Scottish Government on-shore wind farm appeal and consenting performance – a critical appraisal

 



Analysis of Scottish Government data on approval and consenting rate for on-shore wind farms comparing pre and during Covid periods.  September 2022.








Dr Alan Jones, PhD. CEng. FIET.



 

Summary

 

This paper examines data supplied by the Scottish Government on the approval rate for on-shore wind farm appeals of up to 50MW capacity and consents for wind farms exceeding 50MW, i.e. Section 36 applications, over the past five years (2017-2021).  

 

The examination takes the form of a longitudinal study with a view to testing whether an observation by several wind farm campaign groups – that appeal approval and consent rates are high, especially over the recent past, has merit.

 

The analysis shows, with a high level of confidence, an association between an increase in appeals allowed (for wind farms up to and including 50MW) and consents of Section 36 applications between 2020-2021 in relation to the earlier period of 2017-2019.  In other words, the rate of appeals allowed and consents granted is statistically and significantly higher over the past two years than one might expect in relation to pre-Covid levels. 

 

This association has been wholly influenced by Minister and reporter-led decision making during 2021, at a 99% level of confidence, and is unlikely to have happened by chance. 

 

The paper is unable to attribute a reason for the increase other than to establish one exists, although whether the increase is an anomaly or part of a longer-term trend is unknown at this stage.  

 

The Scottish Government declined to comment on an earlier version of the paper.

 

1 Introduction

 

The Scottish Government published information in January 2022, following a request by Oliver Mundell MSP, on the approval rate for wind farm applications in each local authority area broken down by those a) determined and b) not determined by Scottish Ministers in the last five years.[1]  A copy of the Scottish Parliament’s answer to this request is shown in Annex 1 while Table 1 below provides a summary showing appeal approvals and consent decisions over the 5-year period of interest.

 

Table 1 Summary of Scottish Government response on wind farm appeals and consents

Year

Appeals (<=50MW)

Section 36 (>50MW)

 

Allowed Minister

Allowed Reporter

Refused

Minister Consent

PLI Consent[2]

Refused

2017

1

10

5

2

7

2

2018

0

7

9

3

2

3

2019

1

8

6

8

2

5

2020

0

2

5

6

2

1

2021

0

4

0

12

6

1

Total

2

31

25

31

19

12

  

The summary figures for appeals allowed in Table 1 are taken from Table A1 of  Annex 1, which illustrate the Scotland-wide position in relation to on-shore wind farm planning appeals of up to and including 50MW capacity covering the period 2017 to 2021.  All but two appeals (in Argyll and Bute – in 2017 and 2019) were decided by reporters from the Planning and Environmental Appeals Division of the Scottish Government.  The two in Argyll and Bute were allowed by Scottish Ministers.  Meanwhile, the consent figures in Table 1 are taken from Table A2 of the Annex from determinations made by applications for wind farms under Section 36 of the Electricity Act 1989 (over 50MW capacity) where a Public Local Inquiry was held and chaired by a reporter following an objection by the relevant planning authority.  Where the planning authority did not object the decision to consent was taken by Scottish Ministers.  

 

Using the data from Table 1 an evaluation of the percentage of appeals allowed and the Section 36 applications consented compared to those refused is provided in Table 2.  It can be seen here that what may be considered as the Covid-19 period (2020-2021) has had little impact on the rate of appeals allowed compared with the pre-Covid-19 performance although, significantly, the rate of appeals allowed in 2021 has almost doubled compared to the pre-Covid-19 rate.[3]  The rate for consents during the Covid-19 period also increased for both 2020-2021 (93%) and 2021 (95%) compared to  the pre-Covid-19 rate of 71%.

 

Table 2 Percentage (or rate) of appeals allowed and Section 36 applications consented

Period

Appeal Allowed (%)

Consented (%)

2017-2021

Overall

57

81

2017-2019

Pre-Covid Period

57

71

2020-2021

Covid Period

Covid Period

53

93

2021

100

95

 

This simple comparative evaluation helps substantiate observations made by several Scottish wind farm campaign groups – local and national.  Examples of these qualitative observations include: “…we have noticed that approval rates are high…” (Personal communication, Milligan, I. email reply from Save our Hills, 13 June 2022), “…as far as we are aware there has only been one wind farm refused at appeal since covid began…”(Personal communication, Proctor, T. email reply from Help Save Mochrum Fell, 12 June 2022), and “…there were no S36’s refused for over a year until Glenschero was refused in March 2022 as far as I remember…” (Personal communication, Jackson, A. email replies from Scotland Against Spin, 12 and 26 June 2022).

 

It should, perhaps, come as no surprise if the rate of appeals allowed and Section 36 applications consented have been influenced by Covid-19 and the subsequent lockdown in Scotland, which commenced on the 24 March 2020, along with a further lockdown on the 5 January 2021 (Scottish Parliament, 2022).  The Scottish Government, in reviewing planning performance statistics over this period acknowledge that the number of applications submitted as well as the processing and deciding of applications was impacted from several perspectives (Scottish Government, 2021).  

 

Some authorities commented, for instance, that there had been a noticeable reduction in the number of applications, especially over the first two quarters of 2020 with a marked increase in the last two quarters.  Furthermore, following lockdown, planning application processing was impacted by the move to home working , restrictions on travel and site access, reduced availability of agents and consultees as well as staffing and resource issues.  

 

The Scottish Government report also highlights the negative impact from the ability of planning committees to meet as a result of lockdown restrictions and while these combined restrictions affected each authority differently with varying degrees and durations of impact the overall effect on both submissions and processing may help explain the higher than normal number of Section 36 consents occurring in 2021 (as shown in Table 1), which may have, in part at least, been due to delays in determination in 2020.  It is possible too that resource availability and restrictions at local authority level negatively impacted determination, where at least one local authority (Dumfries & Galloway) is cited as “…failing to participate meaningfully, or at all, in the decision making process…” (Personal communication, Proctor, T. email reply from Help Save Mochrum Fell, 12 June 2022).

 

The question this rather simple evaluation raises and which is the subject of this paper, is: 

 

In light of these quantitative data along with qualitative observations from several sources; is the change in the rate of appeals allowed and Section 36 applications consented between the pre-Covid (2017-2019) period and what may be considered as the Covid-19 period (2020-2021) statistically significant?In other words, if there is a difference is it unlikely to have occurred by chance?

 

The following Chapter discusses this issue and begins by setting out the methodology adopted by which to address this question.

 

2 Methodology

 

The methodology adopted in this paper is used to examine whether there is a statistically significant relationship, or association, in the rate of decision making to accept following an appeal or to consent a Section 36 application pre-Covid compared to similar outcomes made during Covid, when many of the normal operating procedures of government along with resource availability, local and central, may have been impacted. It has to be appreciated, however, that even if association is shown to exist it does not imply causation.

 

The analysis of data in Tables A1 and A2 in Annex 1 and as summarised in Table 1 is made against the following criteria:

 

2.1 Timing

 

The period 2017-2019 is assumed to be representative of pre-Covid and is regarded as a collective or pooled period during which, it is assumed, normal appeal accepting and consenting decision processes are deemed to have occurred.  However, the period representing performance during Covid is more difficult because while Covid resulted in a period of ‘lockdown’ with work from home except for essential workers, this did not occur until part way through 2020 and as the data in both tables (provided by the Scottish Government) gives no indication of the point leading up to lockdown when applications were made, heard and decided the Covid period for this analysis is assumed to be represented by the period 2020-2021.

 

2.2 Sample Size 

 

As a general rule the level of confidence in statistical models increases with sample size  - to some upper level, while on the other hand small samples sizes can present challenges and lead to diminished confidence.  Consequently, and because interest here lies in the decisions reached by representatives from the Planning and Appeals Division of the Scottish Government – nominated reporters, along with those of Scottish Ministers, data from Tables A1 and A2 of Annex 1 has been combined.  In practice, this means columns 2,3,5 and 6 from Table 1 has been combined to represent the combined rate of appeals allowed and Section 36 applications consented.  In a similar manner, columns 4 and 7 are combined to represent the overall refusal performance for each year.

 

This pooling of data is considered both desirable, in increasing sample size, and compatible in so far as all decisions have been reached by representatives of the Scottish Government using, presumably, similar procedures, guidelines and professional judgements.

 

 2.3 Exceptions

 

Notes to Table A2 in  Annex 1 mentions consents relating to Fallago Rig and Farr wind farm and these have been ignored as both were extensions to existing operational wind farms.

 

2.4 Analysis

 

Pooled frequency data (based on reporter and Minister decision making) is calculated and displayed in a contingency table to reflect the relationship between the categorical variables of interest, namely: Period of Approval and reporter+Minister Decisions.  Pearson’s chi-square test of association is then used to test the hypothesis about the distribution of observations in the different categories.  The null hypothesis, H0: is that the observed frequencies are the same as the expected frequencies except for chance variation.  Expressed another way – the null hypothesis, H0: represents no difference in the combined appeal approval and consent rates over the two periods of interest.

 

If the observed and expected frequencies are the same then the value of chi-square, denoted X2, is equal to zero.  If on the other hand there is a difference between observed and expected frequencies the value of Xincreases and when this value is sufficiently large in relation to published tables of chi-square distribution the more likely it is that the distribution in this example, for Period of Approval and reporter+Minister Decisions, is significantly different.

 

In this particular analysis the value of X2 was calculated manually, but computer programs are available for such tasks. 

 

3 Results

 

The combined, or pooled, data is shown below in the form of a contingency table where the relationship between the two variables, Period of Approval (Pre-Covid, 2017-2019 and Covid, 2020-2021) and reporter+Minister Decisions (Appeal Allowed or Consented, and Refused) is shown with  individual cell values representing the combination of count or frequency values from Table 1 based on  data provided by the Scottish Parliament.  These cell values therefore represent the observed frequencies.

 

Table 3 Observed frequency of reporter+Minister Decisions 2017-2019 vs 2020-2021

 

Period of Approval

Pre-Covid (2017-19)

Covid (2020-21)

Observed frequency of decisions by reporter+Minister

Appeal Allowed and Consented

51

32

Refused

30

7

 

With this categorical data describing the relationship between the independent variables, reporter+Minister Decisions and Period of Approval, Pearson’s chi-square test of association has been used to determine if there is an association between them.  In other words the goal of this test is to determine whether the null hypothesis, Ho: stands, and if not then the alternative hypothesis, H1: can be accepted - the frequency or rate of pre-Covid decision making differs to that during Covid. 

 

Table 3 therefore reflects the combined decisions reached by reporters and Ministers during both these periods and it appears from the data that there is a difference, with 30 cases refused pre-Covid to 51 appeals allowed and consented while only 7 cases were refused yet 32 appeals allowed and consented during Covid.  The question is whether this observed difference is significant from the pattern of frequencies one would expect to see by chance – if there was no relationship between the variables and only random variation. 

 

While it is possible to calculate the value of the X2 statistic using programs such as IBM’s SPSS, or even MS Excel, as this is a 2x2 matrix it is possible to calculate the value manually by determining the expected count, or the expected frequency of decision making by reporters and Ministers, using the equation:

 

Expected cell frequency = (Row Total x Column Total)/Sum of Row or Column Totals ………(1)

 

in which non-integer values are expressed to the nearest integer value.  Table 4

shows the result of this exercise to calculate the expected frequencies.

 

Table 4 Expected frequency of reporter+Minister decisions 2017-2019 vs 2020-2021

 

Period of Approval

Pre-Covid (2017-19)

Covid (2021-2021)

Expected frequency of decisions by reporter+Minister

Appeal Allowed and Consented

56

27

Refused

25

12

 

Table 4 suggests that if there were no relationship between the variables – other than by chance, then a greater number of refusals would have occurred during Covid.  The question is, is this statistically significant?

 

By making use of the cell values for observed and expected frequencies from Tables 3 and 4 the value of X2can be calculated from the expression:

 

X  Sum of (((Observed Cell Frequency – Expected Cell Frequency)2)/Expected Cell Frequency) ……..(2)

 

which yields a result of 4.46.[4]  

 

As has been stated, the null hypothesis, H0: represents no association between the two categorical variables and if there is sufficient evidence to reject H0: the alternative hypothesis, H1: is accepted - suggesting an association exists between the variables. 

 

The remaining task needed to accept or reject H0 is to look up the critical values of the chi-square distribution and compare it with the X value of 4.46 obtained from the calculation above.  

 

As the contingency table forms a 2x2 matrix there is only 1 degree of freedom ((n-1)x(n-1)) and choosing a suitable probability level of p = .05 (to represent a 95% level of confidence in the result) yields a critical value of 3.84.[5]

 

Because the test statistic X2, of 4.46, is greater than this critical value it is considered too large to have arisen by chance so it can be assumed there is a real difference between the observed and expected frequencies from Tables 3 and 4 leading to a rejection of the null hypothesis and acceptance of the alternative hypothesis.  In other words, there is an association, or relationship, between the reporter and Minister decisions pre-Covid to that during Covid.

 

However, because Pearson’s chi-square test only tests for association it is not possible to imply causation, namely it is not possible to say Covid caused the combined frequency or rate of reporter and Minister decisions to allow appeals and to consent, to change – but there is a relationship, and it is one that deserves to be explored further.

 

4 Discussion and Conclusions

 

The analysis in Chapter 3 proves the presence of a statistically significant relationship between the rate of appeal approvals and consents during 2020-2021 compared to what is considered the base-line period, 2017-2019, prior to Covid.  This result also supports the qualitative observations made by several campaign groups across Scotland.

 

This increased rate of appeal approvals and consents during 2020-2021 does not necessarily chime well with what might be expected based on the planning performance statistics report (Scottish Government, 2021), which describes the impact Covid had on Scotland’s national and local planning system.  Nothing in this report refers to a change of emphasis, urgency, process or procedure in on-shore wind farm appraisals that might lead to such an increase.  

 

Two further hypotheses emerge from this discourse, both of which can be tested from  data shown in Table 1.  These represent a more granulated evaluation of the hypothesis described in Chapter 2 and are represented as:

 

H0: there is no difference in the combined appeal approval and consent rate by reporters and Ministers during 2020 compared to 2017-2019, and 

 

H0: there is no difference in the combined appeal approval and consent rate by reporters and Ministers during 2021 compared to 2017-2019.

 

Before testing these hypotheses there is a caveat relating to the un-pooling of the previous  pooled data.  This relates to Pearson’s chi-square test and small expected cell values that result in reduced confidence if any cell is lower than the prerequisite value of 10 (Horn, 2012). Saunders, Lewis and Thornhill (2007), on the other hand argue that this value is excessive and is only for guidance while Silver (1997, p.110) takes a pragmatic view by stating that expected values should be “…not too small…,” suggesting that providing the smallest expected value is greater than 3 the test statistic, X2, may be used.

 

Sapsford (2007), on the other hand, proposes a rule of thumb whereby every expected cell value must be greater than 5, although in larger tables a few less than this is acceptable so long as they are randomly distributed.  Field (2013) also supports the notion of 5 as the minimum value, because at this level the sampling distribution is close enough to a perfect chi-square distribution.  Consequently, in the following evaluations  with the use of un-pooled observed data from Table 1 if any expected cell value is less than this minimum the more demanding Fisher’s exact test for statistical significance will be used (Freeman and Campbell, 2007).

 

To test the first hypothesis – the performance in 2020 against 2017-2019 Table 5 shows the observed data extracted from Table 1 in the form of a contingency table.

 

Table 5 Observed frequency of reporter+Minister decisions 2017-2019 vs 2020

 

Period of Approval

Pre-Covid (2017-19)

Covid (2020)

Observed frequency of decisions by reporter+Minister

Appeals Allowed or Consented

51

10

Refused

30

6

 

Using equation (1) the expected cell data has been computed and is shown in Table 6.

 

Table 6 Expected frequency of reporter+Minister decisions 2017-2019 vs 2020

 

Period of Approval

Pre-Covid (2017-19)

Covid (2020)

Expected frequency of decisions by reporter+Minister

Appeals Allowed or Consented

51

10

Refused

30

6

 

In this case the observed and expected cell values from the two Tables are identical, which means that applying these cell values to equation (2) results in a chi-square test statistic, X2 equal to zero.  In other words, the null hypothesis, H0: cannot be rejected - there is no difference in the combined appeal approval and consent rate by reporters and Ministers during 2020 compared to 2017-2019, only random variation.

 

Turning now to the second hypothesis – comparing the frequency of decisions by reporters and Ministers over the periods 2019-2019 against 2021 the observed cell data is shown in Table 7 while the expected data can be seen in Table 8.

 

Table 7 Observed frequency of reporter+Minister decisions 2017-2019 vs 2021

 

Period of Approval

Pre-Covid (2017-19)

Covid (2021)

Observed frequency of decisions by reporter+Minister

Appeals Allowed or Consented

51

22

Refused

30

1

Table 8 Expected frequency of reporter+Minister decisions 2017-2019 vs 2021

 

Period of Approval

Pre-Covid (2017-19)

Covid (2021)

Expected frequency of decisions by reporter+Minister

Appeals Allowed or Consented

57

16

Refused

24

7

 

As all expected cell values in Table 8 exceed the minimum value of 5, Pearson’s chi-square test of association is valid, and using equation (2) and inserting the respective observed and expected cell values result in a value for X= 62/57 + 62/24 + 62/16 + 62/7 = 9.8.  In this instance the null hypothesis H0: can be rejected and by comparing the test statistic against footnote 5 it is possible to infer an association exists between reporter and Minister decision making pre-Covid against that of 2021 with a 99% level of confidence.

 

It can be concluded, therefore, that if there was a change of emphasis, urgency, process or procedure in appeal approving and consenting of on-shore wind farm proposals by reporters and Ministers then it can be said, with a very high level of statistical confidence, that this occurred during 2021.  

 

Whether this change occurred by design or chance, or whether it was a short-term anomaly or longer-term in nature cannot be determined from available data.  Furthermore, and as Annex 2 shows, the Scottish minister declined to comment on an earlier draft of this paper on the grounds that the decision making process for onshore wind proposals is fully open, transparent and fair.

 

It is suggested that this temporal analysis should be extended in future to include 2022 data and beyond, to address whether, post-Covid, the reporter and Minister decision making frequency rate has reduced back to pre-Covid levels or whether the 2021 performance marks a new baseline.


Endnotes


[1] This information was published in the form of a written answer by the Scottish Parliament, reference S6W-05215, dated 24 January 2022.

[2] The term, PLI, refers to a Public Local Inquiry, which is held following an objection by the relevant planning authority

[3] Appreciating, of course, that the small sample size can increase the volatility of the result.

[4] Taking cell data from Table 3 (observed values) and Table 4 (expected values) the chi-square test statistic is equal to the sum of (5x5/56) and (5x5/25) and (5x5/27) and (5x5/12) = 4.46

[5] Field (2013) in Appendix A.4. shows that with 1 degree of freedom, as is the case here, the critical value of Xtaken from the chi-square distribution is 3.84 with p = 0.05 (95% probability) and 6.63 with p = 0.01 (99% probability).

References

Field, A. (2013) Discovering Statistics using IBM SPSS Statistics. 4th ed. London: Sage Publications Ltd.

Freeman, J.V. and Campbell, M.J. (2007) The analysis of categorical data: Fisher’s exact test.  [Online] Available: https://www.sheffield.ac.uk/polopoly_fs/1.43998!/file/tutorial-9-fishers.pdf [Accessed 30 January 2022]

Horn, R. (2012) Researching and Writing Dissertations. 2nd ed. London: CIPD.

Open University (2022) Chi Square Analysis [Online] Available: https://www.open.ac.uk/socialsciences/spsstutorial/files/tutorials/chi-square.pdf [Accessed 30 January 2022]

Sapsford, R. (2007) Survey Research. 2nd ed. London: Sage Publications Ltd.

Saunders, M., Lewis, P. and Thornhill A. (2007) Research Methods for Business Students. 4th ed. Harlow: Pearson Education Ltd.

Scottish Government (2021) Planning Performance Statistics 2020/21. [Online] Available: https://www.gov.scot/collections/planning statistics [Accessed 27   May 2022]

Silver, M. (1997) Business Statistics. 2nd ed. Maidenhead: McGraw-Hill Publishing Company.

Spice (2022) Timeline of Coronavirus (Covid-19) in Scotland. [Online] Available: https://spice.spotlight.scot/2022/timeline-of-coronavirus-covid-19-in-scotland/ [Accessed27 May 2022]

Weisstein, Eric W. "Fisher's Exact Test." From MathWorld--A Wolfram Web Resource. [Online] Available: https://mathworld.wolfram.com/FishersExactTest.html [Accessed 30 January 2022]

 

Annex 1

 

The tables below show the position in relation to planning appeal approvals and consents over the period 2017-2021 supplied by the Scottish Parliament as a written answer under question S6W-05215.  

 

In Table A1 all bar two appeals were decided by reporters from the Planning and Environmental Appeals division of the Scottish Government.  The two appeals not decided by reporters, but shown in Table A1, were in Argyll and Bute - one in 2017 and one in 2019, and both were allowed by Scottish Ministers.  

 

Table A1 Planning Appeals

 

2017

2018

2019

2020

2021

Planning Authority

Cases

Appeal Allowed

Percentage Allowed

Cases

Appeal Allowed

Percentage Allowed

Cases

Appeal Allowed

Percentage Allowed

Cases

Appeal Allowed

Percentage Allowed

Cases

Appeal Allowed

Percentage Allowed

Aberdeenshire

 

 

 

 

 

 

 

 

 

1

1

100%

1

1

100%

Argyll and Bute

1

1

100%

1

1

100%

2

1

50%

 

 

 

 

 

 

Scottish Borders

 

 

 

3

3

100%

2

1

50%

2

0

0%

 

 

 

Dumfries and Galloway

2

0

0%

1

0

0%

3

1

33%

1

0

0%

2

2

100%

East Ayrshire

6

4

67%

5

1

20%

1

1

100%

 

 

 

 

 

 

East Renfrewshire

 

 

 

1

0

0%

 

 

 

 

 

 

 

 

 

Fife

1

1

100%

 

 

 

 

 

 

 

 

 

 

 

 

Highland

4

3

75%

2

0

0%

2

1

50%

 

 

 

1

1

100%

Moray

 

 

 

 

 

 

1

1

100%

 

 

 

 

 

 

North Lanarkshire

1

1

100%

 

 

 

 

 

 

 

 

 

 

 

 

Orkney Islands

 

 

 

 

 

 

2

2

100%

 

 

 

 

 

 

Perth and Kinross

 

 

 

1

1

100%

1

1

100%

 

 

 

 

 

 

South Ayrshire

1

1

100%

 

 

 

1

0

0%

2

1

50%

 

 

 

South Lanarkshire

 

 

 

1

1

100%

 

 

 

1

0

0%

 

 

 

West Lothian 

 

 

 

1

0

0%

 

 

 

 

 

 

 

 

 

Total

16

11

69%

16

7

44%

15

9

60%

7

2

29%

4

4

100%

 

 

The following table confirms determinations made by Scottish Ministers on applications for wind farms made under Section 36 of the Electricity Act 1989, where a Public Local Inquiry was held following an objection to a wind farm by the relevant planning authority(s) (i.e. the planning authority(s) for the land on which the wind farm would be built). Where the planning authority did not object consent was granted by Scottish Ministers. The percentage consented column therefore only refers to cases where a public inquiry chaired by a reporter was necessary.

 

Table A2  Section 36 Consents

 

2017

2018

2019

2020

2021

Planning Authority

Decisions

PLI required

Percentage Consented (post PLI)

Decisions

PLI required

Percentage Consented

Decisions

PLI required

Percentage Consented

Decisions

PLI required

Percentage Consented

Decisions

PLI required

Percentage Consented

Argyll and Bute

2

2

0%

 

 

 

3

2

0%

2

0

 

1

1

100%

Dumfries and Galloway

1

1

100%

 

 

 

1

0

 

2

0

 

3

2

50%

Dumfries and Galloway/

South Ayrshire

 

 

 

 

 

 

 

 

 

1

0

 

1

0

 

East Ayrshire

 

 

 

2

1

100%

1

1

100%

1

0

 

3

0

 

East Ayrshire/

Dumfries and Galloway

1

1

100%

 

 

 

 

 

 

 

 

 

 

 

 

Highland

4

3

67%

3

3

33%

4

2

50%

 

 

 

3**

2

100%

Moray

1

1

100%

 

 

 

 

 

 

1

1

100%

1

0

 

North Lanarkshire

 

 

100%

 

 

 

 

 

 

 

 

 

 

 

 

Perth and Kinross

 

 

 

 

 

 

1

1

0%

 

 

 

 

 

 

Scottish Borders

1

1

100%

1

1

0%

 

 

 

1*

1

0%

1

0

 

Scottish Borders/East Lothian

 

 

 

 

 

 

1

0

 

 

 

 

1

1

100%

Shetland Islands

1

0

 

 

 

 

1

0

 

 

 

 

 

 

 

South Ayrshire

 

 

 

1

0

 

 

 

 

1

0

 

1

0

 

South Ayrshire/

Dumfries and Galloway

 

 

 

 

 

 

 

 

 

 

 

 

1

1

100%

South Lanarkshire

 

 

 

 

 

 

3

1

0%

1

0

 

3

0

 

South Lanarkshire/West Lothian

 

 

 

1

0

 

 

 

 

 

 

 

 

 

 

Total

11

9

78%

8

5

40%

15

7

29%

9*

3

67%

19**

7

86%

 

* Does not account for Fallago Rig variation which was for an extension of operational period to a wind farm which was already built and operating.

 

** Does not account for Farr Wind Farm variation which was for an extension      of

operational period to a wind farm which was already built and operating.


Annex 2


Minister for Public Finance, Planning & Community Wealth
Ministear airson Ionmhas Poblach, Dealbhachadh agus Beartas Còimhearsnachd 

Tom Arthur BPA/MSP 

T : 0300 244 4000
E : scottish.ministers@gov.scot 


Oliver Mundell MSP Ann.Menzies@parliament.scot 

Our Reference: 202200310645 Your Reference: OM/Jones/AM 

25 July 2022 


Dear Oliver, 

Thank you for your e-mail of 11 July enclosing an appraisal by Dr Jones concerning on-shore wind farm appeal and consenting performance. 


In the first instance I would confirm that all the decisions referred to in the appraisal were final subject to any possible legal challenge. I am sure you will appreciate in these circumstances that it would not be appropriate for me to comment on either the development proposals or the decisions themselves. 


I can confirm that the Scottish Government is committed to providing clean, green energy from the right developments in the right place. Assessing the environmental impacts is a key part of all wind farm proposals and is fully considered together with cultural heritage, ecological, aviation, acoustic, economic and local community effects. 


Whilst each case is ultimately decide on its own merits, in all cases submissions made by parties are fully considered taking into account matters including Scottish Government policy and UK Government policy on reserved matters, the National Planning Framework, Scottish Planning Policy, consultation responses, views of affected communities and representations made by members of the public, as well as the public inquiry report (in cases decided by Scottish Ministers), before a final decision is made. The merits of each proposal are considered on a case by case basis and a careful balance must be struck between the potential impacts of the development and the associated environmental, economic, renewable energy and climate change benefits. This ensures the right developments are planned, approved then completed, in the right places. With regard to Scottish Government policy you will be aware of the First Minister’s declaration of a global climate emergency in April 2019 and I can confirm that evidence in relation to this is being put before reporters by parties involved in cases. 


It is important to stress that reporters appointed to cases are solely responsible for the decision or report. No other party, including Scottish Ministers, has any input to that. All matters that are considered by the reporter are in the public domain and DPEA also publish all the case submissions which are considered by reporters in relation to each case. 


I can confirm that during Covid DPEA maintained a high level of service and whilst innovative approaches were adopted, such as virtual hearings and inquiries, DPEA took great care to ensure that no parties were prejudiced by this or were unable to fully participate in the process. Where such difficulties arose, the case was put on hold until such time as all parties could fully participate. 


Finally I can say that I am confident that the decision making process on on-shore wind proposals is fully open, transparent and fair and am not minded, at this stage, to carry out further analysis of matter raised in Dr Jones appraisal. 

Yours sincerely 


TOM ARTHUR 



 

 

 

 

 

     


 

 

 







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