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Use of models in air pollution assessmentMax K Wallis aa Friends of the Earth Cymru , 33 The Balcony, Castle Arcade, Cardiff , CF1 2BY , UKPhone: +44 1222 229577Published online: 01 Nov 2012.

To cite this article: Max K Wallis (1998) Use of models in air pollution assessment, Impact Assessment and ProjectAppraisal, 16:2, 139-146, DOI: 10.1080/14615517.1998.10590199

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Impact Assessment and Proiect Appraisal, volwnc 16, number 2, June 1998, pages 139-146, Beech Tree Publishing, 10 Watford Close, Guildford, Surrey GUJ 2EP, UK.

Air pollution

Use of models in air pollution assessment

MaxKWallis

Both plume modelling and air pollution stand­ards are changing under the impact of public protests and improved science. This paper explores how company consultants and the regulatory bodies (now the Environment Agency) are implementing these changes in the UK, drawing on case studies of power stations in South Wales. Under-fulfilment of general policy on transparency and auditability is dis­cussed and proposals for improvement of the regulatory process are given, particularly in respect of public involvement.

Keywords: air pollution; models; assessment

Max K Wallis is at Friends of the Earth Cymru, 33 The Balcony, Castle Arcade, CardiffCF I 2BY, UK; Tel: +44 1222 229577. The author is grateful to Alan Watson of PIC consultancy for helpful. comments.

Impact Assessment and Project Appraisal June I 998

M ODELLING THE DISPERSAL of emis­sions and industrial plumes has long been criticised as an inexact science. It was said

to be inaccurate by factors of between 2 and 5, the lower appropriate to long-term average pollution and the higher to short-term peaks. (Shorter-term peaks close to emitters are now known to be more strongly under-predicted, as detailed below.) Despite these large factors, modelling results are applied as if accurate.

Tall chimney stacks are both costly and visually intrusive, so there is a strong incentive to undertake modelling to justify shorter stacks and for the regula­tors to give approval. Air pollution modelling is also being used with regard to air quality planning, a new responsibility ofUK.local authorities. It is not feasible and is too costly to position monitoring instruments everywhere for long enough periods of time, so local authorities may resort to modelling.

Pollution levels are judged against both short-term and long-term (annual average) standards, the short term being generally an average over one hour. How­ever, people are affected by polluted air over much shorter times - a minute or so for offensive smells and several minutes for irritant gases. Thus Health and Safety Executive (HSE) exposure limits are measured over 10 minutes. For sulphur dioxide (S02),

the new health-based UK limit is given in terms of 15-minute averages. Particular wind or sun conditions give extreme values of air pollution, and in the past the highest 2% of hourly-average measurements or predictions have been discarded ('at the 98 percentile level').

Because of public outcry, the dismissal of pollution peaks has become untenable. Short-term high levels give rise to public complaints, while 'fumigation' by so2 for quite brief periods has long been known to

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Box 1. Smokestack town

Sheila Hargreaves was doing the ironing at home when she suddenly felt ill. She thought it was the heat and stepped outside for a breath of fresh air.

Only it was the air that was making her ill, she believes. "I was surrounded by a brown haze. I felt as though I was eating chemicals. My eyes were stinging and I felt I was going to faint."

At least 100 others are suffering from heart, liver and breathing problems caused, they daim, by pollution from the Castle Cement factory that dominates the Ribble Valley in Clitheroe.

Many of the sick can see the factory chimneys from the windows of their homes. All of them can see the plumes of smoke -white, blue, black or sometimes a strange browny orange -that the chimneys pump out day and night. They rise, move horizontally then 'ground', engulfing houses for miles around. When the kilns 'trip' - switch off the filters to avoid an explosion - the chimneys fire out smoke containing sulphur dioxide and lead-contaminated partides.

The Observer, 27 July 1997

kill off sensitive plants. Bursts of pollution can be a serious problem from incinerators which are designed with a bypass of cleaning devices and so emit fumes directly during malfunction. Cement kilns are simi­larly designed to discharge uncleaned fumes, as the dust filters switch off under raised levels of carbon monoxide ('trips' mentioned in the quotation in Box 1). So the UK has now moved to use the 99.9 percen­tile level (discarding the highest 0.1%) or even the absolute highest.

The EU (European Union) has set new standards in terms of the ninth highest hourly level for N02

(nitrogen dioxide) over a calendar year, the 26th highest hourly level for so2 and the 26th highest daily level for particulates (fine dust). Such disparate and arbitrary numbers are likely to change - and the tendency in the UK is to set stricter standards than these EU minima.

The third main air pollutant is particulates (air­borne dust). The standard has been· set as a daily average only, which is curious. People with respira­tory conditions may suffer from urban dust over shorter exposures. The reason seems to have been that the medical scientists do not have data covering short­time exposures to dust. A further limitation is that dust sizes vary over a wide range and it is the finest that penetrate deep into the lungs and are potentially more harmful than the sizes measured by the currently favoured instruments.

While Her Majesty's Inspectorate of Pollution (HMIP) (the regulator until it became part of the Environment Agency in 1996) accepted company statements in 1991 that pollutants from sufficiently high stacks disperse harmlessly into the atmosphere, 1

the regulators are now saying that the ground-level concentrations (GLCs) should be measured, as well as being calculated by the models. Under the 1996 power station authorisations, the plant operators have to set up one or more monitoring stations for S02 and NOx (nitrogen oxides) monitoring "at a critical loca­tion". Initial arguments arose over siting these moni­tors, with the Environment Agency tending to agree with the operator on commercially convenient and

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less sensitive locations. Public availability of the monitoring data is another issue that is undetermined. Both these aspects would clearly benefit from a public information and consultation process.

Plume modelling

Several computer models and variations are used. The basic 'Gaussian plume' model assumes a plume rising to some height and spreading steadily as it drifts with the wind. Varieties of what is known as "R91" -the code number of the basic National Radiological Pro­tection Board (NRPB) report2 - calculate the rise and spreading for various wind and surface conditions. Figure 1 illustrates how a single plume spreads and that such plumes vary with conditions within a wider envelope. The average over all such plumes ('ensem­ble' of possible plumes) gives an average pollution profile.

The Central Electricity Generating Board (CEGB) had its own 'ALMANAC' version, now an in-house model ofNational Power. However, relying on their own private model had become increasingly embar­rassing for National Power, so recently they have been using standard models. In the United States, the En­vironmental Protection Agency adopted a model akin to R-91, which is known as ISC and is made freely available, including a wide range of adaptations to specific circumstances.

These models are based on an empirical classifica­tion of wind conditions (Pasquill stability classes A to E) that is now accepted to be a poor theoretical basis. The newly developed 'second generation mod­els' define the atmospheric boundary layer (between the ground and near uniform flow at height) in terms of physical parameters. As revealed by Lidar studies of particular plumes,3 the new models give a more

reflection at boundary layer

---·-·-z,

Figure 1. Cross section of plumes over an ensemble of meteorological conditions Indicating how mean height deviates from theoretical centreline depending on height of atmospheric boundary layer

Note: Plumes generally lie between the full lines Zm = mean height zp = theoretical centreline height

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ADD bo<qround auumechcmi5U')' NOx -NOJ

sample ground level concentrations

Figure 2. Modelling procedure flow chart

excludes eddie' and detached now

realistic representation of the changing dispersion with height.

Flows are also unsteady under certain conditions and the new models aim to represent the short-term fluctuations. The relatively small proportions of time when the plume nears the ground give the high peaks, for 10 or 15 minutes, with which the new standards for S02 are concerned. These are very much higher than the ensemble average described above, and also very dependent on special meteorological conditions.

The new model developed in the UK is known as UK-ADMS (atmospheric dispersion modelling sys­tem). This was brought out publicly in 1996 and has given problems because of limited testing. The sec­ond version, ADMS-2, was still giving problems through 1997 in those cases in which there was more than one emission source (though version 2.11 re­solved this) and when treating air flow past buildings. The US EPA's (Environmental Protection Agency) competitor known as AERMOD is still (in December 1997) being tested prior to general release.

The UK Environment Agency possesses the full ADMS-2, but some of its officers use the stripped­down version, ADMS-Screen, which is clearly defi­cient (see below). The expert comparison of ADMS andR-91 with field studies using Lidar3 concluded "it is inappropriate to rely on R-91 type models for sources higher than 30 metres in convective condi­tions".4 The Agency does not specify that ADMS must now be used, but rather says that a model must be "fit for purpose";5 that involves, for meeting air quality standards, predicting the short-term peaks that

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Use of models in air pollution assessment

come from fluctuations under convective conditions. Using the full models is somewhat complex and

requires some understanding of gas-dynamic flows. There are various parameters to be chosen and appli­cation to circumstances with hills or buildings can be problematic. Figure 2 shows the various components of the modelling process and indicates choices to be made and steps to be taken. The choice of model limits the complexity of terrain which can be represented (steepness and superposition ofhills), the shapes and combinations ofbuildings, the number of sources, and output formats.

Atmospheric characteristics may be derived (pref­erably) from observations but are commonly derived from several years of wind data via a 'pre-processor' programme. The many choices put such a modelling process beyond the expertise of most non-expert groups and local councils. There are also substantial costs: ADMS-2 costs £5000 and the appropriate me­teorology data is another £460 per set, while geodetic data for modelling the effect of hilly terrain costs extra.

Such models are also inaccessible to the public or public interest or environmental groups, except via friendly academic institutes. Unless the models can be made available, the setting of procedures that require them is inevitably handicapping to people in the affected communities, and reserves assessment and decision- making to the 'experts'. The transpar­ency objective is unachievable in respect of the gen­eral public.

Moreover, as Appendix 1 shows, the experts do not perform well in the modelling assessment. They do not set out the recommended clear explanation and audit trail: "an essential requirement in the document­ation [is] ... a complete and transparent account of what has been done. Interested parties should be able to ... scrutinise, check and if desired repeat ... ".6

The modelling is not consistent between countries. For instance, there are ways of deriving parameters (boundary layer height and surface heat flux) from the meteorology data. A European project ('COST 710') has been conducted to try to harmonise the 'pre­processing' packages that provide these parameters, and recently concluded in failure; for example, three calculations of the heat flux gave 56--80% of the measured value. 7

There are other parameters to be chosen, a Corio lis parameter and geostrophic wind speed (or friction

Unless the models can be made available, the setting of procedures that require them is inevitably handicapping to people in the affected communities, and reserves' assessment and decision-making to the 'experts'

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velocity) affecting large-scale dispersion, and a roughness parameter affecting the local dispersion. The latter is commonly taken to be 10% of the size of structures in the upwind direction, and would differ for different incident wind directions, especially in coastal locations.

Let me pick out three aspects under which the experts fall down on their own criteria.

Inaccuracy

It is well-established that modelling predictions are accurate only to factors 2 to 5 (the higher factor for short-term peaks at the old 98 percentile level). Stud­ies on behalf ofthe major power generators conducted with the agreement ofHMIP were carried out in 1996 by the Institute of Terrestrial Ecology (ITE).8 These studies mention the 2 to 5 times inaccuracy factor, but in the analysis comparing calculated levels with standards, the ITE treats the calculations as if accurate and allows no safety factor.

For instance in the Pembroke case (Appendix 1 ), the 98 percentile level was said to exceed the EU guideline if average output exceeded 75% of the station's maximum; yet it was not pointed out that, taking the factor 5 inaccuracy into account, makes the comparison far worse. Indeed, the EU limit which is nearly 50% higher could be exceeded by 275%. The modellers have a general problem in that, if this inaccuracy is taken seriously, their predictions are virtually useless.

The experts' meetings to resolve this uncertainty, started at Rise in 1992, revealed a still worse situation. The intercomparison of 12 regulatory models used in various European countries found dramatic differ­ences, with yearly average concentrations differing by a factor of 10.9 These meetings are still on-going; the present advice to model users is that they ask: 'how good is the model for my purpose' and be aware of the uncertainties.

How users assess this quantitatively is unclear, and work on model evaluation and standardisation is far from complete. The ADMS validation paper says that the model's long-term average is unlikely to be inac­curate by more than 2 times.4 Short-term peaks under unusual fluctuating flows and in flows past buildings (over which there is now greater concern) are presum­ably still less accurate, as well as being poorly pre­dicted by the old models.

Topography

For the second aspect in which the experts fall down, consider the verdict 9fthe modelling review group in 1995:6

"where dispersion will be affected by the local terrain, for example in areas close to coasts or where there are significant topographical fea­tures, it is recommended that measurements of relevant quantities should be made at the site for

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a reasonable period, such as one year. [In default of] on-site data, information must nevertheless be provided in order that the assessment can proceed . . . careful consideration needs to be given to the question of the degree to which data from another site are representative of the loca­tion for which data are lacking. Geographic proximity alone is not a sufficient criterion in this respect, as differences in terrain may well make the comparison invalid."

The data used by ITE8 was "10 year average statistics from nearest meteorological station". This is almost universal procedure; if any justification is stated, it is "as advised by the Met Office". Shorter series of data, five years or less, may be used. In none of the cases in Appendix 1 was anything other than geographic proximity given as a reason for using the Met data.

Justification

The third. aspect is that any modelling procedure chosen and factors neglected should be described and justified. The particular model used must be demon­strated to be technically appropriate, 10 or, as phrased more recently, "fit for the purpose".5•6 In practice, the regulators accept recognised models without ques­tioning, even after their own document4 established that the older ones are not fit to predict short-term pollution peaks.

The Agency officers used ADMS-Screen with standard meteorological data for regulatory decisions (Appendix 1, second and fifth examples) when it is quite unfit for the necessary judgements. One set of experts decided that the topography at Barry is hilly, and found this changed peak values significantly, whilst another set decided the area is effectively flat and makes no reference to the first (Appendix 1, second example).

Comments on South Wales studies

The use of modelling for various power stations in South Wales over the last few years is summarised in Appendix 1. There are no examples where applicabil­ity of wind data from distant meteorological (Met) stations was discussed, let alone validated by local measurements. Statistical wind parameters derived from the data are used, though the actual data are known to give higher peak values. In only two cases were calculations carried out using real 'sequential' Met data.

Comparisons were made with old outdated stand­ards (one-hour averaging; 98%ile Directive standard) without reference to expert committee views. It was subsequently confirmed as government policy in the White Paper11 that these are not sufficiently protective of health.

The AES/Barry and NP/Pembroke modelling show two cases of ADMS-Screen predicting lower

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instead of the expected higher short-term peaks, com­pared with the old R-91 models, at least in the way the Environment Agency appear to have used it with 'standard' Met data (that is, representative sets of data as supplied with the program). These two cases also show there is little attempt to prove consistency be­tween the different models and no acknowledgement of uncertainty in predicted values when comparison is made with the air quality standards.

The Agency decided that the 'background' N02 is high at Barry (inferred as 110 11glm3 as 98%ile of one-hr averages) and introduced a criterion that the new AES station should add no more than 10% of the 'headroom' within the EU limit of200!lg/m3 (ignor­ing the 135 11glm3 guideline), but then said they were satisfied with 14%. They allowed the Barry CoGen plant that was supposed to meet the same 10% crite­rion but came out five times higher on their ADMS calculation, arguing that the cost of replacing the newly built stack would be excessive.

The 110 11glm3 taken as background is clearly important for this kind of decision. So it is curious that the 98 percentile hourly value is scaled from limited monthly averages taken by N02 diffusion tubes sited in the town (scaling roughly with 2.5 times the higher of two sites' annual averages). Real data from urban sites give scaling ratios (between 98 percentile one­hour N02 and annual average N02) generally between 2 and 3,11 while N02 diffusion tubes are considered unreliable. So it cannot be satisfactory for the Agency to rely on such a crude estimate.

Comparison between the different predictions is generally not straightforward, because results are quoted for diverse percentile levels and averaging periods. The experts make use of conversion factors, but these are not well known and are subject to uncer­tainties that go unacknowledged. A non-expert would therefore have difficulty in assessing and comparing the results from different studies.

The Uskmouth study was the only one to fully use real Met data, that is, data for each hour over a year (four years in fact), which gives higher peak values than the averaged 'statistical' data generally used. Use of these sequential data showed reasonable con­sistency for the four years (that is, equal to within ± 10%) in applying the new standards for 15-minute S02 and peak hourly values of N02• The annual average N02 was found to be less consistent, to ± 20%.

Only the ITE studies mention inaccuracy of mod­elling, and then by reference to the old factor of 2 to 5 rather than the (worse) modem assessments. The ITE studies did not include the uncertainties in using the model results to draw conclusions. They also failed to address the question of 'fit for purpose', for either long-term average or short-term peaks, but justified use of their old PLUMES model on account of ADMS being still under development.

The review group6 stressed 'auditability' as an essential requirement and "documentation should give a clear and transparent account of what has been

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Use of models in air pollution assessment

done". Recent Agency guidance on assessing envi­ronmental impacts uses the phrase "clear audit trail".12 Graphical and diagrammatic summaries are recommended, with flow charts to show the calcula­tion strategy. None of the examples I have read, including those in Appendix 1, can be said to perform well in the 'audit trail' respect. The Agency's reports of their own calculations at the two Barry plants are little more than bare results.

Conclusions

The examples from South Wales in Appendix 1 show misuse of modelling by both companies/consultants and the Environment Agency. In particular:

• failure to test for robustness of results to uncertain parameters and data sets;

• omitting to validate Met Office data in the locality; failure to specify which Met data set has been used;

• use of Screen model rather than a more accurate model for decision-making;

• application to a building complex which the model cannot handle.

The Agency generally fails to challenge a company's use of 'unfit' models; in the case of CoGen/Barry, they wrote that it did not matter because the Agency itself would be using ADMS for it, while for the BP/Baglan planning stage they excused the failure by saying justification would be required at the licensing stage. The one consultancy uses an 'unfit' model at Baglan, while doing a proper job using ADMS and sequential Met data at Uskmouth (the former dated earlier, but still defended subsequent to the U skmouth study).

The three major power generators in autumn 1996 submitted an ADMS study of supposed typical inland and coastal power stations13 that claimed general re­sults, despite the known sensitivity to extreme Met conditions and geography that vary between sites. The Agency reply14 rejected their discounting ofN02

pollution and required further study of far wider pa­rameter ranges.

The Agency's chiefmodellers have also criticised the use of statistical wind data, pointing out in late 1996 thatthe use ofthe actual 'sequential' hourly data

Transparency in assessment is difficult to achieve when modelling is complex and rather arbitary: if the regulators do not understand the models, and find anomalous results, they cannot explain them confidently and openly to the public

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in the ADMS model gives appreciably different re­sults.14 However, this point has not been pursued by the Agency's Welsh region inspectors. Because ofthe change in N02 standard from a 99.9 percentile level to an absolute ( 100 percentile) between the draft and final version, an argument between the Agency and the power station operators over which data to use to define the 99.9 percentile level became redundant. Use of the real 'sequential' data is sounder, but ad­justment for location or limited observational period is still needed.

The aim of transparency in assessment and decision-making is of cour~e difficult to achieve when the modelling process is so complex and rather arbi­trary. If the regulators do not understand the models, and sometimes find anomalous results (which they discard), they can hardly explain them confidently and openly to the public. From their failures to follow the rules themselves and to follow good scientific practice (testing for robustness; resolving inconsis­tencies), it appears that the process is too complex for the official agencies.

There is a tendency to cover their inadequacies by saying that it is up to the applicants to demonstrate that the modelling they use is valid and fit for the purpose. Yet, when the regulators themselves per­form the calculations, they do not demonstrate that their own modelling is valid, nor do they give a clear audit trail, but hide the inadequacies by giving mini­mal information.

The evidence presented here has shown the need for the regulator (the Environment Agency) to review its procedures and produce a sensitivity analysis over the complex array of assumptions and parameters. However, the science and sensitivity analyses will generally be incomplete and subject to challenge as knowledge advances. So I would argue both for mak­ing the regulatory process more transparent and accessible, and for introducing independent expertise.

Making the standard model or models freely

available (as does US EPA) and requiring operators to supply their computer program and input data to interested parties are essential steps. Many people now have access to sufficiently powerful microcom­puters to run complex models, though simplified models giving potentially less accurate results could also be helpful.

Clearly the Agency should provide the meteoro­logical and geodetic data.free; it should also provide additional help to run the models and interpret results as part of its public register and information ser­vice.The independent expertise, also to be available to the public, would be provided by NGOs (non­governmental organisations) and/or university groups. 'Hazards centres' have a precarious existence in the UK, while 'science shops' have yet to emerge. Such bodies might provide a location for an inde­pendent service, if funding could be found.

As well as plume dispersion, there are other appli­cations of environmental modelling with similar or greater complexity and uncertainty. Deposition modelling and ozone episode modelling are exten­sions of plume modelling which incorporate atmos­pheric chemistry. In the case of acid deposition, the UK's Critical Loads Advisory Group produces as­sessments of the various models,l 5 which are used to inform government policies in the Europe-wide nego­tiations.

Groundwater pollution is assessed in the UK using a model known as LANDSIM, developed under con­tract to the National Rivers Authority, but largely monopolised by its originator}6 That public money went into LANDSIM, but this model unpublished and costs £500 to acquire, again infringes the transpar­ency and auditability objectives. LANDSIM also suf­fers from being a probabilistic model with a large number of user-defined parameters, potentially giv­ing any desired result. So independent expertise for advising on alternative parameters and interpretation, is important for this model too.

Appendix 1. Power station pollution modelling in South Wales

The major power companies submitted their own calculations early in 1996, in connection with updates of their IPC authorisations (Integrated Pollution Control emission licences). Later in 1996, the Institute of Terrestrial Ecology (ITE) by agreement between the major companies and HMIP, supplied predictions of pollution levels from all the major power stations, a using a Gaussian plume model of the R-91 type, but without mention of the March 1996 criticisms of R-91 nor reference to the new air quality standards.

We cite Aberthaw Power station as the South Wales' example, within a few km of Rhoose airport, so the Met data from there can be used without correction. The sizes of the power plants are indicated by their generated power (MW = megawatts) and stack height (m = metres); AQS indicates the air quality standard, average over 1 hour except where stated otherwise; the old UK and EU standards are 98%ile levels (that is, levels exceeded by only 2% of the readings) while the new UK standard for S02 is a 99.9%ile level.

Aberthaw Power Statton, National Power {NP) Date of Issue Model March 96 ALMANAC NP August 96 PLUMES ITE

1460 MW 152m stack Met data ?? statistical, 1 0-yr

AQS 24-hr, 98%ile 24-hr, peak

peakS~ 1231Jg/m3 471Jglm3

The two sets of results differ nearly three times (both adjusted to NP's output level); on the other hand the short-term S02 estimates were in reverse order: ITE's 15-minute peak estimate was 7881Jglm3, while NP's methodology for the 1 0-minute level (factor 2.5 times the one-hr level) gave 4741Jg/m3. Such short-term peaks dearly exceed the 2671Jg/m3 standard and, moreover, ADMS predicts maxima 2--4 times higher than these R-91 models and at locations doser to the stack (reference of Note 3)

(continued.

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Appendix 1. (continued)

Barry Power Station, AES gas-fired CCGT 230 MW Date of Issue Models February 96 ISC2, RTDM TBV Sci. July 96 ADMS Saeen EA October 96 ISC 3 Stanger August 97 ADMS EA

60m stack Met data statistical (?) standard sequential statistical

AQS peak [50m stack] 98%ile 98%ile 98%ile

98,-elleNO~ 22, 341Jg/m 9.11Jg/m3 12.01Jglm3 12.91Jg/m3

Met data from Rhoose airport were used without correction, despite very different topography at Barry - in a basin of hills and with substantial water and urban cover. NOx/N02 was the main pollutant at issue here (S02 only in back-up fuel oil). The Environment Agency (EA) did the initial modelling using ADMS Screen. Stanger Science and Environment found significanUy higher values using ISC (R-91 type) requiring a 95m stack: the difference was never resolved, but AES was happy to accept the Agency's 60m stack. Results are sensitive to terrain and stack height, as shown by the initial calculation of TBV Science that gave peak NOx of 34 1Jg/m3 at the highest elevation in Barry town centre, for a 50m stack and using RTDM (rough terrain dispersion model, version of ISC).

After pressure from FoE Cymru, the EA used the 'full-blown ADMS' in 1997, finding hourly NOx dose to the ISC flat terrain values. The EA also dairns that the terrain has little effect on its ADMS calculations, unlike the RTDM result. And the 60m stack was already erected.

CoGan Power Station, Barry NP/Dow Corning gas-fired CHP 33 MW 50m stack Date of issue Models Met data AQS May 96 ATOM Entec statistical, 10-yr peak May 97 ATOM Fluor Daniel sequential, 4-yr 98%ile/peak October/November 97 ADMS EA statistical, 10-yr 98%ile/peak

one-hrNOx 771Jg/m3 13.6/28.6 1Jg/m3 45 /158 1Jglm3

Again the Met data from Rhoose was used without correction (comments above apply for this plant too). The official guidance on stack height17 requires the stack to be higher than the nearby pair of 80m distillation towers (which are about three times their height in distance away) and a height of 91 m was calculated by En tee consultants. Nevertheless, the Environment Agency agreed to a 50 m stack in November 1996, with no BPEO (best practicable environmental option) assessment or other justification, apparenUy on the basis that Entec's dispersion calculations indicated a 60m or 75m stack would make little improvement.

The ATOM modelling as used (All Terrain Dispersion Model, a version of ISC) indudes building 'downwash' so cannot deal with towers higher than the 45-75m stacks considered. Entec showed no results in the direction of the towers. T~e subsequent study by Fluor Daniel said the buildings had "no significant effect"; however, they found peak levels on the hill to the north, quite different from Entec's maxima eastwards. Fluor Daniel's peak is also three times lower than Entec's, while they gave no mention of the earlier results, induding that the sequential data should give a higher absolute maximum.

After FoE Cymru objected to the use of outdated modelling, the Agency undertook ADMS modelling, pretending the pair of towers could be treated as one solid building and saying NP's results were confirmed. Moreover the version of ADMS is known to give faulty results for a tall, narrow building, taken as analogous to the pair of towers. As the stack had been built, the Agency implied that changing it would be exduded under the 'excessive cost' reason of BATNEEC (best available technique not entailing excessive cost). Their results do indicate high levels of NOx, over three times those accepted from the AES plant just 1km away.

CoGan Power Station, Baglan BP gas-fired CHP Date of issue Models November 96 ATOM ERM

11 00 MW 80m stack Met data statistical, 10-yr

AQS 98%ile, hourly

max one-hr NOx 3481633 1Jg/m3

The two values cover ordinary operation and during back-up use of fuel oil (almost as high S02 too, in the latter case). The 98%ile NOx was given as far lower at 1 0.21Jglm3. The location is coastal with steep hills (200m hillsides within a few km) and Met data from Mumbles (15km across the Bay) was used without qualification. Air quality standards are already exceeded in the nearby town (Port Talbot) due to industrial and motorway emissions.

Pembroke Power Station, National Power (NP) Date of issue Models November 94 ALMANAC NP October 96 PLUMES ITE January 96 R-91 + ADMS NP April (?) 97 ADMS Saeen EA

orimulsion fuelling Met data ??

statistical ?? ??

2000 MW 213 m stack AQS 98%ile/peak hr 98% (+S02 15-min) peak hr peak hr

98%11eNOx 11/63 58.7 124 24

The ITE calculations use Met data from Brawdy, an open coastal location some 30km from the Pembroke site, which is well inland on the Milford Haven waterway. NP used Met data from Aberporth, 60km away on the north coast. NP later produced similar values to those of November 1994 for a BPEO calculation in May 1995. ITE gave five times higher NOx than the November 1994 values of NP (98%ile) and twice that of the EA (Environmental Agency) for the peak hourly NOx. The January 1996 calculation by NP using R-91 reported twice the peak hourly NOx, saying a check with ADMS (unspecified model) gave similar numbers, that is, five times the EA's levels from ADMS-Screen. For maximum hourly S02., NP gave twice the levels of the EA.

Uskmouth Power Station proposed restart with coal fuel 360 MW 122m stack Date of Issue Models Met data April/May 97 ADMS CERC statistical 1 0-yr October 97 ADMS 2.11 ERM sequential 4-yr

AQS NOx, S02 24-hr peaks so2 99.9%ile 15-min NOx peak hour

pglm3 6, 18 610-780 430-530

The Met data is from Rhoose, some 35km west on a far more open part of the Bristol Channel. The first assessment (CERC) was quite inadequate: it provided 24-hr averages (instead of one-hr and 15-min) and implausibly low results. The subsequent study by ERM consultants used four years of real (sequential) wind data, giving ranges as shown over the four years. The N02 peak hourly standard (286 1Jg/m3) may be exceeded, depending on the relative oxidation of emitted NOx. ERM discounted it (implying they assumed oxidation of NO to N02 at under 20-30%), but did not refer to the usual reference [Janssen eta/, 1988, Atmospheric Environment, 22, pages 43-53] on oxidation levels up to 65%.

Note that numerical values for each plant, given in the final columns, are very different. To some extent the urban Barry projects are supposedly allowed little addition, because the 'background' N02 is already high (inferred as 110 1Jglm3 as 98%ile of one-hr averages), while the other plants are allowed to emit more because oflow background. The calculated results for the AES Barry plant appear implausibly low in comparison with CoGan. A 1994 study by TBV Science for the AES site (for lower output and shorter stack) gave much higher levels, while high sensitivity to terrain was shown both then and in the initial 1996 results, but there appear to have been no considerations of robustness under different parameters nor consistency between two calculations using the same Met data.

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Use of models in air pollution assessment

Notes and references

1. National Power's 1991 I PC applications contained the phrase "emissions are released at high level and diluted to harmless concentrations before reaching ground level", Pembroke Power Station, application AA2666.

2. NRPB, "A model for short and medium range dispersion of radionucleids released .to the atmosphere", Working Group on Atmospheric Dispersion, chairman R E Clarke, National Radiological Protection Board, Harwell NRPB-R91, 1979.

3. Lidar probing is a laser-light technique, that makes use of backscattered light from atmospheric irregularities, analogous to radar probing (using radio waves). The key UK study applying the Lidar results for validating the new models is in reference 4, while a discussion is given in ENDS Report 258, "Agency study casts doubt on air dispersion models", July 1996, pages 7-8.

4. HMIP, "Validation of the UK-ADMS dispersion model and assessment of its performance relative to R-91 and ISC using archived LIDAR data", DoE/HMIP/RR/95/022, 1996; also con­ference preprint of the same tiUe and authors (D J Carrruthers et af), CERC, Cambridge.

5. R Timmis, "Atmospheric dispersion modelling for regulatory purposes in the UK", lntemational Journal of Environment and Pollution, 5,1995, pages471-485.

6. Royal Meteorological Society, "Atmospheric dispersion mod­elling: guidelines on the choice and use of models, and the communication and reporting of results", 1995, published in collaboration with the DoE.

7. B Fisher, "Appropriate meteorological data to be used within dispersion models", paper to NSCA Dispersion Modelling meeting, Olympia, 11 November 1997.

146

8. ITE, M J Brown et at, "Estimating the impacts of oxides of sulphur and nitrogen around Aberthaw power station", Institute ofTerrestrial Ecology, Monks Wood, 1996.

9. H R Olesen, "Local-scale regulatory dispersion models: Initia­tives to improve 'modelling culture'", paper presented at the 10th Conference on Applications of Air Pollution Meteorology, Phoenix, Arizona, January 1998 [NERI/Roskilde, preprint).

10. C R Williams, "A regulator's perspective on the use of atmos­pheric dispersion models", in Olesen and Michel (editors), Rise Workshop on Objectives for the next generation of practical shott-range atmospheric dispersion models, 6-8 May 1992, pages 177-185.

11. DoE, UK National Air Quality Strategy, Cm 3587, March 1997. 12. DoE, "Best practical environmental option assessments for

integrated pollution control", Technical Guidance Note (Envi­ronmental) E1 Volume 1 (HMSO, 1997).

13. National Power, PowerGen and Eastern Generation, "Model­ling of power station impacts on local air quality", submitted to the Agency public registers in fulfilment of Improvement Plan Condition 5.3.10, 1996.

14. Environmental Agency, "Comments on power generators' re­sponse to improvement programme condition requiring the development of a local air quality protocol", submitted to the Agency public registers October-November 1996.

15. Critical Loads Advisory Group, Mapping and Modelling Envi­ronmental Acidification in the United Kingdom (Institute of Terrestrial Ecology, Edinburgh, 1996).

16. B P Plimmer (Golder Associates), "The use of a top down probabilistic modelling approach to containment transport", Geoenvironmental Engineering, T Telford, London, 1997.

17. HMIP, "Guidelines on discharge stack heights for polluting emissions", Technical Guidance Note (Dispersion) 01, (HMSO, 1993).

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