Zero Carbon Design 2030 – our tool for quantifying scope 3 transport emissions

In 2021, the practice made a public Zero Carbon Design 2030 (ZCD2030) commitment, for all our projects to be net zero carbon by 2030. The first step of ZCD2030 has been to establish which parts of the carbon footprint we can directly control and which parts we can influence by working with others.

Before we can begin to address controlling emissions or influence change in the transportation sector, we must first educate ourselves on the sector’s contribution to emissions. According to the Department for Energy Security and Net Zero (DESNZ) Greenhouse Gas (GHG) Inventory, transport produced 26% of the UK’s total emissions in 2021 and remains the country’s largest emitting sector. Additionally, as shown in Figure 1, 91% of emissions from domestic transport came from road vehicles (100 MtCO2e); the biggest contributors to this are cars and taxis, which made up 52% of the emissions from domestic transport (57 MtCO2e). This is followed by heavy goods vehicles (HGVs) (20% of domestic transport emissions, 21 MtCO2e) and vans (17% of emissions, 18 MtCO2e).

Figure 1: % GHG emission by transport (2021)

From conversations I have with colleagues, clients, and friends, the urgency of replacing cars with sustainable travel is understood when such statistics are known. To account for this knowledge gap, our team has developed a tool to estimate transport GHG emissions for end-to-end site user journeys.

Emissions are broken down into scopes 1, 2 and 3. Scope 1 covers emissions from sources that an organisation owns or controls directly (for example, from burning fuel in their fleet of vehicles), scope 2 covers emissions that a company causes indirectly (for example, emissions caused by the generation of electricity that’s used in the company’s buildings). Our focus is on scope 3 emissions as they comprise factors not owned or directly controlled by organisations and not classed as scope 2 emissions, for example, business travel, among other things.

Figure 2: Scope 1,2,3 emissions

After inputting data on the number of site users, percentage of users by each travel mode, and average daily travelling distance per site user, our tool calculates the total number of trips per mode. It estimates the total GHG emissions, including breakdown by vehicles, vehicle sizes and vehicle fuel type. Our tool can also measure the impact that modal shift changes in travel behaviour can have on GHG emissions, for instance, greater numbers of site users travelling via public transport and active travel modes and increases in homeworking practices, while also providing comparisons between existing and future scenarios and scenarios with travel plan interventions in place.

Figure 3 shows our tool being applied to one of our current projects. The site is an existing employment site with 7,460 employees, with the proposals seeking to expand the site to a total of 11,735 employees. The actual mode of travel for employees and the site’s catchment area were available to us, allowing us to calculate the average distance travelled per person. Per the output diagrams and graphs in the image, our tool calculated the number of trips by mode and the total carbon emissions, including the breakdown by mode and the carbon emission per person for the existing and future scenarios. We then estimated a proposed mode of travel seeking a reduction in solo driving by increasing sustainable travel, specifically public transport by bus and train. Then, we ran our tool to show the impact of the increased number of employees onsite with the existing modal split versus the same increase when behavioural changes are made towards sustainable travel alternatives.

Figure 3: Project example

In this example, our tool indicated that the proposed 22% reduction in solo driving in favour of a sustainable mode of travel resulted in a lower carbon emission per person in the future scenario with a proposed modal split when compared to the existing scenario, although the total site carbon emission remained higher in the future when compared to the existing scenario, simply based on the proposed increase in site population.

Our tool is designed to raise awareness of transport-related emissions and provide numerical justification for proposed mitigation measures, such as the shift to sustainable and active travel. However, to make the shift possible, this will require a behavioural change in the way we travel, the support of relevant planning policies, and the availability of reliable, affordable, and connected sustainable alternatives. This is definitely a topic for another blog…