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Air pollution, both ambient and indoor, is one of the most significant causes of poor health for people around the world. The WHO estimates that the combined effect of ambient and household air pollution contributes to some seven million deaths annually worldwide. In Europe the European Environment Agency estimates that 97% of urban populations live in areas with PM2.5 levels above the latest WHO guideline limits, and this is associated with 238,000 excess deaths annually. The European Public Health Alliance estimates that health costs related to air pollution amounts to some 166 billion euros across European cities.
“tackling transport emissions has a key role to play in reducing air pollution”
This impact is seen largely in our towns and cities, with a key cause being emissions from road transport. Yet while transport is a major contributor to air pollution, it is also crucial for the efficient functioning of these cities and their economic vitality. Tackling transport emissions and making our urban transport system more sustainable has a key role to play in reducing air pollution and improving public health.
However, introducing new transport schemes that tackle emissions, such as low emission zones (LEZ) and zero emission zones (ZEZ), are often technically complex and politically challenging. Therefore, building a robust evidence base to support the case for action is crucial to success.
At Ricardo we have advised a number of cities seeking to improve urban air quality by implementing zero or low emissions zones and clean air zones (CAZ). In February 2022, Britain’s first zero emissions zone scheme was launched, covering nine streets in the centre of Oxford, a scheme that Ricardo designed with the council. Our air quality specialists supported London in the assessment of its ultra-low emission zone (ULEZ) (ultra-low emission zone) and have been working with local authorities in Bradford, Southampton and Cardiff to complete CAZ feasibility studies. This experience has helped us understand the challenges and benefits of building strong evidence for air quality action.
Understanding the problem
Having a detailed understanding of the scale and sources of pollution across your city is the key building block of your evidence base. The data needed for this can be both measured and modelled, and the types and approaches to the generation of this data is increasing all the time.
The starting point for many will be measured concentration data from reference monitors and diffusion tubes. We are also now seeing an increasing use of sensor data to provide wider coverage across cities to help understand how pollution varies both temporally and spatially in more detail. But underlying all this measured data needs to be effective quality approval and control (QA/QC) systems and procedures to ensure that the data is robust and can be relied upon.
Complementing this more traditional data measurement, new types of measurements are being used to inform understanding and support modelling. For example, satellite data can be used to help map and understand background levels of pollution, especially for larger areas or regions, where on the ground measurement is impractical or very limited. Another area of measurement in which we are seeing an increase is the use of vehicle remote sensing data to estimate real world tail pipe emissions from vehicles. This approach goes beyond the standard emission factors which might be used for vehicle modelling and provides a detailed understanding of the vehicle fleet operating in a city (data which is often unknown).
Measured data, however, only gives you part of the understanding you need – primarily, the level and distribution of air pollution across your city. What it does not necessarily do is provide detailed insight into what is causing the pollution and in turn, an indication as to where to target action. Modelled data provides this missing part of the picture and comprises two main elements – an emissions inventory and dispersion/chemistry modelling that generates the final concentrations of pollutants. The generation of a good emission inventory requires the collection of activity data on a spatial level such as traffic data, point emission sources from industry and area activity such as residential heating. Some of this data may be collected already (such as national statistics) and some may have to be collected from scratch.
Either way, the benefit of modelled data is that it can provide insight into the variance in the causes of pollution in different areas of your town or city. For example, whether road transport is the main problem, and if so, which vehicle types are the most polluting and what is generating this activity. Modelled data can also be helpful in understanding the variables over which you may or may not have control. A good example here is secondary or transboundary particulates which may be generated from activities many miles from your town or city or indeed from natural sources, and can be a major source of pollution.
Developing options
Armed with a good understanding of the air pollution in your city and what causes it, you can then begin to develop options to tackle the pollution. A first step in this is what might be called influence mapping: namely who is responsible for the different sources and what powers do they have to influence them. For example, an environmental regulator may be the key influencer for industrial emissions or a highways authority might be the key player in managing transport emissions. In either case, it would be possible to identify the responsible organisation and relevant departments, what powers they have and if there are any gaps where there is limited control. This approach can inform the process of communication and dialogue with key stakeholders.
Next, it’s important to look at what is already being done that may impact emissions. For example, are there existing transport policies or energy and climate policies in place? If so, these need to be mapped out, exploring any gaps that might exist. Do existing measures affect key sources of pollution (either positively and negatively), and where could more be done? This approach generates new actions and measures to take forward based on an understanding of the problem and what is already being done. This process should be done with key stakeholders to fully utilise existing knowledge and experience to identify all the possible actions you could take.
This structured exploration of potential options provides a long list of what can be done, providing a full picture of options rather than just jumping on to initial ideas. There is never likely to be only one option that will solve the air pollution problem.
For example, when working with Southampton, Ricardo developed a long list of LEZ scheme options targeting different vehicle types and geographical boundaries, coming up with 26 options in total. To complement this, we looked at alternative schemes that might have similar impacts such as developing a freight consolidation scheme and support for electric vehicles. We also considered different combinations of measures. The aim of this was to ensure we had worked through all possible scenarios to ensure we arrived at the most effective solution which in this case was not the LEZ at all.
Assessing the impact of potential options and solutions
Just having a long list of ideas is not a route to success, it is the necessary to assess the effectiveness of mitigation options and prioritise those that are likely to be most effective. However, this step can be difficult and one that many shy away from. It is often helpful to carry out an initial sifting of a long list using a more qualitative assessment, for example in the form of a multi-criteria assessment (MCA). This can be used to carry out qualitative scoring of options against a number of criteria such as impacts on pollution, practicality of implementing, likely cost, political acceptance and wider impacts on the city’s/town’s economy. This approach can help sift out those measure that may not be acceptable (such as being too restrictive) or potentially too costly for the city/town to implement.
With a shorter more manageable list a more detailed assessment of the options can be carried out. Initially this would focus on the air pollution impact of measures, as this is the primary goal. The key steps to this assessment are:
- The impact on the activity or behaviour
- How this will then affect emissions
- Translating this to the actual impact on pollutant concentrations
The first step is arguably the most difficult – trying to get an understanding, for example, on how many people would switch to electric vehicles with a certain amount of investment in charging infrastructure or how people would react to a low emission zone. Evidence from the implementation of similar schemes elsewhere can be useful here to develop assumptions. You could also look to do specific behavioural response surveys with the those impacted by the measures. scheme. There is also the option to use transport models to explore the activity impact of transport schemes from new bus schemes to how people may divert around LEZs. The better you can characterise behaviour response, the more robust your assessment of the impact of the measures scheme will be.
Modelling the impact of these responses on emissions and concentrations is also a core part of this assessment. Therefore, having established a good understanding of the existing situation provides the basis for assessing your options. Without this modelling capability, only a qualitative approach can be used for impact assessments.
With any modelling assessment there will be uncertainty and behavioural response is usually the main one. Trying to assess this uncertainty and what it might mean for the results is another important aspect of impact assessment. This is generally done using sensitivity analysis where assumptions are flexed to see what the impact might be. For example, if we assume more vehicles divert around a LEZ, then we must assume what impact this might have. In other words, would it reduce the effectiveness of the scheme significantly?
Being able to rapidly model different options and assumptions (sensitivities) for different measures is important to keep this analysis manageable. This requires careful consideration of what models to use and how they are set up so that you can change inputs and re-run efficiently.
Ricardo is advising the City of Warsaw in Poland, funded by the Clean Air Fund, to assess the impacts of different LEZ options. The city is one of the most polluted in Europe – with exposure to air pollution having a health-related cost to society of an estimated 4.2 billion euros every year. It also has one of the highest vehicle ownership rates (859 per 1,000 people) in Europe and has seen a growing influx of vehicles from outside of the city. This has driven the desire by the city to introduce an ambitious LEZ by 2024, but in a way that does not disproportionately impact groups of individuals or businesses.
Our team is modelling the changes in pollutant concentrations which will result from the various LEZ options; assessing the health impacts resulting from these changes in emissions and concentrations; carrying out a cost benefit analysis of the different LEZ options; and considering how these costs and benefits are distributed between different social groups and business sectors. We have built a model which draws on a range of key sources of information including the city’s transport model, satellite data for background pollution and remote sensing vehicle emission data to assess the real-world performance of local vehicles. Information on behavioural response is limited for the project so we’re building on experience from London’s ULEZ and complementing this with sensitivity analysis. The outputs of the analysis will be an important input to the final decision-making process for the city.
Building the business case
Pulling all the relevant information into a business case that justifies the scheme to residents, businesses, key decision makers and funders, is the final step in building evidence to support action. This needs to look at all the benefits and costs for each measure and how these balance, in addition to considering how the benefits and costs are distributed; the equity of the measure.
Understanding the full costs and benefits is what is what is known as a cost benefit analysis, and it aims to value all impacts of a scheme in financial terms so that they can be compared. The costs are not only those associated with the implementation of a scheme but also those incurred by residents and businesses such as costs for upgrading a vehicle to comply with an LEZ. The benefits cover the air quality improvements related to the scheme, but also potentially wider benefits such as reduced running costs from new vehicles or health benefits from shifting to walking and cycling. Such an analysis can be extensive, so it is common to use the principle of proportionate analysis when using this approach: considering what are likely to be the key costs and benefits and focus on quantifying those, while having a more qualitative description of others to complement the main analysis.
Cost benefit analysis, however, only looks at things in aggregate which can then hide any inequity in how those cost and benefits are distributed. For example, do some sectors of society bear higher costs or get greater benefits than others? This analysis is known as distribution analysis and attempts to look at how the costs and benefits are distributed between different social groups. This can for example be done for the air quality benefits by overlaying the change in pollutant concentrations on demographic data to see who may have the greatest benefit.
For example, it is often the case that poorer areas suffer from the worst air pollution and so, action here will have the greatest benefit for disadvantaged groups and so have a benefit in terms of reducing health inequalities.
The distributional analysis can be very important in managing the political challenges of implementing schemes such as LEZs as it helps politicians understand who is affected. It can also be used to develop complementary measures to support those who may be most affected. For example, small businesses may struggle with the costs of upgrading vehicles and so a grant scheme targeting that group can help the success of the scheme by being more politically acceptable. Similarly understanding how traffic might be diverted around an LEZ, who might be affected by this and potential traffic management measures to manage this can again help a scheme to be more accepted.
A good illustration of building a strong business case based on detailed evidence is the work Ricardo carried out for Bradford’s LEZ. As well as carrying out the main air quality assessment of the scheme we provided a cost benefit analysis and distribution analysis. This distributional analysis identified small local freight businesses as a key sector impacted by the scheme. Exploring this further we assessed the costs needed to allow the Bradford Council to upgrade their vehicles to comply with the LEZ and helped develop a grant scheme to support them. Overall, the business case for the LEZ in Bradford was successful at securing 43 million pounds (GBP) in funding from central government for the main scheme and supporting measures.
Communicating for success
Consulting and communicating your ideas for action is the final element in making your actions a success. This goes through the entire process from initial influence mapping, through the development of options to the final consultation on your plans. Again, the evidence you have is important for effective communication and engagement. This allows you to:
- Clearly show what the problem is and where action needs to be targeted
- Explain the options you have considered and how it relates to other policies
- Describe what the benefits and costs are likely to be
- Set out who could be impacted and how you are considering mitigating this
Having clear evidence on these points will help bring key stakeholders along with you and get support rather than opposition for your scheme. People want to know what it will mean for them and how you have considered them, whether they are a business or resident.
Political will is probably the key determinant for effective action on air pollution but having a robust evidence base is a close second. Also, that evidence can help support and build that political will. The tools and experience to help you build this evidence are growing all the time. Make the most of them and develop that informed case for action to achieve cleaner air for all.
