Economic, Environmental and Social Impacts of Changes in Maintenance Spend on the Scottish Trunk Road Network

13 Summary of changes and impacts

13.1 Results summary

The overall results from this study are presented in Error! Reference source not found. and Error! Reference source not found..

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Table 13.3 summarises the overall effects caused by Scenario 2 (20% overall maintenance budget reduction) and Scenario 3 (overall 40% maintenance budget reduction) compared to Scenario 1 (maintain the 2010 maintenance budget), the Base Case.

13.2 Results discussion

The overall outcome from the study is that compared with the effect of maintaining the 2010 maintenance budget for 20 years, for the funding Scenarios analysed, the vehicle operating costs were predicted to increase. There is little overall change in the other costs to society considered in this study so to see the net socio-economic effect, the increase in vehicle operating costs should be compared with the reduction in maintenance works costs to Transport Scotland. For the levels of budget reduction considered in this study, the increase in vehicle operating costs more than offsets the reduction in the direct Transport Scotland costs, so the net effect is a reduction in economic welfare.

These results do not include the change in residual value of the network for the different scenarios. The residual value can be considered analogous to the asset value. For the scenarios representing budget reductions over the first 10 years of the analysis period (i.e. Scenario 2, a 20% reduction in the overall maintenance budget, and Scenario 3, a 40% reduction in the overall maintenance budget), compared with the effect of maintaining the 2010 level of maintenance funding (i.e. Scenario 1), there was little change in the asset value for Scenario 2 but with Scenario 3, the reduction in asset value was predicted to be approximately half the net increase in total transport cost.

For the scenarios for budget reductions, the changes in road user costs relative to the base case are most significant for the changes in vehicle operating costs due to changes in surface condition (e.g. in year 2020/21 an annual difference of £62m undiscounted between the costs expected if the current level of maintenance funding was continued and the level that has been predicted after a 40% budget reduction in the maintenance budget). In year 2030/31, after the period of restoring and increasing the annual budgets, for Scenario 3, the undiscounted vehicle operating costs were still £49m higher than in the Base Case.

The effect of discounting the future costs changed the effects as the distribution of costs through the analysis period was not uniform over the 20 years analysis period. For the discounted costs, the Net Present Value for the economic analysis showed an overall increase in the total transport cost compared to the Base Case but the increase was smaller for Scenario 3 (i.e. a 40% reduction in the overall maintenance budget) than for Scenario 2 (i.e. 20% reduction in the overall maintenance budget).

The results of the analyses are heavily dependent on the pavement conditions predicted by the pavement network model. The model shows an improvement in Motorway condition over time at the expense of deterioration in single carriageway APTRs while funding was reduced. Changes in the distribution of funding to road types may change the effects shown in this analysis for vehicle operating costs.

13.3 Assumptions and sensitivity

During this study it was clear that little information was available for non-pavement assets. The results of the analyses are therefore shown for the effects derived from the analysis of pavement condition. Better information on the non-pavement assets would enable more reliable predictions of the effects of cuts in the overall maintenance budget. For example, although it was expected that some maintenance budget reductions would be applied in the technology areas (e.g. signs and ITS), the effects of those reductions could not be quantified in this study.

The effects of the different levels of pavement maintenance funding were based on the predicted pavement condition from the Transport Scotland pavement network model. For the study, using data from the Transport Scotland asset database, the model was used to predict the network condition for 2013, 2017, 2020, 2025 and 2030 for each funding Scenario. Assessing the effects on network condition in intervening years by interpolation was considered sufficiently reliable for this analysis.

Based on the Pavement Network Model outputs and the transformations of the analysis parameters described in this report, some issues about the analyses undertaken have been identified.

  • No change to vehicle operating costs is predicted by the HDM-4 model until the remaining life of a road pavement reduces to around 7 years;
  • No change to average traffic speed is predicted by the analysis until the remaining life of a road pavement reduces to between 30 and 35 years;
  • Reducing the amount of maintenance work reduces the number of interventions on the network and so, in the short-term, delivers a benefit to the road user in terms of travel time (i.e. less disruption at roadworks).

The analysis assumed traffic growth and increases in the value of time, increases in the cost of vehicle fuel and improvements in vehicle engine efficiency in line with STAG (Transport Scotland, 2011b) (Transport Scotland, 2011b) and webtag guidance (Department for Transport, 2011) and summarised in Appendix D.

The Pavement Network Model expresses pavement condition as the Road Condition Index (RCI). To use the outputs from the model in other analyses (e.g. vehicle operating costs in HDM-4 and studies on the effect on traffic of deteriorating pavement condition) RCI values were converted into International Roughness Index (IRI) and 3m Longitudinal Profile Variance. There are no established transformations for these conversions so simple relationships were developed specifically for these analyses.

Table 13.1 Cumulative costs (Undiscounted)

Item

Year

2010/11

13/14

17/18

20/21

25/26

30/31

Total Agency (works) Costs (£m)

Scenario 1: Base case

141

566

1,132

1,556

2,263

2,970

Scenario 2: 20% cut

114

455

910

1,252

1,904

2,666

Scenario 3: 40% cut

85

341

683

939

1,534

2,296

Vehicle operating costs due to surface condition deterioration (£m)

Scenario 1: Vehicle operating costs

4,294

17,480

35,958

50,491

75,842

102,659

Scenario 2: Vehicle operating costs

4,294

17,502

36,060

50,693

76,237

103,226

Scenario 3: Vehicle operating costs

4,294

17,516

36,127

50,827

76,502

103,602

Increase in travel time costs due to surface conditions (£m)

Scenario 1: Travel time costs

21

85

175

246

372

509

Scenario 2: Travel time costs

21

88

189

274

430

596

Scenario 3: Travel time costs

21

90

198

292

467

654

Skid resistance analysis (£m)

Scenario 1: Accident costs

23

91

181

249

363

476

Scenario 2: Accidents costs

23

91

181

249

363

476

Scenario 3: Accident costs

23

92

191

270

391

505

Delay costs at (carriageway) roadworks (£m)

Scenario 1: Delay costs

9

35

68

89

126

162

Scenario 2: Delay costs

9

27

50

65

95

130

Scenario 3: Delay costs

9

23

41

52

79

114

Lighting analysis (£m)

Scenario 1: Lighting accident costs

8

34

67

93

135

177

Scenario 2: Lighting accident costs

8

34

68

93

136

178

Scenario 3: Lighting accident costs

8

34

69

94

137

179

CO2 Emissions (£m)

Scenario 1: CO2 costs

320

1,322

2,753

3,893

5,919

8,135

Scenario 2: CO2 costs

320

1,319

2,742

3,873

5,881

8,081

Scenario 3: CO2 costs

319

1,317

2,735

3,860

5,858

8,050

Table 13.2 Cumulative costs (Discounted)

Item

Year

2010/11

13/14

17/18

20/21

25/26

30/31

Total Agency (works) Costs (£m)

Scenario 1: Base case

141

538

1,006

1,318

1,770

2,152

Scenario 2: 20% cut

114

433

810

1,060

1,476

1,886

Scenario 3: 40% cut

85

324

607

795

1,174

1,584

Vehicle operating costs due to surface condition deterioration (£m)

Scenario 1: Vehicle operating costs

4,294

16,605

31,899

42,563

58,780

73,223

Scenario 2: Vehicle operating costs

4,294

16,625

31,985

42,723

59,063

73,599

Scenario 3: Vehicle operating costs

4,294

16,638

32,041

42,829

59,252

73,848

Increase in travel time costs due to surface conditions (£m)

Scenario 1: Travel time costs

21

81

155

208

288

362

Scenario 2: Travel time costs

21

84

167

229

329

419

Scenario 3: Travel time costs

21

85

174

244

355

456

Skid resistance analysis (£m)

Scenario 1: Accident costs

23

86

161

211

284

345

Scenario 2: Accidents costs

23

86

161

211

284

345

Scenario 3: Accident costs

23

88

169

227

305

366

Delay costs at (carriageway) roadworks (£m)

Scenario 1: Delay costs

9

34

61

76

100

119

Scenario 2: Delay costs

9

26

45

56

75

94

Scenario 3: Delay costs

9

22

37

45

62

81

Lighting analysis (£m)

Scenario 1: Lighting accident costs

8

32

60

78

105

128

Scenario 2: Lighting accident costs

8

32

60

79

106

129

Scenario 3: Lighting accident costs

8

33

61

80

107

130

CO2 Emissions (£m)

Scenario 1: CO2 costs

320

1,256

2,440

3,276

4,572

5,765

Scenario 2: CO2 costs

320

1,253

2,430

3,260

4,544

5,729

Scenario 3: CO2 costs

319

1,251

2,424

3,250

4,528

5,707

Table 13.3 Summary of quantified economic impacts for 20 year analysis period

Cumulative costs1

(£m 20022 Prices)

Undiscounted3

Discounted3

Scenario 1
(Base Case)

Scenario 2

Scenario 3

Scenario 1
(Base Case)

Scenario 2

Scenario 3

Financial Costs to Transport Scotland

Maintenance works

2,970

-304

-674

2,152

-266

-568

Impacts on Society

Vehicle operating costs

102,659

+567

+943

73,223

+376

+625

Travel time (surface condition related)

509

+87

+145

362

+57

+94

Accidents (skid related)

476

0

+29

345

0

+21

Delays (through roadworks)

162

-28

-48

119

-25

-38

Lighting (accidents)

177

+1

+2

128

+1

+2

C02 Emissions

8,135

-54

-85

5,765

-36

-58

Overall (non-works) impact

112,118

+569

+986

79,942

+373

+646

Economic analysis

Works costs reduction

Base Case

304

674

Base Case

266

568

Increase in non-works costs

Base Case

569

986

Base Case

373

646

Net Present Value4

Base Case

-265

-312

Base Case

-107

-78

(1) Annual discount rate = 3.5%.

(2) 2002 prices are 2010 prices factored by 0.81.

(3) Scenario 2 (20% reduction) and Scenario 3 (40% reduction) figures are shown as differences compared to Scenario 1 (2010/11 funding retained).

(4) Negative NPV shows an overall increase in cost (i.e. non-works costs increase more than the reduction in maintenance expenditure).

The Pavement Network Model applies maintenance to lengths in the network in worst condition (remaining life 0 years) and restores them to a remaining life of between 10 and 50 years depending on the maintenance treatment. Therefore, all roads which are restored to a remaining life of 50 years (by reconstruction or strengthening) do not contribute to the analysis again in the period to 2030. For the analyses undertaken for this study, this amounted to around 60% of the treatments applied in the first 10 years of the analysis for Scenario 3 (a 40% cut in the total maintenance budget), so even if the analysis period was lengthened, these maintained roads would have no economic impact on road user costs for the next 15 to 20 years (vehicle operating costs based on condition) or for 40 to 45 years (vehicle speed costs).

The Pavement Network Model applies maintenance treatments in all years in the same proportion as used for year 1. This assumption is reasonable when budgets are not subject to big changes but for the budget reductions considered in this study, the types and proportions of pavement maintenance treatments applied over the first 10 years of the analysis period may change during the period (e.g. more of the lower cost treatments may be applied).

For the first 10 years of the analysis period, in line with existing Transport Scotland policy, the Model applied a higher priority to maintenance of Motorways. For the second 10 years of the analysis period, an equal priority was given to all three road types (Motorways, dual APTRs and single APTRs).

The subjective assessment used in this study for the reduction in overall budget was aimed at maintaining the service to road users on the network. Transport Scotland has a programme of improvements in the provision of road user information. No effect of reducing that element of expenditure, to preserve the maintenance budget was included in this study.

All the analyses undertaken for this study have adopted single values for the many parameters needed in each part of the analysis. No sensitivity to the selected values has been undertaken in this study but a simple analysis of the effects of alternative parameter values may provide a more reliable guide to the possible effects of reducing spend on the different aspects of maintenance. In particular, changing the assumptions made in the pavement network model, that determine the predicted network condition, and the assumptions in the subjective assessment to give a revised distribution of maintenance spend, could lead to modified conclusions on the effects of the maintenance cuts.

This study has been aimed at the effects of maintenance cuts over the period to 2020 and the subsequent increase in budgets over the next 10 years. Reducing the maintenance budgets over a longer period, or a different strategy for recovery in budget levels, may show different overall effects to those shown in this study.

13.3.1 Inflation on maintenance works costs

Inflation of road maintenance costs has been up to 8% per annum in recent years, which is higher than general rates of inflation (Audit Scotland, 2011). Even if current maintenance budget levels are maintained, if the same inflationary pressure continues in future, road authorities will be able to buy less maintenance work than they can today for the same level of budget.

Road authorities use standard indices to update the value of maintenance work prices each year, to manage the risk of inflation in contract costs.

No prediction of specific road cost indices was available for the 20 years analysis period used in this study as the costs are considered too volatile to predict over the time period. Predictions for broader indices are available for more general construction costs but these are less applicable for road maintenance activities. To overcome the difficulties in predicting future price increases, a more appropriate assessment method was considered to be the use of historic trends of various indices to represent the future potential changes.

The ROCOS index (Road Construction Resource Cost Index) (BCIS, 2011) was compared against the Treasury GDP deflator, Retail Price Index and Consumer Price Index. Since 2000, the average annual differential between ROCOS and the various indices was around 4%, and against the Treasury GDP deflator it was 3.9%. Based on experience of the last 10 years, an annual rate of 4% seemed a reasonable basis on which to test the sensitivity of maintenance works costs.

The assumption was also tested finally against oil price predictions from the Department of Energy and Climate Change (Department of Energy and Climate Change, 2011). There were a range of predictions, ranging from low increases (average prices from 2010 onwards varying from 40-50% below 2008 prices) to high increases (prices rising to 40% above 2008 prices by 2015 and peaking and stabilising at 50% above 2008 prices from 2020 onwards). With the differences in these estimates and difficulties with forecasting, and the fact that prices impact on both inputs (e.g. construction price inflation) and impacts (e.g. vehicle operating costs) it was considered that for the purposes of this study, the 4% figure derived from cost price indices described above, was adopted for sensitivity tests.

The results show that the NPV of each funding reduction Scenario becomes less negative compared to the case with no differential rate for road maintenance costs. The Net Present Value for the Scenario with a 20% funding reduction moves from a net impact on society of £107m to £62m and from £79m to £-44m for the Scenario with a 40% reduction in funding. This result implies that it becomes more attractive to consider reductions to road maintenance budgets if there is high inflation for maintenance works, since the cost of delivering the benefits of road maintenance will increase during the analysis period.

However, with higher inflation for maintenance works costs, it is more beneficial to invest now in maintenance than to defer spending to a time when road authority buying power is reduced (i.e. the case not to reduce the current levels of maintenance budgets is strengthened).