Carbon Neutral Mobility
Masters Thesis
Team of 3 people
Manchester School of Architecture
MArch 2, 2022
AJ Student Prize Nominee
The thesis collaborates with Manchester City council to redevelop Manchester Victoria North. It focuses on offsetting carbon from the transportation sector in the site, one of the largest redevelopment projects in the UK.
The development of a computational tool allows developers and planners to visualise different city designs while comparing their carbon emissions, assisting them on creating a zero carbon city as well as other considerations.
The Climate Crisis & Emergency
The Paris Agreement in 2021 set the target of +1.5-2˚C increase in mean global temperature from pre-industrial period to reduce the effects of global warming. Yet despite the pledges by participating countries, the United Nations’ Environmental Programme (UNEP) noted that current pledges only reduce forecast 2030 emissions by 7.5%, which will increase global temperature by 2.7˚C in 2100, above the 1.5˚C goal. (UNEP, 2021)
|Studies after studies have shown that it is already too late, with current measures we can only limit to a 2˚C increase. we have to go zero carbon NOW in order to save ourselves.
Carbon Neutrality as a solution
Carbon neutrality is a system that allow the emissions released into the atmosphere by one entity's activities being balanced by an equivalent amount being removed by another entity (offsetting). Carbon offsets are then seen as credits that can be purchased and sold.
Done in the correct way, it allows carbon to be removed from the atmosphere while being business friendly.
Manchester City Council set a goal to achieve true zero carbon status by 2038 with MCC leading the way to the largest development in the UK - Victoria North. They asked the question, How to Design a Zero Carbon City?
The transportation sector is the largest emitter in the UK
Connectivity, which covers walkability, micro-mobility, public transport and private motorised transport is an essential consideration for socio-economic activities. However, this can contradict to lower energy and emission strategies. Transport contributes 27% to the UK’s emission and 1/3 of a city’s emissions. While the urban morphology of the city and renewable energy have a positive correlation, combining these with an optimal low carbon mobility design strategy proposes a challenge to be tested in an experimental design approach.
The thesis examines ways of design that can improve accessibility and connectivity while minimising all transport emissions, in efforts to create a carbon neutral transportation network.
Looking at carbon emission data per sector in 2019, transportation sector is responsible for 27% emissions in the UK.
Looking at historical data, even though the overall GHG emissions in the UK had dropped by nearly half, emissions from the transportation sector remained the same.
Within the 27%, private passenger cars accounts for more than half of the emissions.
Manchester Victoria North
Victoria North is a neighbourhood to the north of Manchester City Centre with a population of about 50,000 people. 155 hectares of mostly brownfield or underutilised land a location The development area has been bordered by well-established communities such as New Islington and Ancoats. Victoria North, which is one-third the size of the city centre is referred to as the most significant possibility for residential-led growth by Manchester City Council.
Calculating Existing Carbon Emissions on site
To better understand the existing site conditions, especially carbon emissions, a carbon calculator was created with Grasshopper to estimate the current levels of carbon emissions by different vehicle types.
One of the intersections in an iteration of city generation, showing public transport and walkability
Analysing the proposed masterplan by the client
15,000 new homes are expected to be built. There will be an increase in residential neighbourhoods, retail and service hubs. As density increase, so do the amenities required which includes accessibility to transport links. It is important to study the connections between the proposed neighbourhoods to establish the connectivity and accessibility within the site. Besides the proposal of a new transport hub to improve mobility in and out of the site, new pedestrian routes were also introduced.
Creating a computational tool that allow different parties to test and visualise different city designs based on different inputs
The aim of the tool is to generate different city design generation based on rules developed from various urban theories. These different city generations are then analysed through an agent based model to obtain carbon emission levels and accessibility performance score.
The 2 urban strategies being tested are transit and pedestrian oriented development (TOD & POD), while both neighbourhood strategies focus on accessibility to Transport Infrastructure, Pedestrian Oriented Development gives more emphasis Pedestrians.
Lower frequency but higher density agglomerated at one point
Prioritise public transport & Tram Dependant
Moderate distance by walk, small distance by public transport
Promote walkability on street supported by public transport
Differences
Density & Frequency
Priority
Distance to Amenities
Lowering Carbon Emission Strategies
Higher frequency but lower density, more “centres” scattered
Prioritise walkability & Bus Dependant
Short Walking Distance
Promote walkability primarily supported by active transport (bikes/ scooters)
Design tool user inputs
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The City Designer Tool: A step by step walkthrough
The walkthrough video showcases the different steps and their relevant inputs and how they implement into the tool.
Click to view larger
Using an Agent Based Model to evaluate different city designs
In order to understand how each city design would perform, an agent based model was developed to simulate the movement of 35,000 residents (target population of the client) on the site, with each agent have their own home and work location as well as transport preference and destinations.
|The agent based model simulated the movement of 35,000 people, totalling 140,000 unique trips and transport methods in order to measure the performance of a city design
Generating and analysing performance results
Evaluating a selection of 24 results from different configurations of user inputs, showing 2 examples with performance criteria such as carbon emission, energy use, required renewables to offset etc.
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Performance data
Correlative trend line
|Data shows that POD (pedestrian oriented development) performs better in all categories: lower carbon emissions, higher transport and amenities accessibility score. However, carbon emission increases significantly in POD when transport accessibility increases; and due to the nature of a lower density, it requires more roof coverage to offset the carbon generated.
Pedestrian Oriented Development:
Parallel Road option Generation 1 (Seed 612)
The choice of using pedestrian oriented development produced a tighter urban layout that focuses on inner neighbourhood over inter neighbourhood movement. This strategy also creates an overall lower density city as there are more neighbourhoods that are able to fit into the site, which created more land that is in the highest importance spatially, or more “city centres”. However this also means that the connectivity between 2 neighbourhoods might be worse than transport oriented development.
Transport Oriented Development:
Parallel Road option Generation 1 (Seed 438)
Transport oriented development connect residents mainly through tram, leading to a larger reach and therefore a bigger influence to surrounding areas thus less individual neighbourhood, similar to how current cities are built. Due to one small area acting as the city center for a large area, the agglomeration of amenities, offices and residential buildings is more severe, which creates a very high dense area with a lot of mixed use buildings.
Visualising the different city designs
The tool shows 24 different city generations configured through 4 different selectable inputs by the user. This generates 72 sets of unique results that allow the user to compare between and make decisions on planning.
Design explorer tool
The tool video showcases the UI of the explorer as well as the different user inputs and their results.
