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Publication - Report

Climate change: evidence review of mitigation options in the Transport sector

Published: 19 Jan 2017
Part of:
Environment and climate change
ISBN:
9781786527554

Evidence review of potential climate change mitigation measures in the Transport sector.

51 page PDF

654.8kB

51 page PDF

654.8kB

Contents
Climate change: evidence review of mitigation options in the Transport sector
6 Improve transport efficiencies

51 page PDF

654.8kB

6 Improve transport efficiencies

6.1 Lower carbon vehicles and fuels

6.1.1 Overview

The use of lower carbon fuels and vehicles can offer energy security and air quality benefits ( e.g. Smith et al., 2016). The air quality benefits will, however, depend on the fuels used, with the use of diesel (for carbon reduction) potentially having adverse impacts on air quality. For electric vehicles there is the potential for substantial local air quality benefits (especially in cities e.g. Jochem et al, 2016) reflecting that transport is a major source of air quality emissions. The air quality benefits of electric vehicles can be reduced by emissions produced during electricity generation ( e.g. Buekers et al., 2014) and so these benefits can be influenced by the power generation mix and the number of people exposed to pollution from the power plants. The need for further research on the potential adverse side effects on land and water from mining and manufacturing processes required for electric vehicle materials is identified in the SPLiCE (2016) work. In terms of economic benefits Wells (2012) identifies the potential for wealth and employment related impacts. There is limited consideration within the co-benefits literature of the impacts of an electrification of the rail network - anticipated benefits could include reductions in air quality pollutant and journey time savings.

For biofuels, there is a range of potential adverse side effects on land use (direct and indirect changes), biodiversity, food security, health, water use and water quality ( e.g. Renewable Fuels Agency, 2008) which depend strongly on the biofuel feedstock, with second generation biofuels ( e.g. waste or woody material) generally being far less damaging than those from food crops (such as maize, soy and sugar beet). These impacts need to be factored in and mitigated, for example through the enforcement of strict sustainability criteria ( e.g. Smith et al., 2016). Rushton et al. (2014) provides a good synthesis of key issues for UK produced and imported crops. The potential for benefits, for example, in terms of employment opportunities and rural development is also identified. The study suggests that there is limited evidence on these social impacts for waste products. However, recent work by the ICCT (2015) highlights that the use of wastes (and residues) could offer economic benefits including additional jobs. In the Scottish context Celtic Renewables, based in Edinburgh, have received £11 million to develop a new plant to make biofuels from whisky by-products with a further 3 plants planned [4] .

Noise pollution from transport vehicles can have a broad range of negative health impacts including disturbed sleep patterns, reduced cognitive function, raised blood pressure, stress, and cardiovascular disease (Boer and Schroten, 2007; WHO, 2011). Electric and hybrid vehicles offer the potential for noise reduction especially in urban areas (Jabben, 2012). Here, it is important to note that tyre noise and the vehicle itself dominates the noise profile at over 25 mph (Jochem et al., 2016). Any potential for noise reduction also need to be seen in the context of broader reductions in noise limit values and the associated reduction in vehicle noise ( EC, 2014) and safety concerns related to people not hearing the vehicles ( e.g. Czuka, 2014; Altinsoy, 2013), especially when driving speeds are lower and where there is background noise (highly relevant in the urban context). Reflecting this, the European Commission ( EC, 2014) has confirmed that electric and hybrid vehicles are to be fitted with sound generating devices. In any modelling of noise-reduction benefits, the impact of these sound generating devices would need to be taken into consideration.

6.1.2 Quantitative approaches

There is an emerging literature and publically available datasets which will assist in the quantification of the co-benefits associated with moves towards lower carbon vehicles and fuels. For air quality, quantification can occur at a detailed, local level (for example through air quality models) or at a higher, overview level. For the latter, which is typically more appropriate for the appraisal of broader policies the quantification needs to capture 1) potential reductions in the level of pollutants emitted and 2) the cost of the pollutants.

To capture potential reductions in pollutants Defra and the Devolved Administrations publish the Emissions Factor Toolkit which allows users to calculate road vehicle pollutant emission rates for air quality pollutants - NO x, PM 10, PM 2.5 (and CO2) for a specified year, road type, vehicle speed and vehicle fleet composition ( Defra, 2016). The current version of the tool was updated in August, 2016 and includes Emission Factors for lower carbon vehicles (alternatively fuelled vehicles). For the cost of pollutants Defra provide detailed guidance on Economic Analysis and Air Quality ( Defra, 2015). In terms of modelling approaches, there are currently limited, publicly available models.

For noise co-benefits again there is a need to capture the level of potential noise reductions. Again there is a need to understand the level of noise saving from the use of electric vehicles. Here there is an emerging literature on noise savings which takes into account vehicle speeds and tyre noise ( e.g. Pallas et al., 2016). These noise savings would then need to be placed into the context of monetary values. Here it is useful to note the differences between STAG and Web-TAG with regard to the treatment of noise including monetisation (discussed further in Chapter 7.1.1).

6.1.3 Equalities

Social distributional impacts of electric vehicles are a research priority ( SPLiCE, 2016): while there is a limited consideration in the co-benefits literature, evaluation is increasing elsewhere ( e.g. Skinner et al., 2011; Lucas and Pangbourne, 2014; Wells, 2012). For example, Wells (2012) highlights the exclusion of disadvantaged groups from electric mobility. Car clubs could offer the opportunity for broader range of socio-economic groups to access this mobility though further evidence is required to better understand this potential. The requirement for better understanding of access to opportunities e.g. the skill sets required for electric vehicle production is also identified ( SPLiCE, 2016) and within this there may be equity considerations.

One particular aspect of relevance is the need to take into account the current spatial distribution of air quality impacts. There are clear links between socially deprived neighbourhoods and exposure to higher levels of air pollution (Namdeo and Stringer, 2008; King and Healy, 2013). Since lower emission vehicles such as hybrid vehicles and electric vehicles can offer GHG emission reduction and air quality benefits there are opportunities that warrant further exploration. For example, the geographic positioning of demonstration schemes and grants could also target lower income households helping ensure the social and distributional benefits of policies (Skerlos and Winebrake, 2010).

6.2 Network efficiencies

Improvements in network efficiencies include the use of average speed cameras, intelligent transport systems and fuel efficient driving. These are considered in turn below. Reflecting the relatively limited information available, qualitative, quantitative and equalities perspectives are considered together.

6.2.1 Average speed cameras

Soole et al. (2013) in a wide ranging review of the literature draw on a number of benefits. These benefits include:

  • Road safety benefits including reductions in crash rates. These reductions are, in particular, in relation to fatal and serious injury crashes, with a decreasing trend of the magnitude of 33% to 85%.
  • I mprovements in traffic flow due to reductions in speed variability.
  • Favourable cost-benefit ratios are suggested though there was less evidence and less analysis for this.

A high level of compliance was noted reflecting a corresponding level of public acceptance, reflecting the perceived fairness of the approach.

Equalities perspectives were not identified in the literature. Road accidents can be more likely to impact on vulnerable socio-economic groups e.g. those in areas of higher deprivation (Jones et al., 2008), and this is, therefore, an area worth further consideration.

6.2.2 Intelligent transport systems

Intelligent transport systems include Active Traffic Management ( ATM), Intelligent Speed Adaptation ( ISA) and the Automated Highway Systems ( AHS). There is limited literature on wider benefits. However, all three are evaluated in a study by Kolosz and Grant-Muller (2015) which identifies, in addition to fuel and vehicle emission savings, the potential for accident savings across all three options. In terms of cost benefit ratios only ATM had favourable levels: these were around 5.89 in the shorter term, but decreased over time reflecting assumptions with regard to increased energy cost.

6.2.3 Fuel efficient driving

Fuel efficient (eco-driving) driving facilitated through training can benefit private and fleet drivers. These benefits typically involve fuel cost savings (Zarkadoula et al., 2007; Barkenbus, 2010; Sivak and Schoettle, 2012). However, these could be reduced through the rebound effect. Literature exists which suggests that there are potential reductions in accident risk ( e.g. SenterNovem, 2005; Cristea et al., 2012). However, others ( e.g. Saniul Alam and McNabola, 2014) suggest that if eco-driving occurs at the individual rather than group level then this 'unusual' driving behaviour can affect other drivers and in turn alter their behaviour e.g. due to annoyance increased over-taking could occur (Ando and Nishihori, 2011). Thus, the evidence here could be considered potentially inconsistent at this stage. Furthermore, the use of driver assistance could increase the accident risk ( e.g. Saniul Alam and McNabola, 2014).

Lucas and Pangbourne (2014) consider the equity impacts of fuel efficient driving highlighting that benefits would typically accrue to those that already owned cars (therefore not typically considered a more vulnerable group). There is however the potential, if the fuel savings result in air quality benefits, for there to be broader distributional benefits.


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Email: Debbie Sagar