A framework for environmental impact assessment of long-distance energy transport systems

Pergamon

0360-5442(95)00131-x

EnergyVol.21, No.718.pp.693-702,1996 Copyright0 1996ElscvierScienceLtd Rintcdin Great Britain.All rightsreserved 03e&5442/%$15.00+ 0.00

A FRAMEWORK FOR ENVIRONMENTAL IMPACT ASSESSMENT OF LONG-DISTANCE ENERGY TRANSPORT SYSTEMS IV0 H. KNOEPFELT Laboratory for Energy Systems, Swiss Federal Institute of Technology, ETH-Zentrum UNL, CH-80X! Ztitich, Switzerland (Received 18 September 1995)

Abstract-A simple framework for environmental life-cycle assessment (LCA) based on physical measures is presented and applied to the comparison of long-distance energy transport systems, including high-voltage alternating and direct current transmission lines, pipelines for gas and oil, inland waterway, road and rail transportation. Quantitative indicators for fossil-energy consumption, air-emission impacts, land use, audible noise impacts, and visual impacts are developed. These can be used in the context of existing planning or decision making instruments, such as integrated resource planning, technology assessment, LCA, regional planning, line and power plant siting. To reduce all information to a single indicator, the concept of the equivalent impacted area is

introduced for land use, audible noise and visual impacts.It is shownthat pipelines are the environmentally most favourable option in the case of oil and gas transport. In the case of coal transport, early conversion to electricity and transmissionby high-voltagelines can lead to significant impact reductions compared to coal transport with barges and trains. For long transport distances, highvoltage direct current lines yield particularly good results. Copyright 0 1996 Elsevier Science Ltd.

1. INTRODUCTION

Historically, the main objectives of long-distance energy transport have been to access new energy sources and to guarantee the reliability of energy supply. Currently, there is increasing interest in economic gains from international energy trade. In electric systems, for example, the existing generation capacity may be used more efficiently by expanding the transmission links between different power pools. Possible advantages arising from a global link of electric systems spanning across all continents are a matter of intense discussion at the technical, economic and political level.lm3A rapid increase of transboundary trade in electricity has occurred in the past 15 years (average increase of 9% worldwide per year).4 From an environmental point of view, long-distance power transmission could contribute to access remote sources of renewable energy and to replace fossil fuel transport systems, which are often related to high pollution levels. Transmission lines, although, lead to environmental impacts both before/after operation (production, construction and decommissioning of infrastructure) and during operation (increased generation necessary to compensate for electric losses; land use; noise emissions; visual impacts, etc.), as described in earlier publications. 4*5To capture fully all impacts that are functionally related to a system, an LCA approach is used in comparing different transport systems in this paper. In the following sections, we do not investigate the overall economic and environmental effect of energy transport but focus instead on the environmental impacts of the transport systems themselves. The aim is to identify environmental advantages and pitfalls of different transport options, discuss possible improvement measures and provide environmental impact information to be used in existing planning instruments such as integrated resource planning (IRP), technology assessment, integrated regional and transport system planning, line and power plant siting. In the following section, a set of environmental impact indicators is developed for this purpose. An approach oriented at giving a physical measure of potential impact was chosen, as opposed to approaches aiming at calculating externalities based on prevention, control or damage costs. A limited number of standard energy transport systems, according to typical state-of-the-art technology, are analysed in Section 3, including high-voltage alternating and direct current transmission tAddress for correspondence: Stapferstrasse21, CH-8006 Zurich, Switzerland. 693

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lines, pipelines for gas and oil, inland waterways, and road and rail transportation. A typical application of the proposed framework is comparison of environmental impacts of electric supply systems with fossil power plants close to production or unloading terminals and subsequent power transmission with systems based on long-distance transport of fossil fuels and power production close to the end users. The example of energy transport between Dutch production and unloading sites and Southern Germany is discussed in Section 4. 2. DEVELOPING AN INDICATOR SYSTEM FOR DIFFERENT ENVIRONMENTAL IMPACT CATEGORIES

Quantitative indicators for five major environmental impact categories, including fossil-energy consumption; air-emission impacts; land use; audible noise impacts; and visual impacts have been proposed.5 Potential impacts from electric and magnetic fields are not included in the indicator set because of their uncertainty. The fact that an LCA approach is used and that indicators are meant for broad decision making and for technology assessment has repercussions on the requirements that had to be met: (i) the indicator measure is directly related to the environmental impact under consideration. The calculation algorithm is simple, easily understandable and consistent with general LCA principles;6 (ii) Site-specific information on the local state of the environment cannOt be considered which means that the indicators reflect average potential environmental impacts. The indicators for noise impacts and visibility are additionally weighted with average population densities along the transport lines; (iii) It also follows that indicators describe disruptions, mechanisms or potential effects, but never actual damage to man, animals and ecosystems; (iv) Indicators describe the whole range of potential impacts, including impacts at low-level concentration or intervention. Dose-response relationships also below emission or immission limits imposed by law are fully included; (v) It is assumed that classification factors developed for weighting different interventions with respect to an indicator can be linearized in a limited domain. In LCA, this is usually justified with the ceteris paribus assumption, i.e. the interventions and effects caused by the system are small compared with the overall problem. Indicators proposed for land use, noise impacts and visibility all refer to an equivalent impacted areu multiplied by the time of intervention (Table 1). It seems that this approach best fulfils the requirements defined here. The indicator for fossil-energy consumption refers to the higher heating value of different energy resources. Indicators for air-emission impacts refer to equivalent emissions of reference substances. In the latter two cases, the calculation of an equivalent impacted area was not considered a viable approach. Methods aimed at calculating the carrying capacity or the ecological footprint of communities sometimes refer to proxy systems to transform energy use and air-emissions into a measure of land use.’ The underlying assumptions, though, are highly speculative and uncertain and this is why we refrain from this approach. In the following paragraphs the indicator definitions are briefly explained. For more detailed information, see Ref. 5. With respect to the category air-emission impacts, indicators for the following seven environmental effects have been defined: enhancement of greenhouse effect; depletion of the ozone layer; human toxicity; ecotoxicity; acidification; nutrification; and photochemical oxidant formation. Indicators are calculated according to the LCA classification methodology proposed by Heijungs et al* which is fully compatible with the requirements of the present analysis. For a discussion of the method, see also Braunschweig et al9 and Knoepfel.5 The basic idea is that the effects of a reference substance are compared with the effects of the other involved substances under the same conditions based on simple

Table 1. Environmental impact categories and corresponding indicator measures given in this paper. Impact category

Indicator measure.

MJ Fossil fuel use kg or m3 of the reference substance Air emission impacts (detailed) Air emission impacts (aggregated) share of yearly world-wide impacts mZxyrs Land use mZxyrs Audible noise impacts mzxyrs Visual impact

695

Environmental impact assessment

models. Reference substances are CO2 for the greenhouse effect; CFC-11 for the depletion of the ozone layer; body weight exposed to the toxicologically acceptable limit for human toxicity; m3 critically polluted surface water for (aquatic) ecotoxicity; SO, for acidification; PO:- for nutrification; and ethylene for photochemical oxidant formation. With respect to these substances, classification factors are defined for all substances involved. The classification method is the object of continuous improvement, with respect to inclusion of more detailed environmental models (multi-media models, increased spatial detail including information on substance pathways etc.), with respect to considering serial/parallel impacts and to including new effect categories.” The further aggregation to a single indicator for air-emission impacts is part of a valuation procedure, which depends on personal preferences and risk perception. Here we consider three possible valuation models as described by Kortman et al” and by Kalisvaart and Remmerswaal” (Table 2). Other valuation models could be envisaged, but for practical reasons we limit the analysis to three. In a first step, the effect scores for reference substances mentioned above are normalized according to the world-wide effect scores (also other normalization systems could be envisaged). This leads to indicators with a measure of [yrs.]. In the following step the normalized indicators are aggregated using the weighting factors of Table 2. Weighting factors for the NSAEL model are calculated by relating the actual emission level to a critical, No Significant Adverse Effect Level (NSAEL) at which no observable effects according to best available scientific evidence occur. The observability condition leads to relatively high weighting factors for acidification and nutrification and to low weighting factors for the greenhouse effect. MET follows a so-called distance-to-target approach. Actual emission levels are put in relation to target levels considered to be sustainable in the long term as defined by environmental policy makers. Both NSAEL and MET have been operationalized in the context of Dutch studies. PANEL weighting factors are the result of a Delphi interview among environmental experts in research, consultancies, organizations and administration in the Netherlands. The experts also seem to consider potential future risks, thus leading to a higher weighting factor for the greenhouse effect, than in the other models. The same procedure of first defining objective indicators and then aggregating these to a single indicator according to possible valuation criteria is also followed in quantifying land use. For practical reasons land use is classified according to five broad classes based on the concept of hemeroby: natural systems (natural forests; certain conservation areas, etc.); modified systems (cultivated forests, grasslands, etc.); argicultural land; suburban and urban land; and sealed land. Based on these classes it is possible to define 10 types of land use or land depreciation: natural land depreciated to modified land; natural land depreciated to agricultural land, and so on. The corresponding indicators have ,a measure of area multiplied by the time of use, which includes construction, operation and decommissioning of a system. After that, land can either be used again by a follow-up system or restored again to its initial state. The restoration phase is also part of the land use of a system and can be included by using typical restoration times.5 A further aggregation of the different types of land use to a single indicator can be based on various criteria, e.g. on ecological stability of different land types, on the time needed to restore the original state of different land types, on the results of environmental expert panels, on the diversity and endangerment of species (plants or animals).5 Other criteria or a combination of the above could be

environmental

Table 2. Weighting factors for normalized air-emission indicators according to three possible valuation models. Impact Greenhouse effect Depletion of the ozone layer Acidification Nutrification Aquatic ecotoxicity Human toxicity Photochemical oxidant formation TOTAL

NSAEL

PANEL

MET

0.07 0.20 0.47 0.21 not defined 0.05 not defined 1.00

0.24 0.23 0.18 0.22 not defined 0.13 not defined 1.00

0.05 0.40 0.10 0.17 not defined 0.16 0.12 1.00

6%

Ivo H. Knoepfel Table 3. Weighting factors for different land types according to possible valuation criteria, as &fined in Ref. 5. Land use is valued according to the difference between initial and end state (e.g., natural land depreciated to modified land according to PANEL: 1 - 0.84 = 0.16). Scenario Name

EC0 I

Criteria

Stability of vegetation

Parameter used

Biological accumulation degree 1 1 0.1 0.05

Natural Land Modified Land Agricultural Land Suburban, Urban Land Sealed Land

EC0 II

PANEL

Time needed to Societal value of restore to the land original state Natural formation Results from time expert panel

0

1 0.17 0.0047 0.0004

1 0.84 0.52 0.29

0

0

envisaged, but for practical reasons only three valuation models according to Table 3 are considered in the analysis of energy transport systems. Psychological, psychosomatic and stress-induced effects of audible noise show a highly non-linear behaviour with respect to noise levels. We use the concept of annoyance, as defined in noise impact research, as an indicator for potential impact. The idea is to use annoyance curves, showing the percentage of highly annoyed people at different noise levels, to weigh impacted land (at different noise levels) close to transmission lines, roads, railways, etc. Schultz’3 showed that annoyance curves for different noise types correlate well and defined a universal annoyance curve (Fig. 1). The Schultz curve is a 80

40

50 Day-nlght

60 nolso

70 level

50

90

[de(A)]

Fig. 1. Schultz curve.

Fig. 2. System boundaries (frame) for systems transporting electricity (top) and fossil fuels (bottom). A: powerplant supplying the electricity input. B, D: transformer, inverter and switching stations. C: power plant supplying the electricity to compensate for line losses. E: output = 1 TJ electricity at 110 kV. F: main input = fossil fuels. G: loading and unloading stations. H: compressor stations (gas is fed directly from pipeline) or barge/train/truck. I: supply system for electricity or fuels. J: conversion of fossil fuels to electricity-conversion factor = 0.4.

Environmental impact assessment

697

rough approximation of reality, but is considered precise enough for use in this paper and is applied to weigh noise-impacted land leading to the following expression for the equivalent impact’ed area:

ANoise =2XbX

I

q[LJX,L~,o)]dx, (d),

(1)

Xt?

where x(m) is the perpendicular distance from a linear noise source (a road, a transmission line, etc.), b(m) is the length of the linear source, q(-) is the percentage highly-annoyed according to the Schultz curve, L, [d&A)] is the energy-averaged noise level corrected by a factor for the tonal component, &., [d&A)] is L, measured at a distance X, from the centreline, x, is the distance of the road, railway or

right-of-way edge from the centerline, x,, is the distance beyond which the annoyance is zero. We use a tonal correction factor of -5 dB(A) for railways, -10 d&A) for inland waterways and +8 d&A) for transmission lines with respect to road noise, which was not included in Schultz’ original curve but is essential to achieve a better correlation between different noise types (road, railway, etc.). The analysis of more recent studies also shows that the annoyance curves for different road types can diverge greatly. In particular, motorway noise seems to cause much greater annoyance than overland road noise at the same noise level. In future studies the use of more accurate annoyance curves for different noise types should be considered. The concept of calculating an equivalent impacted area is followed also for the indicator describing the visual impact of transmission lines and of railway and pipeline right-of-way. A distinction is made between visibility (the ability to discern an object from the surrounding landscape), visual contact (including additional information on the actual visual contact between the object and resident and transient viewers) and visual impact (covering also sociocultural attributes of the viewers resulting in the perception of visual esthetic impact). An objective quantitative measure that fulfils the indicator requirements in this paper is possible only at the level of visibility. We use the concept of relative visibility to weigh impacted land close to an energy transport facility. The relative visibility function at a defined viewpoint is calculated by projecting the object on a half-sphere that represents man’s viewing field, and putting the projection area in relation to the area of the half-sphere as follows:

4” = l/(2&)

x

R2d6 dcp = 1427r) x

II

dfidq, II

(-),

(2)

where qv is the relative visibility, 6 the angle perpendicular to the earth’s surface, cpthe parallel angle. The equivalent impacted area, using relative visibility as a weighting function, is calculated in the same way as for noise impacts from Eq. (1). Also in the case of visibility the indicator has the measure of an equivalent impacted area multiplied by the time of the impact. The relative contrast between the object and the surrounding landscape has an influence on the maximum distance at which the object can still be seen (visibility limit). This is taken into consideration by setting the integration limits in Eq. (2) equal to the maximum distance of visibility. Because an empirical formula for relative contrast and visibility limit is not easy to define, we included information on visibility limits from field surveys.5 3. COMPARISON OF STANDARD TRANSPORT SYSTEMS

A set of typical long-distance transport systems according to state-of-the-art technology and typical use on the European mainland is defined.5 Care was taken to define system boundaries for all transport options in a consistent way. The functional unit of the analysis is the transport of 1 TJ electricity (Fig. 2, top) or the transport of the fossil-energy needed to produce 1 TJ electricity (Fig. 2, bottom). The output of electricity is set at a voltage of 110 kV. In the case of electricity transport transformer, inverter and switching stations are included in the analysis. In the case of fossil-energy transport an overall conversion factor of 0.4 from fossil fuels to electricity was defined for all systems, In the case of indicators for fossil-energy use and emission impacts enough data was available to perform a true LCA analysis. This means that all impacts functionally related to the transport systems (material and energy inputs, increased generation necessary to compensate electric losses etc.) were

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considered. In the case of indicators for land use, noise impacts and visibility only the direct impacts of the transport systems were considered. Results for the comparison of different long-distance transport systems lead to the following main conclusions? (i) with respect to oil and gas transport, pipelines yield best results for all impact categories; (ii) in the case of oil transport, electric trains and barges lead to better results than power transmission for most impact categories (some exceptions with respect to land use and noise impacts); (iii) in the case of coal transport, power transmission can lead to significant advantages over trains and barges, especially if very high voltages or direct current transmission are considered (some exceptions with respect to noise impacts and visibility); (iv) direct current power transmission shows advantages over electric trains and barges starting from a “break-even” distance of 100 to 700 km, according to the valuation model. A choice of results is reported in Figs. 3-6. With regard to air-emission impacts, the ranking of the systems can slightly change according to the valuation model. The NSAEL model, for example, emphasizes acidification and nutrification, which are in turn mostly dependent on SOP- and NO, emissions. This approach leads to relatively higher values for barge and train transport as compared to transmission lines, The same effect applies to the MET model, where additionally photochemical oxidant formation is considered, which again depends on NO, emissions. Direct current transmission (HVDC) was analysed in detail. HVDC appears to be a very promising option for long-distance transport with regards to environmental impact. In HVDC transmission, higher investments for converter and switching stations are amortized by generally lower transmission losses. So-called break-even distances for a f 500 kV HVDC transmission line with respect to other transport systems are reported in Fig. 6. For the NSAEL and MET models, the typical environmental break-even distances (200-300 km) are considerably lower than the results for a purely economic analysis (typically 600-900 km). Values for the PANEL model are in the same range as economic breakeven distances. 4. AN APPLICATION

TO FOSSIL-ENERGY

TRANSPORT

ON THE EUROPEAN

CONTINENT

Several applications of the proposed framework have been discussed.5 Here we present results for the transport of coal between the port of Rotterdam and the Mannheim/Karlsruhe area in Southern Germany. Rotterdam is the most important port of entry for imported coal in Germany. The coal is 35

??Transmission

30 3 2

line

380kV

25

0 Transmission kV

- 20 !? * 2 15 r & 6 10 t

Transmission f5OOkV

??inland Rail

5

?? Rail

line 750

line DC

barge electric diesel

0 NSAEL Fig. 3. Total normalized

PANEL and weighted

air-emission impacts per TJ electricity coal over a distance of 1000 km.

output for systems transporting

Environmental

699

impact assessment

??Pipeline 0

Transmission 380kV

line

Transmission

line

750 kV WT ransmission

line

DC zt5OOkV

NSAEL Fig. 4. Total normalized

PANEL

and weighted air-emission impacts per TJ electricity natural gas over a distance of 1000 km.

35

output for systems transponing

??Pipeline

30 0

Transmission 380kV

line

Transmission kV

line 750

H Transmission

line DC

f5OOkV

??Inland 5

Rail

0

?? Rail NSAEL Fig. 5. Total normalized

barge electric diesel

PANEL and weighted

air-emission impacts per TJ electricity oil over a distance of 1000 km.

output for systems transporting

unloaded and then shipped to Southern Germany via barge transport on the river Rhine or transported by rail. Economic studies at the beginning of the 1980s showed that this option is clearly more advantageous than producing electricity close to production or unloading terminals and transporting high voltage electricity to Southern Germany. How do the different options compare from an environmental point of view? We will use the indicators proposed in Section 2 and assume standard transport systems as described in Section 3. Barges follow the Oude Maas, the Waal and the Rhine for a total length of about 700 km. Coal electric trains use existing railways via Dordrecht, Eindhoven, Koln and Mainz for a total length of about 600 km. Both barges and electric trains return to Rotterdam empty. In the case of electricity transport it is assumed that electricity is produced directly at the unloading terminal in

700

Ivo H. Knoepfel

1600 1400 1200 E

1000

$

800

5 I P

600

??NSAEL 17 PANEL WIEr

400 200 0

Fig. 6. Break-even-distances beyond which the direct current transmission system (rt 500 kV) leads to lower normalized and weighted air-emission impacts as compared to other systems.

Rotterdam and that new transmission lines are built paralleling existing high voltage lines via Eindhoven, Maasbracht, Oberzier and Btirstadt for a total length of about 600 km. Results for air-emission impacts (Fig. 7) show an advantage for the very high voltage 750 kV lines over all other systems. Results for the HVDC lines are in the same range as for the 750 kV lines. Depending on the valuation model also 380 kV lines show a small advantage over barge transport. The analysis of land use according to models EC0 I and EC0 II leads to similar results for rail transport and 750 kV lines, with higher values for the 380 kV lines (Fig. 8). Even though the 750 kV lines require a larger right-of-way, they yield lower specific land use values than the 380 kV lines, because of the increased transport capacity. According to the PANEL model rail transport leads to the highest value for land use. The reason lies in the fact that PANEL attributes a greater land use value to the sealing of modified or agricultural land due to the railway lines. Results for potential noise impacts (Fig. 9) clearly show highest values for rail transport. It is interesting to note that also the corona noise of the

??Barge ?? Rail

Coal

Coal

HVAC 380kV Coal

??HVAC

NBAEL

750kV Coal

PANEL

Fig. 7. Total normalized and weighted air-emission impacts for the transport of coal energy between Rotterdarn (NL) and Karlsruhe (D).

Environmental

= ;1 .

80

k

80

701

impact assessment

??Barge

Cl Rail Coal

x 3

Coal

4o

ECOI

EC0 II

Fig. 8. Results for the land use indicator

?? HVAC

380kV Coal

??HVAC

750kV Coal

PANEL

in the case of coal energy transport Karlsruhe (D).

between Rotterdam

(NL) and

HVAC 750kV Coal HVAC 380kV Coal

0

0 Settlements

Rail Coal

Barge Coal

0

10

20

30

40

50

(m2 x yrs / TJe) Fig. 9. Results for noise impact indicators

in the case of coal energy transport Karlsruhe (D).

between Rotterdam

(NL) and

750 kV lines can lead to relatively high impacts. It is considerably reduced at lower voltage levels. In Fig. 9, results are also shown when considering an additional weighting of the equivalent impacted area with the density of population close to the lines.

5. CONCLUSIONS

A simple quantitative framework for environmental LCA analysis based on physical quantities has been developed and used for the comparison of long-distance energy transport systems. To reduce all information to a single indicator, the concept of the equivalent impacted area was introduced for land use, audible noise and visual impacts. This is in many ways a useful concept for a general type of analysis, such as LCA or technology assessment. It allows us to describe potential effects without including site-specific information needed to assess actual damage on man and ecosystems. It is also

702

Ivo H. Knoepfel

a useful concept for the further valuation of different impact categories and aggregation to a single indicator. By defining target environmental impact levels, e.g., in the context of environmental policy, equivalent impacted areas could be added to obtain a single indicator. For energy consumption and emission impacts, the definition of an equivalent impacted area is not straightforward and will need further development in the future. Results from the analysis for different energy transport systems show a clear advantage of pipeline transport for oil and gas over other systems. Early conversion of coal to electricity and transmission with very high voltage lines or direct current lines can lead to significant improvements over the transport of coal with barges and trains. Because of other side effects such as audible noise, radio and television interference, potential effects from electric and magnetic fields, the use of very high voltages is clearly restricted. Direct current transmission at voltage levels up to 500 kV seems to be a favourable environmental option for long-distance transport which should be further investigated. REFERENCES

1. A. Voss, A. Wiese and M. Kaltschmitt, “Technische, iikonomische und ijkologische Aspekte eines Global Link”, pp. 195-214, VDI-Workshop on Global Link-interkontinentaler Energieverbund, VDI-Report 1129, Diisseldorf (1994). 2. H. S&tier, “Einfilhrung in die Gesamtproblematik des Global Link”, pp. 1-16 in Ref. 1. 3. C. J. Winter and J. Nitsch eds, WasserstofSals Energietriiger, Springer, Berlin (1986). 4. I. Knoepfel, S. Bemow and M. Lazarus, “Environmental Impacts of Long Distance Energy Transport: Additional benefits of Efficiency”, American Council for an Energy-Efficient Economy, Proc. 1994 Summer Study (28 Aug.-3 Sept. 1994). 5. I. Knoepfel, “Indikatorensystem ftlr die iikologische Bewertung des Transports von Energie”, Dissertation No. 11146, Laboratory for Energy Systems, Swiss Federal Institute of Technology, Ziirich (Sept. 1995). 6. Society for Environmental Toxicology and Chemistry SETAC, “Guidelines for Life-Cycle Assessment: a Code of Practice”, Brussels (1993). 7. M. Wackemagel, “How Big is our Ecological Footprint? Handbook for Estimating a Community’s Appropriated Carrying Capacity”, University of British Columbia, Vancouver (1994). 8. R. Heijungs, J. B. GuinCe, G. Huppes, R. M. Lankreijer, H. A. Udo de Haes, and others, “Environmental LifeCycle Assessment of Products; Guide & Backgrounds”, CML, University of L&den (1992). 9. A. Braunschweig, R. Fiirster, P. Hofstetter, and R. Mtiller-Wenk, “Evaluation und Weiterentwicklung von Bewertungsmethoden ftir bkobilanzen-Erste Ergebnisse”, Institut ftir Wirtschaft und ijkologie, No. 19, St. Gallen (1994). 10. H. A. Udo de Haes ed., “First Working Document on Life-Cycle Impact Assessment Methodology”, Swiss Federal Institute of Technology, Ztlrich (Sept. 1994). 11. J. G. M. Kortman, E. W. Lindeijer, H. Sas, and M. Sprengers, “Towards a Single Indicator for Emissionsan Exercise in Aggregating Environmental Effects”, Milieukunde Interfaculty Dep., University of Amsterdam (1994). 12. S. Kalisvaart and J. Remmerswaal, “The MET-Points Method: a New Single Figure Performance Indicator based on Effect Scores”, Manuscript distributed at the 4th SETAC-Europe Congress, I&den (11-14 April 1994). 13. Th. J. Schultz, Community Noise Rating, 2nd edn. Applied Science Publishers, London (1982).