--- title: Integrated Environmental Modelling description: Explore how strategic transport models can integrate local vehicle fleet data, emissions and noise assessment to make environmental impacts a standard model output. image: https://hs.relativegap.com/hubfs/image_gen_99072db6-828c-426e-8a59-73bbca0c59a1-1.png --- [![RelativeGAP](https://hs.relativegap.com/hs-fs/hubfs/logo_final_bl.png?width=2481&height=836&name=logo_final_bl.png "RelativeGAP")](https://relativegap.com/) [![RelativeGAP](https://hs.relativegap.com/hs-fs/hubfs/logo_final_bl.png?width=2481&height=836&name=logo_final_bl.png "RelativeGAP")](https://relativegap.com/) # Environmental Modelling Beyond Traffic Forecasting Strategic transport models are increasingly expected to tell us more than how many vehicles will use a road or how travel patterns might change. Transport interventions can influence emissions, noise and wider environmental conditions, yet these impacts are often assessed through separate processes after the main transport modelling has been completed. At RelativeGAP, we have been exploring a different approach: integrating environmental assessment directly into the strategic transport modelling workflow. Developing this capability has required considerably more than implementing an emissions calculation methodology. It has involved research into environmental assessment methods, processing detailed local vehicle fleet information, disaggregating model demand, developing emissions and noise calculation procedures, and establishing automated calibration, validation and reporting workflows. The objective is relatively simple: once a transport scenario has been prepared and assigned, environmental indicators should become a standard model output, allowing transport and environmental impacts to be considered together. ## Building the Environmental Modelling Framework The starting point is still a robust strategic transport model. Environmental calculations depend directly on modelled traffic volumes, vehicle composition, speeds and operating conditions, meaning weaknesses in the underlying transport model can translate directly into environmental results. The next challenge is representing the vehicles using the network. Local vehicle registration and fleet datasets can be processed to understand characteristics such as vehicle category, fuel or propulsion technology, age and other attributes influencing environmental performance. This information can then be used to disaggregate modelled demand into more detailed vehicle groups rather than applying generic fleet assumptions across all traffic. This becomes particularly important when looking into the future. Changes in fleet composition, including the transition towards newer technologies and electric vehicles, can substantially change environmental outcomes even where overall travel demand remains similar. Environmental forecasting therefore requires assumptions about both future transport demand and future vehicle fleets. Once these foundations are established, traffic assignment outputs can be connected to the environmental calculation framework at network link level. ![Environmental_module2](https://hs.relativegap.com/hs-fs/hubfs/Environmental_module2.png?width=1626&height=967&name=Environmental_module2.png "Environmental_module2") ## From Traffic Assignment to Environmental Impact For air emissions, our development has focused on implementing the **COPERT methodology** within a strategic modelling environment. An important characteristic of COPERT is that road transport emissions extend beyond conventional hot exhaust emissions. The methodology can also represent cold start emissions, evaporative emissions and non-exhaust particulate matter associated with tyre wear, brake wear and road surface abrasion. This creates a more complete representation of the environmental consequences of road traffic, particularly when combined with detailed information about vehicle fleet composition and network operating conditions. Alongside emissions, we developed a dedicated traffic noise assessment process based on the **RLS-19 methodology**. This allows modelled traffic conditions and road characteristics to be translated into noise indicators, enabling air emissions and traffic noise to be assessed from the same underlying strategic model scenarios. The resulting workflow therefore connects: **transport demand → traffic assignment → vehicle fleet → emissions and noise → environmental indicators** Rather than operating as independent modelling exercises, these components become part of one integrated assessment framework. ## Key Technical Insights Environmental modelling starts with the vehicle fleet and traffic volume alone cannot adequately explain environmental impact. Two links carrying the same number of vehicles can produce different emissions depending on vehicle types, technologies, age profiles and operating conditions. Processing local vehicle fleet and registration data is therefore an important part of environmental model development. Translating these datasets into model compatible vehicle categories provides a much stronger foundation than relying solely on generic fleet assumptions. ## Demand disaggregation matters Strategic transport models often contain considerably fewer demand segments than are required for detailed environmental calculations. An important methodological step is therefore translating assigned traffic into more detailed environmental vehicle categories. Depending on the available data, this can range from relatively simple fleet-based splitting to more sophisticated disaggregation informed by observed vehicle composition across different parts of the network. The appropriate level of complexity should ultimately reflect both the available evidence and the purpose of the assessment. ## Calibration cannot stop with the transport model A transport model may meet conventional traffic calibration and validation requirements without necessarily producing the best possible environmental representation. Environmental modelling introduces another layer of quality assurance. Traffic flows, speeds, fleet assumptions and environmental parameters need to be reviewed together, while observed traffic and environmental measurements can provide an additional basis for testing and refining the resulting calculations. This makes environmental validation part of the modelling process rather than simply a check on the final outputs. ![image_gen_99072db6-828c-426e-8a59-73bbca0c59a1-1](https://hs.relativegap.com/hs-fs/hubfs/image_gen_99072db6-828c-426e-8a59-73bbca0c59a1-1.png?width=600&height=369&name=image_gen_99072db6-828c-426e-8a59-73bbca0c59a1-1.png "image_gen_99072db6-828c-426e-8a59-73bbca0c59a1-1") ## Non exhaust emissions should not be overlooked The transition towards cleaner vehicle technologies will substantially change the composition of road transport emissions, but it does not eliminate every environmental impact associated with road traffic. Tyre wear, brake wear and road surface abrasion remain relevant sources of particulate matter. Including these components alongside exhaust, cold start and evaporative emissions provides a more comprehensive basis for comparing future transport and fleet scenarios. ## Automation changes how environmental assessment can be used Perhaps the most important development is not any individual calculation method, but the integration of the complete process. Once vehicle fleet processing, emissions calculations, noise assessment and output generation are embedded within the strategic model workflow, environmental assessment no longer needs to be undertaken as a separate exercise for every scenario. The same process can be applied consistently across many model tests, making it much easier to compare infrastructure schemes, demand management measures, changes in vehicle technology and other transport policies against both conventional transport and environmental indicators. ## From Additional Assessment to Standard Model Output This integration changes the role environmental modelling can play in transport planning. Traditionally, detailed environmental assessment may be commissioned after transport modelling has identified a preferred option or a relatively small number of scenarios. An integrated framework makes it possible to consider environmental performance much earlier and much more frequently. A model test can potentially provide traffic flows, journey times and demand responses alongside emissions and noise indicators through the same automated workflow.  This does not replace specialist environmental assessment where detailed local analysis is required. Instead, it gives strategic transport modelling another dimension, allowing environmental consequences to inform option development and policy testing from an earlier stage.  For us, this is the most interesting outcome of the development: environmental impact becomes part of understanding how the transport system performs, rather than an additional calculation undertaken afterwards.  ## Developer's Perspective  *‘For me, one of the most exciting parts of this development was turning environmental assessment into something that works directly alongside the strategic transport model. A significant amount of work went into connecting traffic assignment outputs with local vehicle fleet data, emissions and noise calculations, and then automating the complete process. The result is that once a scenario has been prepared and assigned, environmental indicators can be produced as standard model outputs rather than through a separate assessment exercise. This makes it much easier to compare the environmental consequences of different transport scenarios consistently and brings sustainability considerations directly into everyday modelling and option testing.’*   ![rg_033-2](https://hs.relativegap.com/hs-fs/hubfs/rg_033-2.jpeg?width=165&height=165&name=rg_033-2.jpeg "rg_033-2") #### Anett Gosztola **About the Author of this Article** Since joining RelativeGAP as an intern in 2020, Anett Gosztola has grown into a highly skilled transport modeller, combining strategic modelling expertise with a strong interest in programming, behavioural modelling and the development of new methodologies. She has played an important role in several of our research and development initiatives, including the integration of environmental assessment into strategic transport modelling. Alongside her project work, Anett is pursuing a PhD in Transport Sciences through a university and industry collaboration with RelativeGAP. Her research focuses on developing assignment approaches that better represent real world traveller behaviour, particularly short term route choice decisions and responses to changing network conditions. [![RelativeGAP](https://hs.relativegap.com/hs-fs/hubfs/logo_final_bl.png?width=2481&height=836&name=logo_final_bl.png "RelativeGAP")](https://relativegap.com/) Suite 5, 5th Floor, City Reach 5 Greenwich View Place London, E14 9NN,  United Kingdom [info@relativegap.com](mailto:info@relativegap.com) +44 (0)74 9245 2112 all rights reserved ©