Expert Systems and Geographical Information Systems for Impact Assessment - Chapter 7

7 Hard-modelled impacts Air and noise 7.1 INTRODUCTION After discussing in the previous chapter issues of ES design applied to some of the initial stages of IA – screening and scoping – we are now going to move into its “core”: the prediction and assessment of impacts. The prediction of specific impacts always follows variations of a logic which can be sketched out as in Figure 7.1. Different areas of impact lend themselves differently to each of these steps and give rise to different approaches used by “best practice”. We are going to start this chapter by looking at some areas of impact prediction characterised by the central role that mathematical simulation models play in them. As we shall see, this should not be taken to imply that the assessment is “automatic” and that judgement is not involved, far from it: issues of judgement arise all the way through – concerned with the context in which the models are applied, their suitability, the data required, the interpretation of their results – but the centre stage of the assessment is occupied by the models themselves, even if the degree of understanding of their operation can vary. When these models are run by the experts themselves – who know their inner workings and understand the subtleties of every parameter – they can be said to be running in “glass-box” mode. On the other hand, in a context of “technology-transfer” from experts to non-experts – which expert systems imply, in line with the philosophy of this book – models can be run in “black-box” mode, where users know their requirements and can interpret their results, but would not be able to replicate the calculations themselves. It is this transition from one mode of operation to another – the explanation and simplification needed for glass-mode procedures to be applied in black-box mode with maximum efficiency – that we are mainly interested in. Of all the areas of impact listed in the last chapter, two stand out as clear candidates for inclusion in this discussion – air pollution and noise. Their assessment is clearly dominated by mathematical modelling, albeit with all the reservations and qualifications that will unfold in the discussion. © 2004 Agustin Rodriguez-Bachiller with John Glasson 190 Building expert systems for IA Figure 7.1 The general logic of impact prediction. 7.2 AIR POLLUTION In common with other impacts, the prediction of the air pollution impacts from a development can be applied at different stages in the life of the project (e.g. construction, operation, decommissioning), and at different stages in the IA: • consideration of alternatives about project design or its location • assessment (and forecasting) of the baseline situation • prediction and assessment of impacts • consideration of mitigation measures. The central body of ideas and techniques is the same for all stages – centred around simulation models – but the level of detail and technical sophistication of the approach vary considerably.22 7.2.1 Project design and location At the stage when the precise characteristics of the project (equipment to be used, types of incinerators, size and position, etc.) as well as its location are 22 The knowledge acquisition for this part was greatly helped by conversations with Roger Barrowcliffe, of Environmental Resources Management Ltd (Oxford branch), and Andrew Bloore helped with the compilation and structuring of the material. However, only the author should be held responsible for any inaccuracies or misrepresentations of views. © 2004 Agustin Rodriguez-Bachiller with John Glasson Hard-modelled impacts 191 being decided, it would be possible to run full impact prediction models to “try out” different approaches and/or locations – testing alternatives – producing full impact assessments for each. However desirable this approach would be (Barrowcliffe, 1994), it is very rare as it would be extremely expensive for developers. Instead, what is used most at this stage is the anticipation of what a simulation would produce – based mostly on the expert’s experience and judgement – as to what the model is likely to produce in varying circumstances, applying the expert’s “instant” under-standing he/she is capable of, as mentioned in the previous chapter. The range of such circumstances is potentially large; however, in practice, the most common air pollution issues are linked to the effects of buildings and to the effects of the location. To the expert’s judgmental treatment of these issues are also added questions of acceptability and guidance, to be answered by other bodies of opinion. With respect to the effect of buildings, the main problem is that the standard simulation models used for air dispersion do not incorporate well the “downwash” effects that nearby buildings have on the emissions from the stack (although second-generation versions are trying to remedy this, as in the case of the well-known Industrial Source Complex suite of models). Her Majesty’s Inspectorate of Pollution (HMIP) produced a Technical Note in 1991 (based on Hall etal., 1991) discussing this issue for the UK, and a rule-of-thumb that is often used (Barrowcliffe, 1994) simply links the relative heights of the stack and the surrounding buildings, stating that the height of the stack must be at least 2.5 times that of nearby buildings. The crucial location-related variable concerning the anticipation of air-pollution impacts at this stage is the height and evenness of the terrain around the project, as air-dispersion simulation models find irregular terrain (which make local air flows variable) difficult to handle. Such situations can be “approximated” using versions of the standard model – like the Rough Terrain Diffusion Model (RTDF) (Petts and Eduljee, 1994, Ch. 11) – with its equations modified for higher surrounding terrain. However, the effect of irregularity in that terrain is still a problem, until more sophisti-cated simulation models are produced and tested, and looking at previous experiences in the area is often still the best source of wisdom. This also applies to another location-related issue: the possible compounding of impacts between the project in question and other sources of pollution in the area, through chemical reaction or otherwise. This connects with the general area of IA known as “cumulative impact assessment”, an example of which can be found in Kent Air Quality Partnership (1995) applied to air pollution in Kent. This is possibly the only aspect at this stage where GIS could play a role, albeit limited, identifying and measuring proximity to other sources of pollution. Finally, in addition to these technical “approximations” – short of running the model for all the alternative situations being considered – consultation © 2004 Agustin Rodriguez-Bachiller with John Glasson 192 Building expert systems for IA Figure 7.2 Information about project characteristics and location. with informed bodies of opinion must be used. On the one hand, there may be technical issues of project design on which responsible agencies (like HMIP/Environment Agency) can give opinion and guidance. On the other hand, and more important at this stage, the relative sensitivity of the various locations must be assessed in terms of public opinion, and local authorities and public opinion are often the best source for this information (Figure 7.2). 7.2.2 Baseline assessment Assessing the baseline situation with respect to a particular impact usually involves, on the one hand, assessing the present situation and, on the other, fore-casting the situation without the project being considered. Baseline assessment is a necessary stage in IA. However, with respect to air pollution, it does not seem to exercise the mind of experts beyond making sure to cover it in their reports. This maybe due to the fact that this stage does not really involve the use of the technical tools (models) and know-how which characterises their expertise. The first task, assessing the present situation, does not involve any impact simulation, but simply the recording of the situation with respect to the most important pollutants (for a complete list, see Elsom, 2001). These can be grouped as follows: • chemicals (sulphur dioxide, nitrogen oxides, carbon monoxide, toxic metals, etc.) • particulates (dust, smoke, etc.) • odours. This recording could be done directly by sampling a series of locations and collecting the measurements following the techniques well documented © 2004 Agustin Rodriguez-Bachiller with John Glasson Hard-modelled impacts 193 in manuals. In developed countries this is rarely done, as it is possible to get the information from local authorities and environmental agencies who run well-established monitoring programmes for the relevant pollutants (particularly chemicals and particulates). In the UK, various short-term and long-term monitoring programmes for different types of areas (see Elsom, 2001, for more detail) are also made available via the National Air Quality Information Archive on the Internet. This is not the place to discuss in detail such agencies or programmes, but only to mention these sources for the interested reader. The point of interest to us is that this aspect of baseline assessment does not involve any impact simulation nor any running of the model. It is enough to know which agencies to contact and which chemicals to enquire about: • Local authorities are the first-choice sources (Barrowcliffe, 1994); it is common for them to have well-established air-quality networks covering traditional pollutants (such as smoke or nitrogen and sulphur dioxides) but also covering sometimes other pollutants. It is always good practice to contact them for data that may represent better the environment local to the project site rather than national surveys and networks. • The National Air Quality Information Archive Internet site provides information about concentrations of selected pollutants for each kilo-metre-square in the country (Elsom, 2001). • The Automatic Urban Network (AUN) provides extensive monitoring in urban areas for particulates and oxides. • For other chemicals, agencies can be found running more specific mon-itoring programmes, like the one for Toxic Organic Micropollutants (TOMPS) in urban areas. • More adhoc monitoring programmes can also be found in previous Environmental Statements for the same area. • If the area is not covered by any on-going or past monitoring, on-site pollution monitoring may be required at a sample of points, as the lack of credible baseline data may compromise the integrity of the air-quality assessment (Harrop, 1999). • Odour measurement is a difficult area, it can be undertaken scientifi-cally by applying gas chromatography to air samples, but the method most commonly used in the UK is by olfactory means using a panel of “samplers”. For the second task, forecasting the future air pollution without the development, future changes can refer to two sets of circumstances: (i) the whole area changing (growing in population, businesses, traffic, etc.); (ii) specific new sources of pollution being added to the area (new projects in the pipeline, an industrial estate being planned, etc.). The pollution implications of expected changes – if any – in the whole area, can be forecast with the so-called “proportionality modelling” (Samuelsen, 1980) which assumes changes in future pollution levels to be proportional © 2004 Agustin Rodriguez-Bachiller with John Glasson ... - tailieumienphi.vn