this example is X (BAR)+ 3a, and the LCL, which is X(BAR) - 3a. Other confidence limits may be employed.

Returning to Figure 2, once the UCL and LCL have been calculated by the calculator 34 at step 120, the next measurement of gamma takes place at step 130. In practice, the calculation carried out by the calculator 34 is extremely rapid, and certainly shorter than the time difference between consecutive samples.

The UCL and LCL are sent to the latch in the comparator 36, as previously described. At step 140, the comparator 36 compares the most recent measurement, gamma(n + 1) with the UCL and LCL in the latch.

If the comparator determines that the most recent measurement, gamma(n + 1) is within the acceptable control limits, then the counter is advanced at 150, and the next measurement is taken. Provided the subsequent measurements of gamma all lie within the upper and lower control limits, the latch in the comparator 36 continues to store the UCL and LCL first determined, i.e., on the basis of the first n measurements made.

However, if at step 140, the comparator 36 decides that the most recently measured gamma value is above the UCL or below the LCL, then, at step 160, the first alarm 40 is triggered. This indicates to an operator of the monitor that an unacceptably high toxicity value has been measured, based upon the previously calculated control limits.

Simultaneously, the processor 30 suspends further external triggering of the first alarm 40. For example, a bistable or flip-flop 38 can be forced from a first, "off" position into a second, "on" position following the detection of a measurement outside the control limits, so that the first alarm 40 remains on until it is re-set, as explained below.

At step 170, the toxicity measurement detector measures the gamma of the (n + 2)th sample. Although the processor 30 has suspended the operation of the first alarm 40 in an "on" state, the previously determined UCL and LCL are still held in the latch of the comparator 36. The (n + 2)th measurement is compared, at step 180, to these previously determined control limits. If the (n + 2)th measurement is still outside the previously determined control limits, then, at step 190, the measurement number is incremented by 1, and the next sample is measured.

This next sample is then also compared against the previously determined control limits and the loop continues until a measurement within the control limits in the latch is determined.

Once the alarm has been triggered at step 160, the processor follows the loop described between steps 170 and 190 until the toxicity of the next measurement made is within the control limits previously determined. When this determination is made at step 180, the system re-sets itself, that is, in terms of the flow diagram, returns to step 100.

The following steps are taken at this stage.

Firstly, the first alarm 40 is re-set into its "off" state, by flipping the bistable 38 once more.

At the same time, the measurement count is re-set to 1, and the latch in the comparator 36 is cleared. The monitor 10 then takes another set of n measurements before determining a new UCL and LCL on the basis of the n measurements taken since the alarm and latch were re-set.

Of course, it is not necessary to empty the memory 32 of previously stored values, which may be useful for diagnosis purposes.

It has been found that an initial value for n of 20 is particularly suitable for carrying out an analysis on potable or waste water using the MicrotoxTM-OS toxicity measurement detector. Using this example, the monitor 10 measures and stores the first 20 toxicity measurements, calculates a UCL and LCL on the basis of the first 20 measurements, and then compares the 21st measurement against the UCL and LCL first calculated. Provided the 21st, 22nd, ... measurements all lie within the UCL and LCL, i.e., the algorithm follows the loop between 100 and 150, then each subsequent measurement number 21, 22 ... is measured against the UCL and LCL calculated from the first 20 measurements.

If, on the other hand, the 21st measurement (step 130) is outside the control limits (step 140), the monitor 10 measures the 22nd sample at step 170. At step 180, if the 22nd sample measurement is outside the control limits, then the count increments by 1 at step 190 so that, at step 170 again, the 23rd sample is measured. If the 23rd measurement lies outside the control limits, the count is incremented once again at 190 and, returning to step 170, the 24th measurement is made and so forth.

Once a measurement within the previously determined control limits occurs, then the counter is reset to 1 (step 100) and the process starts again.

The previously stored values can either be shifted to new addresses within the memory 32, or a new block of addresses labelled 1 to n can be used for the next data set.

When operating in the manner described above, the monitor thus continually sets and re-sets the control limits, a measurement lying outside the previously determined control limits triggering an alarm and also causing the processor to re-calculate a new set of control limits. A monitor operating in this first mode (shown in the flow chart of Figure 2) can thus take account of variations and cycles in the background gamma, which the prior art monitor cannot do.

Nonetheless, there are drawbacks with a monitor operating in this first mode. Firstly, each time the monitor detects a toxicity measurement outside the control limit, there is a minimum "down time" whilst the monitor collects a new set of data to generate the new control limits. In the example above, with 20 measurements per calculation and 20 minutes between measurements, this gives a minimum "down time" of 5 hours.

The monitor also does not compare any of the measurements m...n with the previous control limits whilst the new control limits are being calculated.

Thus, it is possible that the toxicity of one or more samples used to calculate the new UCL and LCL is itself unacceptably high. The spacing of the new control limits subsequently calculated will then be broadened. Measurements of later samples, having unacceptable toxicity, may be missed.

Of course, the processor 30 could be arranged to trigger the first alarm 40 during the collection of the data for calculating the new control limits. By clearing the latch only after the new set of data has been collected, and comparing each of the measurements to the old control limits, the above potential situation may be avoided. However, the minimum "down time" of the monitor may already be lengthy, and such a technique would potentially slow it down yet further.

To address some of the drawbacks of the monitor operating according to the above principles, a different approach to control limit calculation may be adopted. Such an approach is shown in Figure 3.

Figure 3 shows a flow chart describing the operation of the monitor 10 in a second mode. As previously, the monitor 10 extracts samples of water for toxicity measurement on a repeated basis, with the time between measurements being variable. A time gap of about 20 minutes is again suitable for the application described here.

A sample of water is taken into the sample inlet 20 and its toxicity measured by the toxicity measurement detector 25. Once the measurement has been made, it is sent to the processor 30 where it is stored at a first address in memory 32.

Simultaneously, at step 200 of the flow chart in Figure 3, the count of measurements made is set to 1.

At step 210, subsequent measurements of gamma are made every 20 minutes, for example. The second and subsequent measurements, up to an nth measurement, are stored at second, third ... nth addresses in the memory 32, respectively.

At step 220, the upper and lower control limits are calculated. The method of calculation is as previously described, i.e., an "X/moving R" calculation on the measurements, and the difference between them, is employed.

Once the calculation of the control limits has been made at step 220, the resultant values are loaded into the latch in the comparator 36.

Next, at step 230, the (n + 1)th measurement is made by the toxicity measurement detector 25. This (n + 1)th measurement is stored at an (n + 1)th address in memory 32, and at the same time is compared, at step 240, with the control limits previously determined on the basis of the first m to n measurements (and stored in the latch).

At step 250, if the (n + 1)th measurement is determined to be within the control limits, the process moves on to step 270. At step 270, the count number of the first measurement, m, and most recent measurement, n, are incremented by 1. Then, the process returns to step 220. That is, the control limits are re-calculated, following incrementation of the count, based upon the set of measurements m to n as incremented by 1.

If, at step 240, the (n + 1)th measurement lies outside the control limits calculated on the basis of the previous m to n measurements then, at 260, the first alarm 40 is triggered. This indicates to an operator of the monitor that a sample of water having an unacceptably high level of toxicity has been measured.

At step 270, the measurement count is incremented by one. Then, the process loop returns to step 220, and new control limits are determined on the basis of the last m to n measurements, each of which has now been incremented by 1.

The first alarm 40 is not switched off until, at step 240, the comparator determines a subsequent measurement of gamma lies within the control limits determined on the basis of the previous m to n gamma measurements. Again, the first alarm 40 may be controlled by a bistable 38, the bistable flipping from a first, "off", state to a second, "on", state when the comparator determines that a measurement lies outside the control limits previously calculated. The bistable 38 is then flipped back to the "off" state the next time a measurement lying within new control limits occurs.

A suitable value for n is again 20. Thus, referring back to Figure 3, the monitor operates as follows.

The monitor collects the first 20 measurements and stores them in the memory 32. The control limits are calculated on the basis of these first 20 measurements. The 21st measurement is then taken, stored in the memory 32, and simultaneously compared with the control limits calculated on the basis of measurements 1 to 20. If the 21st measurement lies within the control limits, the processor 30 calculates a new set of control limits based on measurements 2 to 21, stored in the memory. If the 21st measurement lies outside the control limits, the processor 30 still calculates a new set of control limits based on measurements 2 to 21, stored in the memory, but additionally triggers the first alarm 40.

Whether or not the alarm is triggered, the latch is cleared and the new set of control limits, based on measurements 2 to 21, is stored there instead. A 22nd measurement is then taken, and compared with the new control limits. The monitor continues to take 23rd, 24th ... measurements, each time re-calculating the control limits based on the previous 20 measurements and setting or resetting the first alarm 40 as appropriate.

A monitor operating in this second mode, as described in connection with Figure 3, therefore operates continuously, whilst compensating for any drift in background toxicity. Furthermore, the monitor thus arranged, does not have a "down time", once steps 200 and 210 have been completed.

However, a monitor operating in this second mode cannot analyse each of the measurements taken to identify and exclude measurements lying outside the control limits. In other words, if one of the measurements taken has a high gamma, well outside the control limits, it in turn will still be used to calculate later control limits. This can lead to widely spaced upper and lower control limits, and the first alarm 40 may not then subsequently be triggered, even for measurements having a relatively high toxicity. Conversely, a run of measurements having a low spread of gamma can force the control limits subsequently calculated to be narrow, thus potentially allowing false alarms.

To address this, yet a further embodiment of an environmental monitor 10, operating in a third mode, is now described, with reference to Figure 4.

Figure 4 shows a flow diagram of a monitor 10, operating in a third mode. The principles are similar to those described in connection Figure 3, although the monitor is able to exclude measurements lying outside previously calculated control limits when calculating subsequent control limits.

At step 300, the count of measurements taken is set to 1. The toxicity measurement detector 25 measures the toxicity, gamma, of a sample in the sample inlet 20 and sends that measurement to a first address in the memory 32. The monitor continues to take measurements on samples made every 20 minutes or so, and each subsequent measurement, up to the nth measurement, are stored in respective addresses in memory 32. This is shown at step 310 of Figure 4.

At step 320, the upper and lower control limits are calculated by the calculator 34, on the basis of the previous m to n measurements made. Once again, an "X/moving R" analysis of the m to n measurements is employed. The control limits thus calculated are output to the comparator 36, where they are stored in a latch.

At step 330, an (n + 1)th measurement is made.

This is simultaneously sent to an (n + 1)th address in the memory 32, and to the comparator 36. At step 340, the (n + 1)th measurement is compared, in comparator 36, with the control limits stored in the latch.

If the comparator indicates that the (n + 1)th measurement lies within the control limits, then, at step 350, the measurement count is incremented by 1.

Next, at step 360, the new (n + 1)th measurement is made, and sent simultaneously to a new (n + 1)th address in memory 32. The process then returns to step 320, and new control limits, based upon measurements m to n as incremented, are made by the calculator 34. Provided no measurements lying outside the continually updated control limits are made, the process cycles between steps 320 to 360 until monitoring is complete.

If, on the other hand, at step 340, the comparator 36 determines that the (n + 1)th measurement lies outside the control limits, then, at step 370, the first alarm 40 is triggered. At step 380, the (n + 2)th measurement is made. This is sent to the memory 32 in the processor 30, and also to the comparator 36.

At step 390, the (n + 2)th measurement is compared with the control limits in the latch.

If the (n + 2)th measurement lies within the control limits calculated on the basis of the first n to m measurements, then, at step 400, a new set of control limits is calculated by calculator 34, based on the last (n - m) results, together with the (n + 2)th measurement. In other words, once the comparator 36 determines, at step 340, that there is a measurement lying outside the control limits, subsequent control limits are calculated on the basis of previous measurements, but excluding any such measurements outside the control limits. Once the comparator has determined that the most recent measurement lies within the control limits, the first alarm 40 is re-set. As before, this may be carried out using a bistable 38.

At step 420, the measurement count is incremented by 1, and the process loop returns to step 380, that is, the next measurement is made. Once the comparator has determined, at step 36, that a measurement lies outside the control limits, all subsequent calculations of control limits exclude that measurement. In terms of the flow diagram of Figure 4, once a measurement lying outside the control limit has been made, the process then continues around the loop of steps 380 to 420 until monitoring is complete.

If, within that loop of steps 380 to 420, any further measurements are made which lie outside the control limits, these also trigger the first alarm 40, at step 410, before the measurement count is once again incremented at step 420.

Thus, as will be seen from Figure 4, all measurements lying outside previously calculated control limits are excluded from future calculations of new control limits.

To further illustrate the operation of a monitor operating in the third mode shown with reference to Figure 4, a specific example is now given.

The first set of control limits are calculated on the basis of the first 20 results, i.e., m = 1, n = 20. Once the 21st measurement has been made and compared with the control limits calculated on the basis of the first 20 results, if the comparator 36 determines that the 21st measurement lies within the control limits, then m is incremented to 2, and n is incremented to 21. The 22nd measurement is then taken, and compared with new control limits calculated on the basis of measurements 2 to 21.

If, at step 340, the comparator 36 determines that the 21st measurement is outside the control limits calculated on the basis of measurements 1 to 20, then the first alarm 40 is triggered and the 22nd measurement is made. At step 390, the 22nd measurement is compared with the control limits calculated at step 320 on the basis of the measurements 1 to 20. If the 22nd measurement lies within those control limits, then a new set of control limits based on measurements 2 to 20 and 22 is made by the calculator 34 (i.e., measurement 21 is excluded).

The alarm is switched off, and the monitor then measures the 23rd sample. If the 23rd sample lies within the control limits, calculated on the basis of measurements 2 to 20 and 22, then yet a further set of control limits is calculated based on measurements 3 to 20, 22 and 23. Thus, subsequent control limits always exclude measurement number 21, which was found to lie outside the relevant control limits at that time. If, for example, the 24th measurement is then determined at step 390 to lie outside the control limits determined on the basis of measurements 3 to 20, 22 and 23, then the 24th measurement is also excluded from future control limit calculations.

In the foregoing description of the three modes of operation of the monitor 10, only the triggering of the first alarm 40 has been described. As explained in the description of Figure 1, however, a second alarm 50 can also be triggered by the processor 30 when the processor determines that a run of several measurements, each larger than the previous, or each smaller than the previous, has occurred. The manner in which the processor determines that such a run of measurement has occurred will generally be independent of the control limits calculated, and suitable architecture for carrying out a comparison of previous measurements stored in the memory 32 will be apparent to the skilled person.

In addition, a third alarm 60 can be triggered by a set of measurements within the middle third of the control limits exceeds the quantity of measurements within the two outer thirds of the control limits by more than a predetermined amount. The proportions are a consequence of the control limits being calculated on the basis of mean X + 3a.

As the calculator 34 not only calculates each set of control limits, but also the mean X and the mean R, these latter two measurements can also be sent to a second latch within the comparator 36. Again, suitable architecture for comparing a plurality of measurements with the mean X and the mean R to trigger the third alarm 60, if necessary, will be apparent to the skilled person.

Although, in the above examples, the control limits are calculated on the basis of 20 measurements, other numbers of measurements can, of course, be used.

Indeed, by varying the number of historical measurements used in the calculation of control limits, different sizes (i.e., periods) of cycling within the background toxicity can be taken into account.

Furthermore, the monitor 10 is not necessarily restricted to operation in only one of the first, second or third modes. It may be desirable, in certain circumstances, to switch the monitor between, say, the first mode and the second mode.

The monitor 10 may have an output such that the measurements within the memory 32, and the groups of calculated control limits, mean X and mean R, can be collected by a personal computer. For example, the monitor 10 may be provided with a serial port or other communications device. The personal computer can then download the information from the processor 30 within the monitor 10, and plot it as a graph of toxicity versus time.

In yet a further embodiment, the monitor or a computer to which it may be attached can link the measurements of toxicity to potential causes of that toxicity. For example, a simple neural network could analyse measurements and trends in the measurements and provide a list of possible causes, in order of probability.

Referring now to Figures 5a to 5d, graphs of measured gamma versus time are shown. All data are collected from a first supply of waste water, with measurements being taken over six days. The vertical axis indicates toxicity, gamma, whereas the horizontal axis indicates time in hours:minutes.

Figure 5a shows a graph of toxicity versus time generated by a prior art environmental monitor. The long dotted line indicates the upper control limit, and the dash-dot line indicates the lower control limit. The short dotted line indicates the mean toxicity, gamma. Each of these parameters is calculated on the basis of the first 20 measurements.

It will be noted that a large quantity of the measurements in Figure 5a exceed the upper control limit, and each of the measurements A, B, C and D (and indeed other measurements not specifically labelled) would therefore have triggered an alarm. The cyclical (periodic) nature of the measured values, due to background variations in toxicity, is apparent.

Turning now to Figure 5b, a graph of gamma against time over five days is shown. The raw data in Figure 5b is identical to that in Figure 5a, although the mean gamma and upper and lower control limits have been calculated in accordance with a monitor according to the present invention, operating in a first mode.

It may be seen that, of the four exemplary measurements A, B, C and D, measurements A, C and D would not have triggered the first alarm 40 using this monitor. This is because the repeated recalculation of the control limits takes into account the cyclical variations in the background gamma, thus minimising the risk of false alarms.

Measurement B, however, would have triggered an alarm. It will also be seen from Figure 5b that a fifth exemplary measurement, E, took place during a period when the control limits were being recalculated. Thus, measurement E would not have triggered a first alarm either.

Turning next to Figure 5c, the same set of raw data used in Figures 5a and 5b is shown, but analysed by the monitor of the present invention operating in the second mode. Because of the rolling window of data points used to calculate the control limits and the mean gamma, data points A and C would not trigger an alarm. Data points B, D and E would, however. The control limits are not suspended at any point in Figure 5c.

Figure 5d again shows the raw data of Figures 5a to 5c, this time with the control limits calculated by the monitor operating in the third mode. That is, measurements lying outside the control limits are not used to calculate subsequent control limits. It may be seen from Figure 5d that only the measurement C lies within the control limits when calculated in this way. Each of the data points A, B, D and E would have triggered the first alarm 40.

Figure 6a shows a graph of toxicity, gamma, against time for a second supply of waste water.

Again, in Figure 6a, the control limits are calculated on the basis of the first 20 measurements and are not updated. The same raw data is used in Figures 6b-6d, although the monitor of the present invention, operating in the first, second and third modes respectively, is employed to analyse those measurements and determine the control limits.

Finally, Figure 7a shows a plot of gamma against time for measurements collected from a supply of potable water. The measurements made on the supply of potable water are compared to control limits calculated on the basis of the first 20 measurements made. In general, it may be seen from Figure 7a that many of the gamma values are very low, as would be expected from a potable water supply. Much of the variation in the raw data is probably not due to changes in toxicity. Indeed, many of the gamma values are negative, thus indicating that light enhancement (hormesis) of the bacteria used to measure gamma has occurred. Alternatively, the negative gamma values may simply indicate that there is zero toxicity at the dilution used. A particular advantage of the monitor of an embodiment of the present invention is that it calculates both a UCL and an LCL, thus allowing detection of both inhibitory and stimulatory (hormetic) effects Despite this, the prior art monitor, using fixed control limits, would have triggered an alarm between 11.00 a.m. and approximately 4.00 p.m. on the fourth day of measurement, due to the cluster of points marked F in Figure 7a. Further alarms would have been triggered due to the measurements marked G and H as well. It is apparent by inspection of Figure 7a that the measurements F and H are not, in fact, indicative of a high level of toxicity, although measurement G is significantly larger than the background gamma and does appear to indicate a higher level of toxicity.

Thus, measurements F and H would be considered false alarms.

Referring now to Figure 7b, the monitor of the present invention, operating in a first mode, would trigger an alarm when the first of the measurements generally labelled F was obtained. However, because the control limits would then be suspended, no alarm would be raised in respect of the subsequent measurements between midday and 4.00 p.m. that would have triggered the first alarm 40 in the prior art monitor. Similarly, the first measurement in the peak (labelled G) would have triggered an alarm.

Figures 7c and 7d show the results of a monitor according to the present invention, operating in second and third modes respectively. It will be seen that, generally, the data points F lie within the control limits once the first measurement in that group, at around 11.00 a.m., has triggered an alarm.

On the other hand, the measurements G would generate an alarm.

Turning finally to Figure 8, the data of Figures 5a-5d, analysed using the monitor of the present invention operating in a third mode (Figure 5d) is shown once more. Those data points ringed in solid line have been further analysed by the processor 30 of Figure 1. Those marked "second alarm" would cause the second alarm 50 to be triggered, as they contain a run of 7 or more sequentially increasing or decreasing measurements. Those measurements marked "third alarm" would cause the third alarm 60 to be triggered. This is because these measurements are considered to exhibit unusual patterns or trends, despite being within the control limits.

Claims (24)

1. Claims 1. An environmental monitor comprising: detector means arranged repeatedly to measure the value of a parameter of a substance to be monitored; and, processor means including calculating means for generating a permissible range of measured values, based on the measured values, and comparator means for comparing a measured value with the permissible range, the monitor being arranged to actuate an additional means when the measured value lies outside the permissible range of values; the processor means being arranged to update the permissible range, in dependence upon the measured values as further values are measured.
2. 2. An environmental monitor as claimed in claim 1, in which the processor means updates the permissible range only when the monitor indicates that a measured value lies outside the range.
3. 3. An environmental monitor as claimed in claim 2, in which the processor means updates the permissible range only when the monitor indicates that the most recent measured value lies outside the range.
4. 4. An environmental monitor as claimed in claim 3, in which the processor means updates the permissible range on the basis of a next predetermined number, n, of measured values once the monitor has indicated that the most recent measured value lies outside the range.
5. 5. An environmental monitor as claimed in claim 4, in which the processor means updates the permissible range on the basis of the next 20 measured values.
6. 6. An environmental monitor as claimed in claim 1, in which the processor means updates the permissible range each time the detector means measures a further value.
7. 7. An environmental monitor as claimed in claim 6, in which the processor means updates the permissible range on the basis of a last predetermined number, n, of measured values.
8. 8. An environmental monitor as claimed in claim 7, in which the processor means updates the permissible range on the basis of the last 20 measured values.
9. 9. An environmental monitor as claimed in claim 1, in which the processor means updates the permissible range each time the detector means measures a further value, provided that the further value does not lie outside the permissible range.
10. 10. An environmental monitor as claimed in claim 9, in which the processor means excludes values lying outside the permissible range when generating an updated permissible range.
11. 11. An environmental monitor as claimed in claim 10, in which the processor means updates the permissible range on the basis of a last predetermined number, n, of measured values that do not lie outside the permissible range.
12. 12. An environmental monitor as claimed in claim 11, in which the processor means updates the permissible range on the basis of the last 20 measured values that do not lie outside the permissible range.
13. 13. An environmental monitor as claimed in any one of the preceding claims, further comprising storage means for storing the measured values of the parameter.
14. 14. An environmental monitor as claimed in claim 13, in which the processor means updates the permissible range on the basis of the stored measured values.
15. 15. An environmental monitor as claimed in any one of the preceding claims, further comprising a first alarm arranged to be triggered when the comparator means determines that a measured value lies outside the permissible range.
16. 16. An environmental monitor as claimed in any one of the preceding claims, further comprising a second alarm arranged to be triggered when each of a predetermined number, m, of sequentially measured values is larger than the previously measured value in the sequence.
17. 17. An environmental monitor as claimed in any one of the preceding claims, in which the second alarm is arranged to be triggered additionally, or alternatively, when each of the predetermined number, m, of sequentially measured values is smaller than the previously measured value in the sequence.
18. 18. An environmental monitor as claimed in any one of the preceding claims, in which the calculating means calculates the mean value of the measured values, the mean value of the difference between consecutive measured values, and the standard deviation of the difference between consecutive readings, the permissible range being between the mean value of the measured values plus 3 standard deviations, and the mean value of the measured values minus 3 standard deviations.
19. 19. An environmental monitor as claimed in claim 18, further comprising a third alarm arranged to be triggered when the proportion of values within a middle one third of the permissible range differs from the proportion within the remaining two thirds of the permissible range by more than a predetermined amount.
20. 20. An environmental monitor as claimed in any one of the preceding claims, adapted to monitor the toxicity of a substance.
21. 21. An environmental monitor as claimed in claim 20, in which the detector means is adapted to measure the value of gamma.
22. 22. An environmental monitor as claimed in claim 20 or claim 21, in which the detector means is arranged to measure the value of gamma every 17 to 20 minutes.
23. 23. A waste water treatment plant, or a potable water supply line, including an environmental monitor as set out in any one of the preceding claims.
24. 24. An environmental monitor substantially as described herein, with reference to Figures 1 to 4, 5b-5d, 6b-6d, 7b-7d, or 8.