4 Shift to lower carbon transport modes
Mitigation options which involve a shift to lower carbon travel includes the use of walk and cycle modes (often termed "active travel"); modal shift to public transport and the use of car clubs. These are considered in turn below.
4.1 Active travel
Modal shift to walking or cycling modes dominates the transport related co-benefits literature ( e.g. Woodcock et al., 2009; Haines et al., 2009 and Shaw et al., 2014). Examples of co-benefits arising from active travel include improved health through physical activity, and (alongside public transport and demand management measures) can contribute to improved air quality through reduced fossil fuel use, reduced congestion and reduced noise pollution (Smith et al., 2016), as well as increased economic benefits through increased footfall - the 'pedestrian pound' (Lawlor, 2014).
While there is the potential for adverse side effects from the risks of increased accidents or exposure to pollution faced by cyclists and walkers, modelling studies conclude that the benefits of physical activity outweigh these risks (de Hartog et al., 2010: Woodcock et al., 2009, 2014; Rabl and de Nazelle, 2012). However, this may not apply to younger age groups where the risks of accidents is higher (Woodcock et al., 2014).
The costs of physical inactivity in Scotland to the NHS in terms of diseases are estimated to be approximately £94.1 million annually (Foster and Allender, 2012). Social Return on Investment ( SROI) evidence indicates a return of approximately £8 per £1 invested in walking and path development projects (Paths for All, 2013). The 'Let's get Scotland Walking' strategy (2014) identifies a range of co-benefits from strategies to increase walking - connecting the elderly with their communities, a healthier and more productive workforce, carbon reductions and local economy benefits (Scottish Government, 2014). As an example of benefits for local economies, the Fife Coastal Path generated approximately £24-29 million expenditures among local businesses each year, supporting 800 - 900 full time jobs (Fife Coast and Countryside Trust, 2007). While investing in making streets more accessible for walking and cycling could increase retail sales by 30% due to increased footfall (Lawlor, 2014). The provision of good urban spaces and effective urban design can also lead to increases in both house prices and rental rates as the ability to walk to local services and shops can be linked to higher property value (Lawlor, 2014). There is on-going economic analysis with regard to health and broader benefits, summaries include, for example, the systematic review by Brown et al. (2016) updating the work by Cavill et al. (2008).
Research gaps exist with regard to the evaluation of real world active travel interventions (Smith et al., 2016). Here an emerging Scottish orientated literature can contribute to reducing these gaps: for example, the evaluation of the Scottish Government's Smarter Choices, Smarter Places pilot programme which ran from 1999-2012 assessed the impact of active travel initiatives funded by the pilot (Halden et al., 2013). The programme aimed to encourage people to reduce car use in favour of more sustainable modes. Achieving such behavioural change was intended to save people money, help to make them healthier, reduce transport emissions and develop more cohesive communities. Seven areas across Scotland took place in pilot programmes with outcomes then implemented more broadly. The evaluation highlighted that in terms of outcomes, individuals in areas where measures had been implemented were on average 6% more likely to achieve physical activity guidelines than those in areas without sustainable travel measures (Norwood et al., 2014).
In terms of air quality, congestion and noise reduction benefits, impacts relate to reductions in car vehicle kilometres driven, with potential benefits being substantial. For example, Smith et al. (2015) suggests that the congestion reduction benefits can have a Net Present Value of £48 billion for the UK over the period from 2008 to 2030. A broad evidence base suggests that interventions result in less car driver trips for example, in all seven Smarter Choices, Smarter Places study areas, the decrease in the proportion of car driver trips was greater than the background trend from comparable areas (Halden, 2013). In congestion reduction terms, opportunities exist in terms of work place travel (reflecting the peak time nature of congestion). A recent systematic review (Petrunoff et al., 2016) on the potential for active travel in work place settings suggested a median result of an 11.1% reduction in employees driving private vehicles to work. The potential for bias in a number of the studies was, however, identified. In terms of broader benefits, it will also be important to see active travel as part of an integrated package of measures ( e.g. Sloman et al., 2010), particularly at the city level. Congestion and air quality benefits will accrue depending on the potential for modal shift from car users. Thus, this package of measures could include public transport, car clubs and potentially demand management. For example, in the Petrunoff et al., (2016) study the greatest decrease in car use (a 42% reduction) was found in the intervention which combined active travel with strategies to manage travel (increased parking charges and restrictions in parking places).
4.1.2 Quantitative approaches
Transport modelling approaches aim to quantify co-benefits of active travel, with the focus predominantly on the health benefits. This project identified two key existing sets of models which were of relevance to the Scottish context. These models are:
- Health Economic Assessment Tools (
- Integrated Transport Health Impact Modelling Tool ( ITHIM) - covers walking and cycling
Future work of relevance includes the development of the Cycling Scotland - Cycling potential tool. This is of particular relevance given its broadening to include a number of co-benefits.
Health Economic Assessment Tool
The Health Economic Assessment Tool ( HEAT) was developed by the World Health Organisation ( WHO) and performs economic assessments of the health benefits of walking or cycling. It estimates the value of reduced mortality that results from specified amounts of walking or cycling. The HEAT models are used for assessments for groups of people and are designed to analyse habitual behaviour such as regular leisure time activities and commuting through walking and cycling.
The HEAT models for walking and cycling use internationally agreed methodologies and data assumptions. For walking the applicable age range is set to approximately 20 - 74 years and for cycling the applicable age range is set to approximately 20 - 64 years. These assumptions reflect insufficient information on relative risks in younger and older populations. The models enable the assessment of interventions to increase levels of walking and cycling, quantifying impacts based on the value of a statistical life, quantifying impacts for a period of up to 50 years, including benefit-cost calculations and discount rates.
Caution should be applied when utilising the tool in predominantly sedentary populations as the underlying risk estimates underpinning the models are derived from populations with a broad distribution of activity levels. The same applies for groups with very high average levels of physical activity.
The HEAT approach is currently used by Department for Transport ( DfT) web based Transport Analysis Guidance ( WebTAG) and STAG guidance. DfT WebTAG is in the process of being updated e.g. to capture premature mortality (years of life lost impacts).
A local authority wishes to implement a cycling campaign to increase cycling amongst a population of 200 individuals. Before the cycling campaign, the population with an average age structure (20 - 64 years) did not cycle at all.
One year after the cycling campaign, the cycling amongst the population increases to 30 minutes per day, 260 days per year. This is the equivalent of 130 hours of cycling per year and a 15% reduction in the risk of mortality.
With the UK specific mortality data of 249 deaths per 100,000 persons per year, the value of a statistical life ( VSL) of £3,229,114 ( UK specific value in HEAT), and a 5% annual discount rate, the annual benefits averaged over the next 10 years can be estimated to £131,000, or accumulated to £1,308,000 over the ten years.
Data required by the HEAT models largely depends on the level of detail required. The model enables users to quantify co-benefits at either a single point in time or before and after an intervention. Levels of physical activity can be input as either duration (time), distance, steps, or trips per person. Subsequently, data on the number of people benefitting from the action can be inputted, enabling a quantification of mortality risks with and without intervention. Users can further select data on the value of a statistical life, national mortality rates, and discount rates. HEAT is developed in the European context and respectively the default values employ European values. These values can, however, be adjusted to reflect local situations.
Table 4‑1 Data requirements for HEAT and potential Scottish sources
Scottish data source
An estimate of how many people are walking or cycling
Scottish Household survey
Trips per person per year
An estimate of the average duration spent walking or cycling (can be duration, distance, trips)
Scottish Household Survey
HEAT provides a default value
Data for the Scottish specific context can include:
The Integrated Transport and Health Impact Modelling Tools
The Integrated Transport and Health Impact Modelling Tools ( ITHIM) are a group of related models and tools developed at the Centre for Diet and Activity Research ( CEDAR) to provide an integrated assessment of the health effects of transport policies and scenarios at a national and urban level. The models include walking, cycling and other types of physical activities.
The effects are modelled through health benefits associated with physical activity, road traffic injury risk, and exposure to fine particulate matter ( PM 2.5) air pollution. In addition, some versions of ITHIM also predict changes in CO2 emissions. The health benefits covered include reductions in cardiovascular diseases, depression, diabetes, dementia, breast cancer, and colon cancer. Road traffic injuries are modelled using a risk, distance and speed based model, including differentiated risk levels based on gender and age. The tool models exposure to physical activity, comparing distributions of weekly physical activity under different scenarios. Walking, cycling and other types of physical activities are quantified as Metabolic Equivalent of Task ( MET)  hours per week. In ITHIM version 2 individual exposure to air pollution while walking and cycling is taken into account.
ITHIM offers the opportunity to capture, in addition to mortality:
- Premature mortality (years of life lost - YLL)
- Morbidity (years living with a disability - YLD)
- Combined morbidity and mortality (disability-adjusted life years - DALYs). This is the total of premature mortality and morbidity.
ITHIM is currently used in research and by health and transport professionals to compare the impact of travel patterns, estimate health impacts of various scenarios, and model the impact of interventions, and can work either as stand-alone models, or linked to other models.
Data required for the ITHIM models include population census data (including age and gender), census travel data, and Global Burden of Disease ( GBD) data.
Table 4‑2 Data requirements for ITHIM and potential Scottish data sources
Scottish data sources
Scottish Household Survey
Physical activity data including walking, cycling, household activity and work related activity, by age and gender
The Scottish Health Survey: Chapter 5 Data Activity
Global Burden of Disease - adjusted to take into account population size, age, sex and gender distribution and depending on scale - health data e.g. mortality rates and Ischemic Heart Disease ratios ( IHD)
Census 2011, data
Scotland Health Statistics
Scottish Health survey
Cycling Scotland - Cycling Potential
Cycling Scotland (a charity that aims to increase the uptake of cycling and make it part of everyday life) (Cycling Scotland, 2016) worked together with Steer Davies Gleave and Clackmannanshire Council to develop a methodology for evaluating the potential for higher uptake of cycling in urban areas. The study built on a wide selection of available data to identify areas where cycling levels could potentially be increased with additional support, investment and infrastructure. The tool applies to urban areas with a population higher than 10,000 people and has been run as a pilot study for Clackmannanshire Council. The pilot consists of four modules: environment, schools, tourism and development, and enables the user to weight models based on priorities set by the local authorities. The model considers population density, topography, national cycling network, local cycle network, average road speed, average distance to work, average distance to school, access to services and existing mode shares
Cycling Scotland aims to include additional co-benefits into the methodology by incorporating climate change emissions, health & wellbeing benefits and the economic benefits of active travel.
Quantification of the impact of reductions in car use
Reductions in noise, congestion and air quality pollutants are all linked with reductions in car use. There is overlap here with modal shift to public transport and reductions in the need to travel. Methods to capture the impacts with regard to reductions in car use are therefore discussed in a separate Chapter - Chapter 7.
In terms of data sources to help quantify these impacts, Web-TAG Unit 5.4 draws attention to the use of data from the use of Smarter Choices in the UK Sustainable Travel Towns (Sloman et al., 2010), correspondingly data on level of impacts in the Scottish context could be drawn from the Smarter Choices, Smarter Places study, associated follow on projects, and broader quantitative Scottish studies.
Active travel can offer the potential for very large health benefits from increased physical activity, as discussed in section 4.1. Challenges, however, relate to achieving behavioural change in the groups that could benefit most, including ethnic minorities and women. For example, ethnic minority groups can also suffer higher levels of cardiovascular disease, coronary heart disease and diabetes, and consequently an increased uptake of active travel could lead to even greater social and economic benefits than for the population at large (Transport for London, 2011).
Safety aspects of active travel, cycling in particular, also need to be taken into consideration. Statistics from DfT indicate that there is a gender disparity in cycling accidents, indicating that women might be more likely to experience accidents with HGVs and buses, potentially due to differences in biking patterns and speeds (Transport for London, 2011). Research indicates there might be a gender discrepancy in road fatalities, with women in London up to twice as likely to be killed in collisions involving HGVs (>3.5 tonnes) compared to men despite lower cycling levels (Woodcock et al., 2014).
While women have a higher propensity to walk, they are underrepresented in the number of cyclists in Scotland (Sustrans, 2016). A study by Sustrans identified the following factors as barriers to uptake of cycling for women: not feeling safe, age, lack of fitness and concerns around appearance. 67 % of women identified cycle lanes separated from traffic as the primary measure to increase their cycling, and 21% wanted reduced speed limits for road vehicles (Henry, 2013).
Action has been taken across the UK to consider the role of biological sex and gender identity with regards to cycle uptake and use. One such example includes the 'Beryl's Night' initiative by the Oxford-based Broken Spoke bicycle co-op, providing a space for women and trans people to fix, teach, socialise and learn about bikes and to participate in the wider cycling community (Broken Spoke, 2016).
Active travel such as cycling among the older population can influence health co-benefits and social benefits related to independence and wellbeing by providing a means of engaging with the outdoor environment for relaxation and recreation. Cycling accounts for only 1% of all journeys among those aged 65 and older in the UK, compared to 23% in the Netherlands, 15% in Denmark, and 9% in Germany. CycleBOOM (which ran between 2013 - 2016) was aimed at understanding cycling among the older population and how this affects independence, health and wellbeing in order to advise practitioners and policy makers on how the environment and technologies can be designed to assist people to reconnect with cycling and continue cycling in older age (Black and Street, 2014, Cycle-BOOM, 2016).
Taking forward opportunities and overcoming barriers will involve a greater understanding of behaviour change (Smith et al., 2016) including challenges to sustained change in behaviours (Uttley and Lovelace, 2016) and cultural factors ( e.g. Aldred and Jungnickel, 2014) ensuring that existing interventions are inclusive as possible. In the Scottish context recent research in Glasgow (Clark and Curl, 2016) highlights the potential opportunities for broadening of bicycle hire schemes to ensure inclusivity and uptake by a broader demographic (who may receive greater health benefits) reflecting that the current cycle hire schemes tend to be in areas where there is already a high proportion of people cycling to work. There is emerging research funded by Public Health England on opportunities and barriers for functional walking for disabled people (Living Streets, 2016) and research on the role that electric bikes can play in facilitating active travel in harder to reach groups, ( e.g. Cairns et al., 2015).
4.2 Public transport
Public transport can potentially offer large co-benefits from reductions in congestion and noise. This shift can include moves from car to bus and rail and from road to rail freight. The level of these benefits will depend, however, on the extent of modal shift from existing car and road fleet users. In terms of the academic literature the focus, especially with regard to congestion reduction benefits tends to be on fixed infrastructure related projects typically light or heavy rail. For the latter, the impact of new schemes such as the impact of Manchester Metrolink scheme ( e.g. Senior, 2009) dominates the literature. Bus transport can, however, be included in a mixture of measures, e.g. in relation to improvements associated with the UK Sustainable Travel Towns (Sloman et al., 2010) and Smarter Choices Smarter Places Scotland (Halden et al., 2013).
Modal shift to public transport can be seen as an integrated package of measures including walk and cycle modes. Walking and cycling will be used, for example, to access bus stops and rail stations. The potential for savings is considerable for example, in the Sloman et al. (2010) evaluation of the three UK sustainable travel towns car driver trips by residents fell by 9% per person, while in the Smarter Choices Smarter Places Scotland research statistically significant decreases in the proportion of trips made as a car driver were observed in Barrhead, Dumfries, Kirkintilloch/Lenzie and Larbert/Stenhousemuir, with reduction ranging from 19.4 percentage points to 1.6 percentage points in Glasgow East End (Halden et al., 2013). Furthermore, there is a broad existing literature highlighting the importance of 'locking in' the benefits of modal shift through for example road space reallocation ( e.g. Cairns et al., 2004; Sloman et al; 2010; Skinner et al., 2011). For active travel, public transport, and demand management the suggested savings in congestion reduction are estimated to be £8.4 billion per year for the UK as a whole in 2030 (Smith et al., 2015).
Public transport and car clubs can also offer employment and broader well-being benefits. These benefits are considered further in the section on equalities.
The wider implications of modal shift from plane to train currently receives limited consideration in the literature, and in the Scottish context will predominantly apply to domestic travel. Drawing from the wider evidence relating to the use and value of time, working time availability on trains may be of benefit ( e.g. Lyons et al., 2008) and warrants further investigation. The broader literature suggests the potential for there to be induced travel (D'Alfonso et al., 2016) whereby there is generated demand following improvements ( e.g. improved capacity, speed, comfort and frequency) (Givoni and Dobruszkes, 2013) and this would need to be taken into consideration in any evaluation.
4.2.2 Quantitative approaches
As with modal shift to walking and cycling the potential for reductions in congestion, noise, and air quality pollutants is linked to the potential for a modal shift from the car to these modes. Reflecting the overlap here across the climate change mitigation options this is addressed in Chapter 7. WebTAG provides data on the potential for modal shift from car to rail - Table 1 in Tag Unit A5.4 (Marginal External Costs). Data on shifts from car to bus is captured in a certain extent in guidance on Modelling Smarter Choices ( TAG Unit M5.2) e.g. in relation to new conventional bus which serve the workplace.
Public transport is the main transport alternative to car use, with the 2011 Scottish Census indicating that 52% of non-car users commute (to work and study) by public transport modes, followed by active transport at 42% (Scotland's Census, 2011). Public transport offers a number of opportunities from an equalities perspective. Scotland's concessionary fare scheme ( e.g. Hupert and Galilee, 2015; Rye and Mykura, 2009) is identified as helping reduce social exclusion. This scheme provides free or subsidised travel on buses for those aged over 60 or who have a disability (Transport Scotland, 2016). While innovative shared transport schemes ( e.g. Wright et al., 2009) in rural Highland Scotland offers opportunities in terms of providing access to employment and training in areas which are harder to reach by conventional schemes.
In terms of achieving the broader benefits of public transport, steps need to be taken to ensure that existing barriers are addressed. For example, disabled people can face barriers when using public transport, these can be physical (such as a lack of accessible vehicles), attitudinal (a lack of knowledge among transport staff) and economical (reflecting potential lower incomes) (Rees, 2016). On average, the number of trips made by those with mobility disabilities is significantly fewer than those without and this gap grows as people get older ( DfT, 2012). As Rye and Mykura (2009) note, while concessionary fares reduce cost, other significant barriers to socially inclusive public transport exist. These barriers include the need for suitable facilities such as benches and bus stop shelters, as well as real and perceived safety concerns (Mackett et al., 2008; The Coalition for Racial Equality and Rights, 2008a; Yavuz and Welch, 2010). The lack of awareness and knowledge of the needs of disabled people is also harder to change (Rees, 2016).
For women personal safety can be a barrier, and they tend to self-limit their activities and movement to a larger degree than men due to such perceptions and actual risk (GenderSTE, 2016). Public transport can also serve as the scene for discrimination based on gender identity and sexual orientation. The Diversity Trust (2014) found that 36 % of surveyed respondents had been discriminated against at some point, with 32% of incidents taking place on public transport.
Overcoming barriers to increased use of public transportation and reducing perceived as well as real threats are an essential part of reducing transport inequality and subsequent mitigation of greenhouse gases (Andrich et al., 2013; Hargreaves et al., 2013; Yavuz and Welch, 2010). Here policy makers need to understand the key disadvantaged groups and their travel needs, with engagement with groups essential in the design and implementation of policy (Skinner et al., 2011).
Email: Debbie Sagar