An Integrative Approach to Assess Externalities: Combining Ecological-Economic Modelling

and Choice Experiments – the Context of On-Shore Wind Energy Supply

Cornelia Ohl*, Jürgen Meyerhoff#

* Helmholtz Centre for Environmental Research - UFZ, Leipzig

# Berlin Institute of Technology (TU Berlin)

Grant No01UN0601A, B

Overview

1. The Project

2. First Results

3. Outlook

The Project: Background

Impacts on Nature

CO2-emmissions and

running out of resources

Global Climate Change

Not in my backyard

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Windenergyn

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The Project: Goals

• Quantifying externalities of wind energy supply with the help of Choice Experiments (CE) and an Ecological-Economic Modelling (EEM) procedure.

• Identification, Evaluation and Visualisation of alternative land use options.

• Support site selection for the installation of wind power plants

The Project: Modelling procedure

Data on:

Wind speed,

Impacts on nature (esp. collision risk red kite) and humans (noise, shadow etc.).

3 representative wind mills(2MW, 3 MW, 6 MW)

For each technology calcula-tion of: energy output, land consumption, collision risk red kite etc.

Display of GIS – Maps Visualisation of e.g. Energy output (here: classified according to German EEG)

(1km grids)red – low energy outputgreen - high energy output

The Project: Identification of sites

Red: Suitable sites from a nature conservation point of view

Grey: Sites elected by regional planning bodies

Green: Potential sites for a specific wind mill erection

The Project: Choice Experiments• Characteristics of wind energy production are defined as

attributes of environmental changes

• Focus is on: – Height of the turbines – Seize of a wind farm– Impacts on local wildlife (collision risk red kite)– Distance to settlement areas – Cost of allocation patterns (surcharge monthly power bill)

• Setting options presented to German public

• Survey includes statements concerning attitudes toward wind power generation, etc. and Choice Experiments– Two representative studies (West Saxony; Northern Hesse) – Nationwide online-survey (Accessible: June to July 2008)

First Results: Online-Survey Presentation of Attributes and levels

Attributes Levels

Size of the wind farm large (16 to 18 mills), medium (10 to 12 mills), small (4 to 6 mills)

Height of the wind milll 110 meter, 150 meter, 200 meter

Local nature impact small, medium, large

Minimum distance to village/town

750 meter, 1.100 meter, 1.500 meter

Surcharge to power bill per month

€ 0 / € 1 / € 2,5 / € 4 / € 6

Note: underlined attribute levels describe programme A (constant least cost scenario)

First Results: Online-Survey Self selection bias

• Respondents were gained through press releases and announcements on various web pages

• Thus, sample is not representative for German population, e.g.:– only 20% women in sample (nationwide

around 51%)– 44% of respondents buy green energy

(nationwide around 5%)

First Results: Online-Survey Consistency of choices

Programme A Programme B Programme C

Size of the wind farm large farms small farms large farms

Height of the wind mill 200 Meter 110 Meter 110 Meter

Local nature impact medium low medium

Minimum distance to village/town

750 Meter 1.100 Meter 1.500 Meter

Surcharge to power bill per month

€ 0 € 6,- € 1,-

Each respondent was presented 4 choice cards during interview plus a fifth card with a dominant alternative

Programm A presents status quo for wind power production in 2020

First Results: Online-Survey Choice of dominant alternative• Respondents were randomly presented one of two

choice cards with a dominant alternative, i.e., all attributes were at least as good as in the other alternative and at least one was better

DomAlt1Programm C dominates B

DomAlt2Programm B dominates C

Programm A(Status quo 2020)

624 / 62.4 % 623 / 62.5%

Programm B 39 / 3.9 % 331 / 32.7%

Programm C 337 / 33.7% 48 / 4.8 %

First Results: Online-Survey Effect of attribut level - Conditional logit

prei -.1381398 .0113599 -12.16 0.000 -.1604049 -.1158748 Ab_150 .0483705 .0274669 1.76 0.078 -.0054636 .1022046 Ab_110 .0842059 .0274698 3.07 0.002 .0303661 .1380457 Nathigh -.9416609 .03483 -27.04 0.000 -1.009927 -.8733953 Natlow .7163201 .0274705 26.08 0.000 .6624789 .7701613 Hei_150 -.0554923 .0278145 -2.00 0.046 -.1100077 -.0009769 Hei_110 -.2331647 .0292514 -7.97 0.000 -.2904965 -.1758329 WPsma -.0785838 .0279784 -2.81 0.005 -.1334205 -.023747 WPmid .1018578 .0288742 3.53 0.000 .0452654 .1584502 ASCSQ .2338557 .0681016 3.43 0.001 .1003789 .3673325 choice Coef. Std. Err. z P>|z| [95% Conf. Interval]

Log likelihood = -7349.8337 Pseudo R2 = 0.1633 Prob > chi2 = 0.0000 LR chi2(10) = 2869.34Conditional (fixed-effects) logistic regression Number of obs = 23988

• Apart from “Ab_150” all variables are significant at 5% level

• Apart from “Hei_110” and “Hei_150” signs are as expected, e.g., price: “prei” is negative

• Negative sign for “Hei_110” and “Hei_150” indicates that people do not prefer a move from wind mills of 200 meter height to smaller ones

First Results: Online-Survey Implicit prices based on CL

/attribute price

• Implicit price (IP) indicates WTP for movement from one attribute level to another

• IP is given by:

WPmid 0.74 (0.32 / 1.16)

WPsma -0.57 (-0.98 / -0.16)

Hei_110 -1.69 (-2.19 / -1.19)

Hei_150 -0.40 (-0.79 / -0.01)

Natlow 5.18 (4.29 / 6.07)

Nathigh -6.82 (-7.98 / -5.65)

Ab_1100 0.61 (0.21 / 1.01)

Ab_1500 0.35 (-0.04 / 0.74)

Outlook: Evaluation of Sites Integration of Survey Results in the EE-Model Goal: Sustainable Site Selection

Natur impactgreen = low

Energy outputgreen = high

Social impactgreen = low

S e a r c h f o r c o m p r o m i s e !

Outlook: Site Selection with MULBOCompromise 1: Equality of goals

Green: Potential sites for wind power generation as selected by MULBO

Blue:Sites selected by regional planning bodies

Red:Wind mill erection (Typ I) not allowed by legislation

Thank you for attention!

Websites: http://www.ufz.de/index.php?de=14638

http://www.landschaftsoekonomie.tu-berlin.de/8359.html